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Posted to commits@hudi.apache.org by "jonvex (via GitHub)" <gi...@apache.org> on 2025/08/12 15:33:27 UTC
[PR] Col stats new schema [hudi]
jonvex opened a new pull request, #13711:
URL: https://github.com/apache/hudi/pull/13711
### Change Logs
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### Impact
_Describe any public API or user-facing feature change or any performance impact._
### Risk level (write none, low medium or high below)
_If medium or high, explain what verification was done to mitigate the risks._
### Documentation Update
_Describe any necessary documentation update if there is any new feature, config, or user-facing change. If not, put "none"._
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### Contributor's checklist
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3282870172
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3267696262
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3282624991
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3276771766
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2359606800
##########
hudi-common/src/main/java/org/apache/hudi/avro/HoodieAvroWrapperUtils.java:
##########
@@ -238,4 +234,120 @@ private static Pair<Boolean, String> getIsValueWrapperObfuscated(Object statsVal
}
return Pair.of(false, null);
}
+
+ public enum PrimitiveWrapperType {
+ V1(Object.class, HoodieAvroWrapperUtils::wrapValueIntoAvro, HoodieAvroWrapperUtils::unwrapAvroValueWrapper, GenericRecord.class),
+ NULL(Void.class, HoodieAvroWrapperUtils::wrapNull, HoodieAvroWrapperUtils::unwrapNull, Void.class),
Review Comment:
OK, let's keep it for completeness.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3314001177
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3305241850
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3308546477
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2364512208
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/utils/SparkMetadataWriterUtils.java:
##########
@@ -206,6 +212,16 @@ public static ExpressionIndexComputationMetadata getExpressionIndexRecordsUsingC
: new ExpressionIndexComputationMetadata(colStatRecords);
}
+ private static SparkValueMetadata getValueMetadataFromColumnRangeDataset(Dataset<Row> dataset, HoodieIndexVersion indexVersion) {
Review Comment:
then there would be no point to this method. I'm leaving as is
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3309894277
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3267728652
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3288869389
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3194562646
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3194024154
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2302297589
##########
hudi-hadoop-common/src/main/java/org/apache/parquet/avro/HoodieAvroSchemaConverter.java:
##########
@@ -0,0 +1,593 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.parquet.avro;
+
+import org.apache.avro.LogicalType;
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+
+import org.apache.hadoop.conf.Configuration;
+import org.apache.parquet.schema.ConversionPatterns;
+import org.apache.parquet.schema.GroupType;
+import org.apache.parquet.schema.LogicalTypeAnnotation;
+import org.apache.parquet.schema.MessageType;
+import org.apache.parquet.schema.PrimitiveType;
+import org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName;
+import org.apache.parquet.schema.Type;
+import org.apache.parquet.schema.Types;
+import org.apache.parquet.schema.LogicalTypeAnnotation.UUIDLogicalTypeAnnotation;
+
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.List;
+import java.util.Map;
+import java.util.Set;
+
+import static org.apache.avro.JsonProperties.NULL_VALUE;
+import static org.apache.parquet.avro.AvroReadSupport.READ_INT96_AS_FIXED;
+import static org.apache.parquet.avro.AvroReadSupport.READ_INT96_AS_FIXED_DEFAULT;
+import static org.apache.parquet.avro.AvroRecordConverter.getRuntimeAvroVersion;
+import static org.apache.parquet.avro.AvroWriteSupport.WRITE_FIXED_AS_INT96;
+import static org.apache.parquet.avro.AvroWriteSupport.WRITE_OLD_LIST_STRUCTURE;
+import static org.apache.parquet.avro.AvroWriteSupport.WRITE_OLD_LIST_STRUCTURE_DEFAULT;
+import static org.apache.parquet.avro.AvroWriteSupport.WRITE_PARQUET_UUID;
+import static org.apache.parquet.avro.AvroWriteSupport.WRITE_PARQUET_UUID_DEFAULT;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.TimeUnit.MICROS;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.TimeUnit.MILLIS;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.dateType;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.decimalType;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.enumType;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.stringType;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.timeType;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.timestampType;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.uuidType;
+import static org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.BINARY;
+import static org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.BOOLEAN;
+import static org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.DOUBLE;
+import static org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.FIXED_LEN_BYTE_ARRAY;
+import static org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.FLOAT;
+import static org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.INT32;
+import static org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.INT64;
+import static org.apache.parquet.schema.Type.Repetition.REPEATED;
+
+/**
+ * <p>
+ * Converts an Avro schema into a Parquet schema, or vice versa. See package
+ * documentation for details of the mapping.
+ * </p>
+ */
+@SuppressWarnings("all")
+public class HoodieAvroSchemaConverter {
Review Comment:
Add more javadocs on why this is needed, where the code is copied from, additional changes in Hudi, and how to maintain this class?
##########
hudi-common/src/test/resources/nullWrong.avsc:
##########
@@ -197,7 +197,48 @@
},
"null"
]
- }
+ },
+ {
+ "name": "timeMicroField",
Review Comment:
Is this needed as it's for `nullWrong` schema which seems to be unrelated?
##########
hudi-hadoop-common/src/main/java/org/apache/hudi/common/util/OrcUtils.java:
##########
@@ -257,7 +258,7 @@ public Schema readAvroSchema(HoodieStorage storage, StoragePath filePath) {
}
@Override
- public List<HoodieColumnRangeMetadata<Comparable>> readColumnStatsFromMetadata(HoodieStorage storage, StoragePath filePath, List<String> columnList) {
+ public List<HoodieColumnRangeMetadata<Comparable>> readColumnStatsFromMetadata(HoodieStorage storage, StoragePath filePath, List<String> columnList, HoodieIndexVersion indexVersion) {
Review Comment:
Similar here on avoiding `indexVersion`
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/index/bloom/HoodieBloomIndex.java:
##########
@@ -231,12 +231,13 @@ protected List<Pair<String, BloomIndexFileInfo>> loadColumnRangesFromMetaIndex(
List<Pair<String, BloomIndexFileInfo>> result = new ArrayList<>(fileToColumnStatsMap.size());
for (Map.Entry<Pair<String, String>, HoodieMetadataColumnStats> entry : fileToColumnStatsMap.entrySet()) {
+ ValueMetadata valueMetadata = ValueMetadata.getValueMetadata(entry.getValue().getValueType());
result.add(Pair.of(entry.getKey().getLeft(),
new BloomIndexFileInfo(
partitionAndFileNameToFileId.get(entry.getKey()),
// NOTE: Here we assume that the type of the primary key field is string
- unwrapAvroValueWrapper(entry.getValue().getMinValue()).toString(),
- unwrapAvroValueWrapper(entry.getValue().getMaxValue()).toString()
+ valueMetadata.unwrapValue(entry.getValue().getMinValue()).toString(),
+ valueMetadata.unwrapValue(entry.getValue().getMaxValue()).toString()
Review Comment:
For ensuring backwards compatibility through tests, could you generate test artifacts/tables by using 0.15.0 and 1.0.2 release (and from this PR) with column stats enabled and columns of different primitive and logical types (use MOR with log files), and used that for validating col stats reading and data skipping? That'll give us much more confidence on compatibility.
##########
hudi-hadoop-common/src/main/java/org/apache/hudi/common/util/ParquetUtils.java:
##########
@@ -473,7 +481,10 @@ private <T extends Comparable<T>> HoodieColumnRangeMetadata<T> getColumnRangeInF
.reduce(HoodieColumnRangeMetadata::merge).get();
}
- private static Comparable<?> convertToNativeJavaType(PrimitiveType primitiveType, Comparable<?> val) {
+ private static Comparable<?> convertToNativeJavaType(PrimitiveType primitiveType, Comparable<?> val, ValueMetadata valueMetadata) {
+ if (valueMetadata.getValueType() != ValueType.V1) {
+ return valueMetadata.standardizeJavaTypeAndPromote(val);
+ }
Review Comment:
Could `ParquetUtils#readColumnStatsFromMetadata` avoid checking the value type or index version and let the caller to do the conversion, i.e., reading parquet metadata and returning the raw stats should not care about the Hudi-related semantics?
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3321050760
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3320538321
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2354097524
##########
hudi-utilities/src/test/resources/streamer-config/source-timestamp-millis.avsc:
##########
@@ -0,0 +1,162 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+{
+ "type" : "record",
+ "name" : "triprec",
+ "fields" : [
+ {
+ "name": "timestamp",
+ "type": "long"
+ },
+ {
+ "name": "_row_key",
+ "type": "string"
+ },
+ {
+ "name": "partition_path",
+ "type": "string"
+ },
+ {
+ "name": "trip_type",
+ "type": {
+ "type": "enum",
+ "name": "TripType",
+ "symbols": [
+ "UNKNOWN",
+ "UBERX",
+ "BLACK"
+ ],
+ "default": "UNKNOWN"
+ }
+ },
+ {
+ "name": "rider",
+ "type": "string"
+ },
+ {
+ "name": "driver",
+ "type": "string"
+ },
+ {
+ "name": "begin_lat",
+ "type": "double"
+ },
+ {
+ "name": "begin_lon",
+ "type": "double"
+ },
+ {
+ "name": "end_lat",
+ "type": "double"
+ },
+ {
+ "name": "end_lon",
+ "type": "double"
+ },
+ {
+ "name": "distance_in_meters",
+ "type": "int"
+ },
+ {
+ "name": "seconds_since_epoch",
+ "type": "long"
+ },
+ {
+ "name": "weight",
+ "type": "float"
+ },
+ {
+ "name": "nation",
+ "type": "bytes"
+ },
+ {
+ "name": "current_date",
+ "type": {
+ "type": "int",
+ "logicalType": "date"
+ }
+ },
+ {
+ "name": "current_ts",
+ "type": {
+ "type": "long",
+ "logicalType": "timestamp-millis"
Review Comment:
No, the reason this works is that we're using an existing type in the datagen. Otherwise we need a new schema. the other test covers all the types. I have a standalone for this one because that was the type that was asked for
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2350297406
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/utils/SparkValueMetadata.java:
##########
@@ -0,0 +1,230 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.client.utils;
+
+import org.apache.hudi.SparkAdapterSupport$;
+import org.apache.hudi.avro.ValueMetadata;
+import org.apache.hudi.avro.ValueType;
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.ArrayComparable;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.spark.sql.types.ArrayType;
+import org.apache.spark.sql.types.BinaryType;
+import org.apache.spark.sql.types.BooleanType;
+import org.apache.spark.sql.types.ByteType;
+import org.apache.spark.sql.types.CharType;
+import org.apache.spark.sql.types.DataType;
+import org.apache.spark.sql.types.DateType;
+import org.apache.spark.sql.types.Decimal;
+import org.apache.spark.sql.types.DecimalType;
+import org.apache.spark.sql.types.DoubleType;
+import org.apache.spark.sql.types.FloatType;
+import org.apache.spark.sql.types.IntegerType;
+import org.apache.spark.sql.types.LongType;
+import org.apache.spark.sql.types.NullType;
+import org.apache.spark.sql.types.ShortType;
+import org.apache.spark.sql.types.StringType;
+import org.apache.spark.sql.types.TimestampType;
+import org.apache.spark.sql.types.VarcharType;
+
+import java.sql.Date;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.util.Arrays;
+
+public class SparkValueMetadata extends ValueMetadata {
+
+ private final DataType dataType;
+
+ protected SparkValueMetadata(ValueType valueType, DataType dataType) {
+ super(valueType);
+ this.dataType = dataType;
+ }
+
+ public Comparable convertSparkToJava(Object value) {
+ return convertSparkToJava(value, true);
+ }
+
+ public static SparkValueMetadata getValueMetadata(DataType dataType, HoodieIndexVersion indexVersion) {
+ if (indexVersion.lowerThan(HoodieIndexVersion.V2)) {
+ return SparkV1EmptyMetadata.get();
+ }
+ if (dataType == null) {
+ return new SparkValueMetadata(ValueType.NULL, null);
+ }
+ ValueType valueType = fromDataType(dataType);
+ if (valueType == ValueType.DECIMAL) {
+ return new SparkDecimalMetadata((DecimalType) dataType);
+ } else {
+ return new SparkValueMetadata(valueType, dataType);
+ }
+ }
+
+ private static ValueType fromDataType(DataType dataType) {
+ return fromDataType(dataType, true);
+ }
+
+ private static ValueType fromDataType(DataType dataType, boolean root) {
+ if (dataType instanceof NullType) {
+ return ValueType.NULL;
+ } else if (dataType instanceof BooleanType) {
+ return ValueType.BOOLEAN;
+ } else if (dataType instanceof IntegerType || dataType instanceof ShortType || dataType instanceof ByteType) {
+ return ValueType.INT;
+ } else if (dataType instanceof LongType) {
+ return ValueType.LONG;
+ } else if (dataType instanceof FloatType) {
+ return ValueType.FLOAT;
+ } else if (dataType instanceof DoubleType) {
+ return ValueType.DOUBLE;
+ } else if (dataType instanceof StringType || dataType instanceof CharType || dataType instanceof VarcharType) {
+ return ValueType.STRING;
+ } else if (dataType instanceof TimestampType) {
Review Comment:
Also how's `timestamp-millis` logical type in Avro is handled in the Spark datasource/SQL write path? Is `TimestampType` used or a different type used?
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2352833905
##########
hudi-common/src/main/java/org/apache/hudi/avro/processors/Parser.java:
##########
@@ -46,21 +48,19 @@ public Pair<Boolean, Object> handleStringValue(String value) {
public static class DateParser extends Parser {
- private static final long MILLI_SECONDS_PER_DAY = 86400000;
-
@Override
public Pair<Boolean, Object> handleNumberValue(Number value) {
- return Pair.of(true, new java.sql.Date(value.intValue() * MILLI_SECONDS_PER_DAY));
+ return Pair.of(true, LocalDate.ofEpochDay(value.intValue()));
Review Comment:
What's the motivation behind this change? I see this is used in Json to Row converter and I'm wondering if this can change the data to be written to a Hudi table.
##########
hudi-common/src/main/java/org/apache/hudi/avro/HoodieAvroUtils.java:
##########
@@ -1150,12 +1151,33 @@ public static Object rewritePrimaryType(Object oldValue, Schema oldSchema, Schem
case NULL:
case BOOLEAN:
case INT:
- case LONG:
case FLOAT:
case DOUBLE:
case BYTES:
case STRING:
return oldValue;
+ case LONG:
+ if (oldSchema.getLogicalType() != newSchema.getLogicalType()) {
+ if (oldSchema.getLogicalType() instanceof LogicalTypes.TimestampMillis) {
+ if (newSchema.getLogicalType() instanceof LogicalTypes.TimestampMicros) {
+ return DateTimeUtils.millisToMicros((Long) oldValue);
+ }
+ } else if (oldSchema.getLogicalType() instanceof LogicalTypes.TimestampMicros) {
+ if (newSchema.getLogicalType() instanceof LogicalTypes.TimestampMillis) {
+ return DateTimeUtils.microsToMillis((Long) oldValue);
+ }
+ } else if (oldSchema.getLogicalType() instanceof LogicalTypes.LocalTimestampMillis) {
+ if (newSchema.getLogicalType() instanceof LogicalTypes.LocalTimestampMicros) {
+ return DateTimeUtils.millisToMicros((Long) oldValue);
+ }
+ } else if (oldSchema.getLogicalType() instanceof LogicalTypes.LocalTimestampMicros) {
+ if (newSchema.getLogicalType() instanceof LogicalTypes.LocalTimestampMillis) {
+ return DateTimeUtils.microsToMillis((Long) oldValue);
+ }
+ }
Review Comment:
Do we have tests around schema evolution for these cases (not a blocking issue to resolve for this PR)?
##########
hudi-common/src/main/java/org/apache/hudi/avro/ConvertingGenericData.java:
##########
@@ -128,7 +125,8 @@ public boolean validate(Schema schema, Object datum) {
case LONG:
return isLong(datum)
|| TIME_MICROS_CONVERSION.getConvertedType().isInstance(datum)
- || TIMESTAMP_MICROS_CONVERSION.getConvertedType().isInstance(datum);
+ || TIMESTAMP_MICROS_CONVERSION.getConvertedType().isInstance(datum)
+ || LOCAL_TIMESTAMP_MICROS_CONVERSION.getConvertedType().isInstance(datum);
Review Comment:
Should `TIME_MILLIS_CONVERSION`, `LOCAL_TIMESTAMP_MILLIS_CONVERSION`, and `TIMESTAMP_MILLIS_CONVERSION` also be handled or they are handled somewhere else?
##########
hudi-client/hudi-spark-client/src/test/java/org/apache/hudi/client/functional/TestHoodieBackedTableMetadata.java:
##########
@@ -350,7 +375,7 @@ public void testMetadataRecordKeyExcludeFromPayload(final HoodieTableType tableT
* plan has not been successfully executed before the new one is scheduled.
*/
@ParameterizedTest
- @CsvSource({"COPY_ON_WRITE,6", "COPY_ON_WRITE,8", "MERGE_ON_READ,6", "MERGE_ON_READ,8"})
+ @MethodSource("testMetadataTableKeyGeneratorArgs")
Review Comment:
How much is the increased time for running all tests compared to before? Would like to make sure the time to finish these tests is still reasonable.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2352935167
##########
hudi-common/src/main/java/org/apache/hudi/avro/AvroSchemaUtils.java:
##########
@@ -423,22 +428,24 @@ private static Schema pruneDataSchemaInternal(Schema dataSchema, Schema required
}
List<Schema.Field> newFields = new ArrayList<>();
for (Schema.Field requiredSchemaField : requiredSchema.getFields()) {
- Schema.Field dataSchemaField = dataSchema.getField(requiredSchemaField.name());
- if (dataSchemaField != null) {
- Schema.Field newField = new Schema.Field(
- dataSchemaField.name(),
- pruneDataSchema(dataSchemaField.schema(), requiredSchemaField.schema(), Collections.emptySet()),
- dataSchemaField.doc(),
- dataSchemaField.defaultVal()
- );
- newFields.add(newField);
- } else if (mandatoryFields.contains(requiredSchemaField.name())) {
+ if (mandatoryFields.contains(requiredSchemaField.name())) {
Review Comment:
The reason for this change is because of timestamp partition column. Sometimes we read it as a string even when the table schema has it as a long etc.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3300020266
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3300381167
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3185143998
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## CI report:
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3185315745
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3189916598
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3193082825
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3293727173
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3288756085
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3288969484
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2357276756
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/metadata/HoodieBackedTableMetadataWriter.java:
##########
@@ -575,10 +576,11 @@ private Pair<List<String>, Pair<Integer, HoodieData<HoodieRecord>>> initializeCo
if (partitionIdToAllFilesMap.isEmpty()) {
return Pair.of(Collections.emptyList(), Pair.of(fileGroupCount, engineContext.emptyHoodieData()));
}
+ HoodieIndexVersion columnStatsIndexVersion = existingIndexVersionOrDefault(PARTITION_NAME_COLUMN_STATS, dataMetaClient);
// Find the columns to index
final List<String> columnsToIndex = new ArrayList<>(HoodieTableMetadataUtil.getColumnsToIndex(dataMetaClient.getTableConfig(),
dataWriteConfig.getMetadataConfig(), tableSchema, true,
- Option.of(dataWriteConfig.getRecordMerger().getRecordType())).keySet());
+ Option.of(dataWriteConfig.getRecordMerger().getRecordType()), columnStatsIndexVersion).keySet());
Review Comment:
discussed that we won't do this because the caller usually collects the col ranges right after getting the cols to index, and they need the index version for that as well
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2352874709
##########
hudi-common/src/main/java/org/apache/hudi/avro/AvroSchemaUtils.java:
##########
@@ -423,22 +428,24 @@ private static Schema pruneDataSchemaInternal(Schema dataSchema, Schema required
}
List<Schema.Field> newFields = new ArrayList<>();
for (Schema.Field requiredSchemaField : requiredSchema.getFields()) {
- Schema.Field dataSchemaField = dataSchema.getField(requiredSchemaField.name());
- if (dataSchemaField != null) {
- Schema.Field newField = new Schema.Field(
- dataSchemaField.name(),
- pruneDataSchema(dataSchemaField.schema(), requiredSchemaField.schema(), Collections.emptySet()),
- dataSchemaField.doc(),
- dataSchemaField.defaultVal()
- );
- newFields.add(newField);
- } else if (mandatoryFields.contains(requiredSchemaField.name())) {
+ if (mandatoryFields.contains(requiredSchemaField.name())) {
Review Comment:
What is the case where the behavior is changed? Add a unit test on that case (I see `TestAvroSchemaUtils` with tests covering this method is not change)?
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2353097916
##########
hudi-common/src/main/java/org/apache/hudi/avro/processors/Parser.java:
##########
@@ -46,21 +48,19 @@ public Pair<Boolean, Object> handleStringValue(String value) {
public static class DateParser extends Parser {
- private static final long MILLI_SECONDS_PER_DAY = 86400000;
-
@Override
public Pair<Boolean, Object> handleNumberValue(Number value) {
- return Pair.of(true, new java.sql.Date(value.intValue() * MILLI_SECONDS_PER_DAY));
+ return Pair.of(true, LocalDate.ofEpochDay(value.intValue()));
Review Comment:
ok, I was able to figure this out finally
I think this is what happened:
I had to change the row processing for local timestamp because we added timestamp ntz to the schema converters so timestamp ntz now is a type instead of just a long. So anyways, I must have run the entire class and saw that this test was failing as well and fixed it.
So why was this test failing? It actually also fails on master when I run it on my machine?
Why is that? It's because of timezones!!
This is what happens when I run this test on master with my default timezone (new york):
<img width="1710" height="940" alt="image" src="https://github.com/user-attachments/assets/b46d3546-f6d1-48bb-9440-1f85ba2ad6e1" />
Now I configure the test with UTC timezone:
<img width="1253" height="695" alt="image" src="https://github.com/user-attachments/assets/88e819fd-0bef-45dd-a2cb-2fbe01b3f7ad" />
And it passes:
<img width="1715" height="912" alt="image" src="https://github.com/user-attachments/assets/3aa9e332-864f-4f74-9e7d-92b12da27880" />
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3301249123
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3288761269
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2349996170
##########
hudi-client/hudi-client-common/src/test/java/org/apache/hudi/table/upgrade/TestEightToNineUpgradeHandler.java:
##########
@@ -305,7 +306,7 @@ private void assertPayloadClassChange(Map<ConfigProperty, String> propertiesToAd
}
}
- @Test
+ @Disabled
Review Comment:
Why are these tests disabled? Will the upgrade and downgrade handling of column stats index fix these tests?
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/io/HoodieAppendHandle.java:
##########
@@ -427,15 +429,17 @@ protected void processAppendResult(AppendResult result, Option<HoodieLogBlock> d
updateWriteStatus(result, stat);
if (config.isMetadataColumnStatsIndexEnabled()) {
+ HoodieIndexVersion indexVersion = HoodieTableMetadataUtil.existingIndexVersionOrDefault(PARTITION_NAME_COLUMN_STATS, hoodieTable.getMetaClient());
Set<String> columnsToIndexSet = new HashSet<>(HoodieTableMetadataUtil
.getColumnsToIndex(hoodieTable.getMetaClient().getTableConfig(),
config.getMetadataConfig(), Lazy.eagerly(Option.of(writeSchemaWithMetaFields)),
- Option.of(this.recordMerger.getRecordType())).keySet());
+ Option.of(this.recordMerger.getRecordType()), indexVersion).keySet());
Review Comment:
Could `HoodieTableMetadataUtil#getColumnsToIndex` take hoodieTable.getMetaClient() and figure out the index version within the method `HoodieTableMetadataUtil#getColumnsToIndex`? Similar for `collectColumnRangeMetadata` so that the logic of fetching index version is not present in `HoodieAppendHandle`.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2353665825
##########
hudi-common/src/main/java/org/apache/hudi/common/util/FileFormatUtils.java:
##########
@@ -64,10 +66,24 @@ public abstract class FileFormatUtils {
* @param fileColumnRanges List of column range statistics for each file in a partition
*/
public static <T extends Comparable<T>> HoodieColumnRangeMetadata<T> getColumnRangeInPartition(String relativePartitionPath,
+ String columnName,
@Nonnull List<HoodieColumnRangeMetadata<T>> fileColumnRanges,
- Map<String, Schema> colsToIndexSchemaMap) {
+ Map<String, Schema> colsToIndexSchemaMap,
+ HoodieIndexVersion indexVersion) {
ValidationUtils.checkArgument(!fileColumnRanges.isEmpty(), "fileColumnRanges should not be empty.");
+ if (indexVersion.greaterThanOrEquals(HoodieIndexVersion.V2)) {
+ ValueMetadata valueMetadata = ValueMetadata.getValueMetadata(colsToIndexSchemaMap.get(columnName), indexVersion);
+ return fileColumnRanges.stream()
+ .map(e -> {
+ T minValue = (T) valueMetadata.standardizeJavaTypeAndPromote(e.getMinValue());
+ T maxValue = (T) valueMetadata.standardizeJavaTypeAndPromote(e.getMaxValue());
+ return HoodieColumnRangeMetadata.create(
+ relativePartitionPath, e.getColumnName(), minValue, maxValue, e.getNullCount(), e.getValueCount(), e.getTotalSize(),
+ e.getTotalUncompressedSize(), valueMetadata);
+ }).reduce(HoodieColumnRangeMetadata::merge).orElseThrow(() -> new HoodieException("MergingColumnRanges failed."));
+ }
+ // we are reducing using merge so IDK why we think there are multiple cols that need to go through schema evolution
Review Comment:
AFAIK the merging of column stats should only happen for partition stats, i.e., merging the stats of multiple files in a partition. Some type promotions in schema evolution should not happen on min and max values, e.g., int -> string, where the ordering can be different, e.g., 2 compared to 11, vs "2" compared to "11".
##########
hudi-common/src/main/java/org/apache/hudi/avro/HoodieAvroWrapperUtils.java:
##########
@@ -238,4 +234,120 @@ private static Pair<Boolean, String> getIsValueWrapperObfuscated(Object statsVal
}
return Pair.of(false, null);
}
+
+ public enum PrimitiveWrapperType {
+ V1(Object.class, HoodieAvroWrapperUtils::wrapValueIntoAvro, HoodieAvroWrapperUtils::unwrapAvroValueWrapper, GenericRecord.class),
+ NULL(Void.class, HoodieAvroWrapperUtils::wrapNull, HoodieAvroWrapperUtils::unwrapNull, Void.class),
Review Comment:
Is this used? My understanding is that the min and max values do not consider nulls.
##########
hudi-common/src/main/java/org/apache/hudi/common/util/DateTimeUtils.java:
##########
@@ -71,6 +77,41 @@ public static long instantToMicros(Instant instant) {
}
}
+ public static long instantToNanos(Instant instant) {
+ long seconds = instant.getEpochSecond();
+ int nanos = instant.getNano();
+
+ if (seconds < 0 && nanos > 0) {
+ // Shift seconds by +1, then subtract a full second in nanos
+ long totalNanos = Math.multiplyExact(seconds + 1, 1_000_000_000L);
+ long adjustment = nanos - 1_000_000_000L;
+ return Math.addExact(totalNanos, adjustment);
+ } else {
+ long totalNanos = Math.multiplyExact(seconds, 1_000_000_000L);
+ return Math.addExact(totalNanos, nanos);
+ }
+ }
Review Comment:
Could we add a few unit tests on these new date and time utils?
##########
hudi-common/src/main/java/org/apache/hudi/common/util/DateTimeUtils.java:
##########
@@ -71,6 +77,41 @@ public static long instantToMicros(Instant instant) {
}
}
+ public static long instantToNanos(Instant instant) {
+ long seconds = instant.getEpochSecond();
+ int nanos = instant.getNano();
+
+ if (seconds < 0 && nanos > 0) {
+ // Shift seconds by +1, then subtract a full second in nanos
+ long totalNanos = Math.multiplyExact(seconds + 1, 1_000_000_000L);
+ long adjustment = nanos - 1_000_000_000L;
+ return Math.addExact(totalNanos, adjustment);
+ } else {
+ long totalNanos = Math.multiplyExact(seconds, 1_000_000_000L);
+ return Math.addExact(totalNanos, nanos);
+ }
+ }
Review Comment:
Are these standard utils copied from somewhere?
##########
hudi-common/src/main/java/org/apache/hudi/avro/HoodieAvroWrapperUtils.java:
##########
@@ -238,4 +234,120 @@ private static Pair<Boolean, String> getIsValueWrapperObfuscated(Object statsVal
}
return Pair.of(false, null);
}
+
+ public enum PrimitiveWrapperType {
+ V1(Object.class, HoodieAvroWrapperUtils::wrapValueIntoAvro, HoodieAvroWrapperUtils::unwrapAvroValueWrapper, GenericRecord.class),
+ NULL(Void.class, HoodieAvroWrapperUtils::wrapNull, HoodieAvroWrapperUtils::unwrapNull, Void.class),
+ BOOLEAN(Boolean.class, HoodieAvroWrapperUtils::wrapBoolean, HoodieAvroWrapperUtils::unwrapBoolean, BooleanWrapper.class),
+ INT(Integer.class, HoodieAvroWrapperUtils::wrapInt, HoodieAvroWrapperUtils::unwrapInt, IntWrapper.class),
+ LONG(Long.class, HoodieAvroWrapperUtils::wrapLong, HoodieAvroWrapperUtils::unwrapLong, LongWrapper.class),
+ FLOAT(Float.class, HoodieAvroWrapperUtils::wrapFloat, HoodieAvroWrapperUtils::unwrapFloat, FloatWrapper.class),
+ DOUBLE(Double.class, HoodieAvroWrapperUtils::wrapDouble, HoodieAvroWrapperUtils::unwrapDouble, DoubleWrapper.class),
+ STRING(String.class, HoodieAvroWrapperUtils::wrapString, HoodieAvroWrapperUtils::unwrapString, StringWrapper.class),
+ BYTES(ByteBuffer.class, HoodieAvroWrapperUtils::wrapBytes, HoodieAvroWrapperUtils::unwrapBytes, BytesWrapper.class);
+
+ private final Class<?> clazz;
+ private final Function<Comparable<?>, Object> wrapper;
+ private final Function<Object, Comparable<?>> unwrapper;
+ private final Class<?> wrapperClass;
+
+ PrimitiveWrapperType(Class<?> clazz, Function<Comparable<?>, Object> wrapper, Function<Object, Comparable<?>> unwrapper, Class<?> wrapperClass) {
+ this.clazz = clazz;
+ this.wrapper = wrapper;
+ this.unwrapper = unwrapper;
+ this.wrapperClass = wrapperClass;
+ }
+
+ public Class<?> getClazz() {
+ return clazz;
+ }
+
+ public Object wrap(Comparable<?> value) {
+ return wrapper.apply(value);
+ }
+
+ public Comparable<?> unwrap(Object value) {
+ return unwrapper.apply(value);
+ }
+
+ public Class<?> getWrapperClass() {
+ return wrapperClass;
+ }
+ }
+
+ private static Object wrapNull(Comparable<?> value) {
+ return value;
Review Comment:
So is `value` `null` here?
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2359357383
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/io/HoodieAppendHandle.java:
##########
@@ -427,15 +429,17 @@ protected void processAppendResult(AppendResult result, Option<HoodieLogBlock> d
updateWriteStatus(result, stat);
if (config.isMetadataColumnStatsIndexEnabled()) {
+ HoodieIndexVersion indexVersion = HoodieTableMetadataUtil.existingIndexVersionOrDefault(PARTITION_NAME_COLUMN_STATS, hoodieTable.getMetaClient());
Set<String> columnsToIndexSet = new HashSet<>(HoodieTableMetadataUtil
.getColumnsToIndex(hoodieTable.getMetaClient().getTableConfig(),
config.getMetadataConfig(), Lazy.eagerly(Option.of(writeSchemaWithMetaFields)),
- Option.of(this.recordMerger.getRecordType())).keySet());
+ Option.of(this.recordMerger.getRecordType()), indexVersion).keySet());
Review Comment:
Decided to keep it as is.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2359753233
##########
hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/spark/sql/adapter/BaseSpark3Adapter.scala:
##########
@@ -110,5 +110,8 @@ abstract class BaseSpark3Adapter extends SparkAdapter with Logging {
def stopSparkContext(jssc: JavaSparkContext, exitCode: Int): Unit
// Older Spark 3.x versions do not have TimestampNTZType
- override def isTimestampNTZType(dataType: DataType): Boolean = false
+ override def isTimestampNTZType(dataType: DataType): Boolean = {
+ // TimestampNTZType$ but don't want to rule out possibility of TimestampNTZType
+ dataType.getClass.getSimpleName.startsWith("TimestampNTZType")
+ }
Review Comment:
We discussed that Spark 3.3 also has experimental support on `TimestampNTZType`.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3308130706
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3308228760
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3308193261
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3309820597
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3221074360
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3320934753
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2370847456
##########
hudi-common/src/main/java/org/apache/hudi/stats/ValueMetadata.java:
##########
@@ -0,0 +1,254 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.ParquetAdapter;
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.Pair;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.io.Serializable;
+
+import static org.apache.hudi.avro.AvroSchemaUtils.resolveNullableSchema;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE_ADDITIONAL_INFO;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE_ORDINAL;
+
+/**
+ * Holder for VaueType and additional info
+ * Used for wrapping and unwrapping col stat values
+ * as well as for type promotion
+ */
+public class ValueMetadata implements Serializable {
+
+ private static final ParquetAdapter PARQUET_ADAPTER = ParquetAdapter.getAdapter();
+
+ private final ValueType valueType;
+
+ protected ValueMetadata(ValueType valueType) {
+ this.valueType = valueType;
+ }
+
+ public ValueType getValueType() {
+ return valueType;
+ }
+
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ return HoodieValueTypeInfo.newBuilder()
+ .setTypeOrdinal(valueType.ordinal())
+ .setAdditionalInfo(getAdditionalInfo())
+ .build();
+ }
+
+ String getAdditionalInfo() {
+ return null;
+ }
+
+ public Comparable<?> standardizeJavaTypeAndPromote(Object val) {
+ return this.getValueType().standardizeJavaTypeAndPromote(val, this);
+ }
+
+ public Object wrapValue(Comparable<?> value) {
+ return this.getValueType().wrapValue(value, this);
+ }
+
+ public Comparable<?> unwrapValue(Object value) {
+ return this.getValueType().unwrapValue(value, this);
+ }
+
+ public void validate(Object minVal, Object maxVal) {
+ if (getValueType() == ValueType.V1) {
+ return;
+ }
+ this.getValueType().validate(minVal);
+ this.getValueType().validate(maxVal);
+ }
+
+ public boolean isV1() {
+ return this.getValueType() == ValueType.V1;
+ }
+
+ public static class V1EmptyMetadata extends ValueMetadata {
+ private static final V1EmptyMetadata V1_EMPTY_METADATA = new V1EmptyMetadata();
+ public static V1EmptyMetadata get() {
+ return V1_EMPTY_METADATA;
+ }
+
+ private V1EmptyMetadata() {
+ super(ValueType.V1);
+ }
+
+ @Override
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ // V1 should never be persisted to the MDT. It is only for in memory
+ return null;
+ }
+ }
+
+ public static final ValueMetadata NULL_METADATA = new ValueMetadata(ValueType.NULL);
+
+ interface DecimalValueMetadata {
+
+ int getPrecision();
+
+ int getScale();
+
+ static String encodeData(DecimalValueMetadata decimalValueMetadata) {
+ return String.format("%d,%d", decimalValueMetadata.getPrecision(), decimalValueMetadata.getScale());
+ }
+
+ static Pair<Integer, Integer> decodeData(String data) {
+ //TODO: decide if we want to store things in a better way
+ String[] splits = data.split(",");
+ return Pair.of(Integer.parseInt(splits[0]), Integer.parseInt(splits[1]));
+ }
+ }
+
+ static class DecimalMetadata extends ValueMetadata implements DecimalValueMetadata {
+
+ static DecimalMetadata create(String additionalInfo) {
+ if (additionalInfo == null) {
+ throw new IllegalArgumentException("additionalInfo cannot be null");
+ }
+ Pair<Integer, Integer> data = DecimalValueMetadata.decodeData(additionalInfo);
+ return new DecimalMetadata(data.getLeft(), data.getRight());
+ }
+
+ static DecimalMetadata create(LogicalTypes.Decimal decimal) {
+ return new DecimalMetadata(decimal.getPrecision(), decimal.getScale());
+ }
+
+ static DecimalMetadata create(PrimitiveType primitiveType) {
+ return new DecimalMetadata(PARQUET_ADAPTER.getPrecision(primitiveType), PARQUET_ADAPTER.getScale(primitiveType));
+ }
+
+ static DecimalMetadata create(int precision, int scale) {
+ return new DecimalMetadata(precision, scale);
+ }
+
+ private final int precision;
+ private final int scale;
+
+ private DecimalMetadata(int precision, int scale) {
+ super(ValueType.DECIMAL);
+ this.precision = precision;
+ this.scale = scale;
+ }
+
+ @Override
+ public int getPrecision() {
+ return precision;
+ }
+
+ @Override
+ public int getScale() {
+ return scale;
+ }
+
+ @Override
+ String getAdditionalInfo() {
+ return DecimalValueMetadata.encodeData(this);
+ }
+ }
+
+ public static ValueMetadata getEmptyValueMetadata(HoodieIndexVersion indexVersion) {
+ if (indexVersion.lowerThan(HoodieIndexVersion.V2)) {
+ return V1EmptyMetadata.get();
+ }
+ return NULL_METADATA;
+ }
+
+ public static ValueMetadata getValueMetadata(HoodieValueTypeInfo valueTypeInfo) {
+ // valueTypeInfo will always be null when version is v1
+ if (valueTypeInfo == null) {
+ return V1EmptyMetadata.get();
+ }
+
+ ValueType valueType = ValueType.fromOrdinal(valueTypeInfo.getTypeOrdinal());
+ if (valueType == ValueType.V1) {
+ return V1EmptyMetadata.get();
+ } else if (valueType == ValueType.DECIMAL) {
+ return DecimalMetadata.create(valueTypeInfo.getAdditionalInfo());
+ } else {
+ return new ValueMetadata(valueType);
+ }
+ }
+
+ public static ValueMetadata getValueMetadata(GenericRecord columnStatsRecord) {
+ if (columnStatsRecord == null) {
+ // TODO: Should we return V1EmptyMetadata here?
+ return NULL_METADATA;
Review Comment:
Otherwise, we will need to pass index version because we don't want to assign null if it's v1, or v1 if we are on v2
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3310645586
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3320705576
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Re: [PR] feat(metadata): Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3323119159
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<details>
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2364528051
##########
hudi-common/src/main/java/org/apache/hudi/internal/schema/Type.java:
##########
@@ -64,7 +64,14 @@ enum TypeID {
TIME(Long.class),
TIMESTAMP(Long.class),
DECIMAL(BigDecimal.class),
- UUID(UUID.class);
+ UUID(UUID.class),
+ DECIMAL_BYTES(BigDecimal.class),
+ DECIMAL_FIXED(BigDecimal.class),
Review Comment:
This is because we convert between avro and internalschema at several points
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3314137025
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3267382449
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3267376179
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## CI report:
* d12c4827b897af08510795c7b3ea0592ab6b364a Azure: [FAILURE](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=8350)
* fc598f6fa98284db6d6d61bfd85e80771397206a UNKNOWN
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3267495893
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3194679117
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3193858320
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* 714e47eb6dcc8aee75a2e4de69a751b2014c7ceb UNKNOWN
* b41b39fc5025b32b2acfa3aa667261c03e0e2aed Azure: [FAILURE](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=7859)
* e7cfe3e7c5855d1bbcae9f675aced802a78b811b UNKNOWN
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2294237907
##########
hudi-common/src/main/java/org/apache/hudi/avro/ValueType.java:
##########
@@ -0,0 +1,637 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.avro;
+
+import org.apache.hudi.avro.model.ArrayWrapper;
+import org.apache.hudi.common.util.DateTimeUtils;
+import org.apache.hudi.common.util.collection.ArrayComparable;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.avro.util.Utf8;
+import org.apache.parquet.io.api.Binary;
+import org.apache.parquet.schema.LogicalTypeTokenParser;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.math.BigDecimal;
+import java.math.BigInteger;
+import java.math.MathContext;
+import java.math.RoundingMode;
+import java.nio.ByteBuffer;
+import java.sql.Date;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.time.LocalDateTime;
+import java.time.LocalTime;
+import java.time.ZoneOffset;
+import java.util.Objects;
+import java.util.UUID;
+import java.util.function.BiFunction;
+import java.util.function.Function;
+
+import static org.apache.hudi.avro.HoodieAvroUtils.convertBytesToBigDecimal;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToMicros;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToNanos;
+import static org.apache.hudi.common.util.DateTimeUtils.microsToInstant;
+import static org.apache.hudi.common.util.DateTimeUtils.nanosToInstant;
+import static org.apache.hudi.common.util.StringUtils.getUTF8Bytes;
+
+public enum ValueType {
+ V1(HoodieAvroWrapperUtils.PrimitiveWrapperType.V1.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.V1,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ NULL(HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ BOOLEAN(HoodieAvroWrapperUtils.PrimitiveWrapperType.BOOLEAN, ValueType::castToBoolean),
+ INT(HoodieAvroWrapperUtils.PrimitiveWrapperType.INT, ValueType::castToInteger),
+ LONG(HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG, ValueType::castToLong),
+ FLOAT(HoodieAvroWrapperUtils.PrimitiveWrapperType.FLOAT, ValueType::castToFloat),
+ DOUBLE(HoodieAvroWrapperUtils.PrimitiveWrapperType.DOUBLE, ValueType::castToDouble),
+ STRING(HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING, ValueType::castToString),
+ BYTES(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToBytes),
+ FIXED(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToFixed),
+ DECIMAL(BigDecimal.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES,
+ ValueType::castToDecimal, ValueType::toDecimal, ValueType::fromDecimal),
+ UUID(UUID.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING,
+ ValueType::castToUUID, ValueType::toUUID, ValueType::fromUUID),
+ DATE(Date.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToDate, ValueType::toDate, ValueType::fromDate),
+ TIME_MILLIS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToTimeMillis, ValueType::toTimeMillis, ValueType::fromTimeMillis),
+ TIME_MICROS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimeMicros, ValueType::toTimeMicros, ValueType::fromTimeMicros),
+ TIMESTAMP_MILLIS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMillis, ValueType::toTimestampMillis, ValueType::fromTimestampMillis),
+ TIMESTAMP_MICROS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMicros, ValueType::toTimestampMicros, ValueType::fromTimestampMicros),
+ TIMESTAMP_NANOS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampNanos, ValueType::toTimestampNanos, ValueType::fromTimestampNanos),
+ LOCAL_TIMESTAMP_MILLIS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMillis, ValueType::toLocalTimestampMillis, ValueType::fromLocalTimestampMillis),
+ LOCAL_TIMESTAMP_MICROS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMicros, ValueType::toLocalTimestampMicros, ValueType::fromLocalTimestampMicros),
+ LOCAL_TIMESTAMP_NANOS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampNanos, ValueType::toLocalTimestampNanos, ValueType::fromLocalTimestampNanos);
+
+ private final Class<?> internalType;
+ private final HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType;
+ private final BiFunction<Object, ValueMetadata, Comparable<?>> standardize;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toPrimitive;
Review Comment:
Will add to the code.
Standardize puts all types into the correct internal type. So fixed will become byte buffer, and also type promotion is handled.
toComplex converts logical types from the wrapper type to the internal type. Timestamps are stored as longs etc, so those get converted to Instants or LocalDateTimes.
toPrimitive reverses what toComplex does.
Whenever we unwrap a value from the mdt, we call toComplex on it. And before we wrap vales to write to the mdt, we call toPrimitive.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2288535173
##########
hudi-client/hudi-spark-client/src/main/scala/org/apache/hudi/BaseSparkInternalRecordContext.java:
##########
@@ -67,6 +73,30 @@ public static Object getFieldValueFromInternalRow(InternalRow row, Schema record
}
}
+ public static Object getFieldValueFromInternalRowAsJava(InternalRow row, Schema recordSchema, String fieldName) {
+ Object value = getFieldValueFromInternalRow(row, recordSchema, fieldName);
+ return sparkTypeToJavaType(value);
+ }
+
+ public static Object sparkTypeToJavaType(Object value) {
Review Comment:
https://github.com/apache/spark/blob/5660dbadf90ed08faef6dc883fd98f55b098e96a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/InternalRow.scala#L178 yeah
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "danny0405 (via GitHub)" <gi...@apache.org>.
danny0405 commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2289987780
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/table/upgrade/EightToNineUpgradeHandler.java:
##########
@@ -209,4 +229,24 @@ static void populateIndexVersionIfMissing(Option<HoodieIndexMetadata> indexDefOp
}
}));
}
+
+ /**
+ * Drop logical type indexes since we support them correctly now.
+ */
+ static List<String> mdtPartitionsToDrop(Option<HoodieIndexMetadata> indexDefOption, Schema tableSchema) {
+ Set<String> partitionsToDrop = new HashSet<>();
+ indexDefOption.ifPresent(idxDefs ->
+ idxDefs.getIndexDefinitions().forEach((indexName, idxDef) -> {
+ if (idxDef.getVersion() == null || idxDef.getVersion().lowerThan(HoodieIndexVersion.V2)) {
+ idxDef.getSourceFields().stream().filter(field -> {
+ Option<Schema> schema = AvroSchemaUtils.findNestedFieldSchema(tableSchema, field);
+ if (schema.isEmpty()) {
Review Comment:
schema..isPresent ?
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3276298051
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2359339082
##########
hudi-hadoop-common/src/main/java/org/apache/hudi/common/util/ParquetUtils.java:
##########
@@ -473,7 +481,10 @@ private <T extends Comparable<T>> HoodieColumnRangeMetadata<T> getColumnRangeInF
.reduce(HoodieColumnRangeMetadata::merge).get();
}
- private static Comparable<?> convertToNativeJavaType(PrimitiveType primitiveType, Comparable<?> val) {
+ private static Comparable<?> convertToNativeJavaType(PrimitiveType primitiveType, Comparable<?> val, ValueMetadata valueMetadata) {
+ if (valueMetadata.getValueType() != ValueType.V1) {
+ return valueMetadata.standardizeJavaTypeAndPromote(val);
+ }
Review Comment:
We discussed that this is hard to achieve given the APIs we have now. So we'll punt this.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2359401416
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/stats/SparkValueMetadata.java:
##########
@@ -0,0 +1,156 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.SparkAdapterSupport$;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.spark.sql.types.BinaryType;
+import org.apache.spark.sql.types.BooleanType;
+import org.apache.spark.sql.types.ByteType;
+import org.apache.spark.sql.types.CharType;
+import org.apache.spark.sql.types.DataType;
+import org.apache.spark.sql.types.DateType;
+import org.apache.spark.sql.types.Decimal;
+import org.apache.spark.sql.types.DecimalType;
+import org.apache.spark.sql.types.DoubleType;
+import org.apache.spark.sql.types.FloatType;
+import org.apache.spark.sql.types.IntegerType;
+import org.apache.spark.sql.types.LongType;
+import org.apache.spark.sql.types.NullType;
+import org.apache.spark.sql.types.ShortType;
+import org.apache.spark.sql.types.StringType;
+import org.apache.spark.sql.types.TimestampType;
+import org.apache.spark.sql.types.VarcharType;
+
+import java.sql.Date;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+
+public abstract class SparkValueMetadata extends ValueMetadata {
+
+ private SparkValueMetadata() {
+ super(null);
+ throw new IllegalStateException("This constructor should never be called");
+ }
Review Comment:
Change this to `SparkValueMetadataUtils` without being `abstract` and remove the constructor?
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2359620625
##########
hudi-common/src/main/java/org/apache/hudi/common/util/FileFormatUtils.java:
##########
@@ -64,10 +66,24 @@ public abstract class FileFormatUtils {
* @param fileColumnRanges List of column range statistics for each file in a partition
*/
public static <T extends Comparable<T>> HoodieColumnRangeMetadata<T> getColumnRangeInPartition(String relativePartitionPath,
+ String columnName,
@Nonnull List<HoodieColumnRangeMetadata<T>> fileColumnRanges,
- Map<String, Schema> colsToIndexSchemaMap) {
+ Map<String, Schema> colsToIndexSchemaMap,
+ HoodieIndexVersion indexVersion) {
ValidationUtils.checkArgument(!fileColumnRanges.isEmpty(), "fileColumnRanges should not be empty.");
+ if (indexVersion.greaterThanOrEquals(HoodieIndexVersion.V2)) {
+ ValueMetadata valueMetadata = ValueMetadata.getValueMetadata(colsToIndexSchemaMap.get(columnName), indexVersion);
+ return fileColumnRanges.stream()
+ .map(e -> {
+ T minValue = (T) valueMetadata.standardizeJavaTypeAndPromote(e.getMinValue());
+ T maxValue = (T) valueMetadata.standardizeJavaTypeAndPromote(e.getMaxValue());
+ return HoodieColumnRangeMetadata.create(
+ relativePartitionPath, e.getColumnName(), minValue, maxValue, e.getNullCount(), e.getValueCount(), e.getTotalSize(),
+ e.getTotalUncompressedSize(), valueMetadata);
+ }).reduce(HoodieColumnRangeMetadata::merge).orElseThrow(() -> new HoodieException("MergingColumnRanges failed."));
+ }
+ // we are reducing using merge so IDK why we think there are multiple cols that need to go through schema evolution
Review Comment:
Got it. Should we remove this comment from code and add a follow-up task to refactor the code?
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2359708388
##########
hudi-common/src/main/java/org/apache/hudi/stats/ValueType.java:
##########
@@ -0,0 +1,668 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.avro.AvroSchemaUtils;
+import org.apache.hudi.avro.HoodieAvroWrapperUtils;
+import org.apache.hudi.common.util.DateTimeUtils;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.avro.util.Utf8;
+import org.apache.parquet.io.api.Binary;
+import org.apache.parquet.schema.LogicalTypeTokenParser;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.math.BigDecimal;
+import java.math.BigInteger;
+import java.math.MathContext;
+import java.math.RoundingMode;
+import java.nio.ByteBuffer;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.time.LocalDateTime;
+import java.time.LocalTime;
+import java.time.ZoneOffset;
+import java.util.Objects;
+import java.util.UUID;
+import java.util.function.BiFunction;
+import java.util.function.Function;
+
+import static org.apache.hudi.avro.HoodieAvroUtils.convertBytesToBigDecimal;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToMicros;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToNanos;
+import static org.apache.hudi.common.util.DateTimeUtils.microsToInstant;
+import static org.apache.hudi.common.util.DateTimeUtils.nanosToInstant;
+import static org.apache.hudi.common.util.StringUtils.getUTF8Bytes;
+
+public enum ValueType {
+ V1(HoodieAvroWrapperUtils.PrimitiveWrapperType.V1.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.V1,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ NULL(HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ BOOLEAN(HoodieAvroWrapperUtils.PrimitiveWrapperType.BOOLEAN, ValueType::castToBoolean),
+ INT(HoodieAvroWrapperUtils.PrimitiveWrapperType.INT, ValueType::castToInteger),
+ LONG(HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG, ValueType::castToLong),
+ FLOAT(HoodieAvroWrapperUtils.PrimitiveWrapperType.FLOAT, ValueType::castToFloat),
+ DOUBLE(HoodieAvroWrapperUtils.PrimitiveWrapperType.DOUBLE, ValueType::castToDouble),
+ STRING(HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING, ValueType::castToString),
+ BYTES(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToBytes),
+ FIXED(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToFixed),
+ DECIMAL(BigDecimal.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES,
+ ValueType::castToDecimal, ValueType::toDecimal, ValueType::fromDecimal),
+ UUID(UUID.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING,
+ ValueType::castToUUID, ValueType::toUUID, ValueType::fromUUID),
+ DATE(LocalDate.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToDate, ValueType::toDate, ValueType::fromDate),
+ TIME_MILLIS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToTimeMillis, ValueType::toTimeMillis, ValueType::fromTimeMillis),
+ TIME_MICROS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimeMicros, ValueType::toTimeMicros, ValueType::fromTimeMicros),
+ TIMESTAMP_MILLIS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMillis, ValueType::toTimestampMillis, ValueType::fromTimestampMillis),
+ TIMESTAMP_MICROS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMicros, ValueType::toTimestampMicros, ValueType::fromTimestampMicros),
+ TIMESTAMP_NANOS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampNanos, ValueType::toTimestampNanos, ValueType::fromTimestampNanos),
+ LOCAL_TIMESTAMP_MILLIS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMillis, ValueType::toLocalTimestampMillis, ValueType::fromLocalTimestampMillis),
+ LOCAL_TIMESTAMP_MICROS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMicros, ValueType::toLocalTimestampMicros, ValueType::fromLocalTimestampMicros),
+ LOCAL_TIMESTAMP_NANOS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampNanos, ValueType::toLocalTimestampNanos, ValueType::fromLocalTimestampNanos);
+
+ private final Class<?> internalType;
+ private final HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType;
+ private final BiFunction<Object, ValueMetadata, Comparable<?>> standardize;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toPrimitive;
+
+ ValueType(HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType, Function<Object, Object> single) {
+ this(primitiveWrapperType.getClazz(),
+ primitiveWrapperType,
+ (val, meta) -> (Comparable<?>) single.apply(val),
+ ValueType::passThrough,
+ ValueType::passThrough);
+ }
+
+ ValueType(Class<?> internalType,
+ HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType,
+ BiFunction<Object, ValueMetadata, Comparable<?>> standardize,
+ BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex,
+ BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toPrimitive) {
+ this.internalType = internalType;
+ this.primitiveWrapperType = primitiveWrapperType;
+ this.standardize = standardize;
+ this.toComplex = toComplex;
+ this.toPrimitive = toPrimitive;
+ }
+
+ Comparable<?> standardizeJavaTypeAndPromote(Object val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return standardize.apply(val, meta);
+ }
+
+ private Comparable<?> convertIntoPrimitive(Comparable<?> val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return toPrimitive.apply(val, meta);
+ }
+
+ private Comparable<?> convertIntoComplex(Comparable<?> val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return toComplex.apply(val, meta);
+ }
+
+ void validate(Object val) {
+ if (val == null) {
+ return;
+ }
+
+ if (!internalType.isInstance(val)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ internalType.getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ }
+
+ public Object wrapValue(Comparable<?> val, ValueMetadata meta) {
+ if (meta.getValueType() == V1) {
+ return primitiveWrapperType.wrap(val);
+ }
+
+ if (val == null) {
+ return null;
+ }
+ if (!this.internalType.isInstance(val)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ this.internalType.getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ return primitiveWrapperType.wrap(convertIntoPrimitive(val, meta));
+ }
+
+ public Comparable<?> unwrapValue(Object val, ValueMetadata meta) {
+ if (meta.getValueType() == V1) {
+ return primitiveWrapperType.unwrap(val);
+ }
+
+ if (val == null) {
+ return null;
+ }
+
+ if (!primitiveWrapperType.getWrapperClass().isInstance(val)) {
+ if (!(val instanceof GenericRecord)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ primitiveWrapperType.getWrapperClass().getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ } else if (((GenericRecord) val).getSchema().getField("value") != null) {
+ return standardizeJavaTypeAndPromote(HoodieAvroWrapperUtils.unwrapGenericRecord(val), meta);
+ } else {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ primitiveWrapperType.getWrapperClass().getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ }
+ return convertIntoComplex(primitiveWrapperType.unwrap(val), meta);
+ }
+
+ private static ValueType[] myEnumValues;
+
+ public static ValueType fromInt(int i) {
+ if (ValueType.myEnumValues == null) {
+ ValueType.myEnumValues = ValueType.values();
+ }
+ return ValueType.myEnumValues[i];
+ }
+
+ public static ValueType fromPrimitiveType(PrimitiveType primitiveType) {
+ if (primitiveType.getLogicalTypeAnnotation() != null) {
+ return LogicalTypeTokenParser.fromLogicalTypeAnnotation(primitiveType);
+ }
+ switch (primitiveType.getPrimitiveTypeName()) {
+ case INT64:
+ return ValueType.LONG;
+ case INT32:
+ return ValueType.INT;
+ case BOOLEAN:
+ return ValueType.BOOLEAN;
+ case BINARY:
+ return ValueType.BYTES;
+ case FLOAT:
+ return ValueType.FLOAT;
+ case DOUBLE:
+ return ValueType.DOUBLE;
+ case INT96:
+ // TODO: probably wrong
+ return ValueType.DECIMAL;
+ case FIXED_LEN_BYTE_ARRAY:
+ return ValueType.FIXED;
+ default:
+ throw new IllegalArgumentException("Unsupported primitive type: " + primitiveType.getPrimitiveTypeName());
+ }
+ }
+
+ public static ValueType fromSchema(Schema schema) {
+ switch (schema.getType()) {
+ case NULL:
+ if (schema.getLogicalType() == null) {
+ return ValueType.NULL;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Null: " + schema.getLogicalType());
+ case BOOLEAN:
+ if (schema.getLogicalType() == null) {
+ return ValueType.BOOLEAN;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Boolean: " + schema.getLogicalType());
+ case INT:
+ if (schema.getLogicalType() == null) {
+ return ValueType.INT;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.Date) {
+ return ValueType.DATE;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.TimeMillis) {
+ return ValueType.TIME_MILLIS;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Int: " + schema.getLogicalType());
+ case LONG:
+ if (schema.getLogicalType() == null) {
+ return ValueType.LONG;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.TimeMicros) {
+ return ValueType.TIME_MICROS;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.TimestampMillis) {
+ return ValueType.TIMESTAMP_MILLIS;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.TimestampMicros) {
+ return ValueType.TIMESTAMP_MICROS;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.LocalTimestampMillis) {
+ return ValueType.LOCAL_TIMESTAMP_MILLIS;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.LocalTimestampMicros) {
+ return ValueType.LOCAL_TIMESTAMP_MICROS;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Long: " + schema.getLogicalType());
+ case FLOAT:
+ if (schema.getLogicalType() == null) {
+ return ValueType.FLOAT;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Float: " + schema.getLogicalType());
+ case DOUBLE:
+ if (schema.getLogicalType() == null) {
+ return ValueType.DOUBLE;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Double: " + schema.getLogicalType());
+ case BYTES:
+ if (schema.getLogicalType() == null) {
+ return ValueType.BYTES;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.Decimal) {
+ return ValueType.DECIMAL;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Bytes: " + schema.getLogicalType());
+ case STRING:
+ if (schema.getLogicalType() == null) {
+ return ValueType.STRING;
+ } else if (Objects.equals(schema.getLogicalType().getName(), LogicalTypes.uuid().getName())) {
+ return ValueType.UUID;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for String: " + schema.getLogicalType());
+ case FIXED:
+ if (schema.getLogicalType() == null) {
+ return ValueType.FIXED;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.Decimal) {
+ return ValueType.DECIMAL;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Fixed: " + schema.getLogicalType());
+ case UNION:
+ return fromSchema(AvroSchemaUtils.resolveNullableSchema(schema));
+ default:
+ throw new IllegalArgumentException("Unsupported type: " + schema.getType());
+ }
+ }
+
+ // Casting to standardize types and also type promotion
+ private static Comparable<?> passThrough(Object val, ValueMetadata meta) {
+ return (Comparable<?>) val;
+ }
+
+ private static Boolean castToBoolean(Object val) {
+ if (val instanceof Boolean) {
+ return (Boolean) val;
+ } else {
+ throw new UnsupportedOperationException("Unable to convert boolean: " + val.getClass());
+ }
+ }
+
+ private static Integer castToInteger(Object val) {
+ if (val == null) {
+ return null;
+ }
+ if (val instanceof Integer) {
+ return (Integer) val;
+ } else if (val instanceof Long) {
+ return ((Long) val).intValue();
+ } else if (val instanceof Float) {
+ return ((Float) val).intValue();
+ } else if (val instanceof Double) {
+ return ((Double) val).intValue();
+ } else if (val instanceof Boolean) {
+ return ((Boolean) val) ? 1 : 0;
+ } else {
+ // best effort casting
+ return Integer.parseInt(val.toString());
+ }
+ }
+
+ private static Long castToLong(Object val) {
+ if (val == null) {
+ return null;
+ }
+ if (val instanceof Integer) {
+ return ((Integer) val).longValue();
+ } else if (val instanceof Long) {
+ return ((Long) val);
+ } else if (val instanceof Float) {
+ return ((Float) val).longValue();
+ } else if (val instanceof Double) {
+ return ((Double) val).longValue();
+ } else if (val instanceof Boolean) {
+ return ((Boolean) val) ? 1L : 0L;
+ } else {
+ // best effort casting
+ return Long.parseLong(val.toString());
+ }
+ }
+
+ private static Float castToFloat(Object val) {
+ if (val == null) {
+ return null;
+ }
+ if (val instanceof Integer) {
+ return ((Integer) val).floatValue();
+ } else if (val instanceof Long) {
+ return ((Long) val).floatValue();
+ } else if (val instanceof Float) {
+ return (Float) val;
+ } else if (val instanceof Double) {
+ return ((Double) val).floatValue();
Review Comment:
Got it. It should be removed if such evolution is not allowed.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3288939001
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3286661176
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3286752531
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2370826329
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/utils/SparkMetadataWriterUtils.java:
##########
@@ -206,6 +212,16 @@ public static ExpressionIndexComputationMetadata getExpressionIndexRecordsUsingC
: new ExpressionIndexComputationMetadata(colStatRecords);
}
+ private static SparkValueMetadata getValueMetadataFromColumnRangeDataset(Dataset<Row> dataset, HoodieIndexVersion indexVersion) {
Review Comment:
I didn't understand what you wanted. But now I do. Updated
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3293346510
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3293126597
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3312767980
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3299645816
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* 3630ba26e8964bfa0f052261ef2367977cb08d16 Azure: [FAILURE](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=8543)
* 87bfc6f3911334303d3c2809c2cf440ac9dc3f6f UNKNOWN
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2353742311
##########
hudi-common/src/main/java/org/apache/hudi/common/util/DateTimeUtils.java:
##########
@@ -71,6 +77,41 @@ public static long instantToMicros(Instant instant) {
}
}
+ public static long instantToNanos(Instant instant) {
+ long seconds = instant.getEpochSecond();
+ int nanos = instant.getNano();
+
+ if (seconds < 0 && nanos > 0) {
+ // Shift seconds by +1, then subtract a full second in nanos
+ long totalNanos = Math.multiplyExact(seconds + 1, 1_000_000_000L);
+ long adjustment = nanos - 1_000_000_000L;
+ return Math.addExact(totalNanos, adjustment);
+ } else {
+ long totalNanos = Math.multiplyExact(seconds, 1_000_000_000L);
+ return Math.addExact(totalNanos, nanos);
+ }
+ }
Review Comment:
No, actually I think I just copied the above method, and then changed it to nanos
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2353807468
##########
hudi-utilities/src/test/resources/streamer-config/source-timestamp-millis.avsc:
##########
@@ -0,0 +1,162 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+{
+ "type" : "record",
+ "name" : "triprec",
+ "fields" : [
+ {
+ "name": "timestamp",
+ "type": "long"
+ },
+ {
+ "name": "_row_key",
+ "type": "string"
+ },
+ {
+ "name": "partition_path",
+ "type": "string"
+ },
+ {
+ "name": "trip_type",
+ "type": {
+ "type": "enum",
+ "name": "TripType",
+ "symbols": [
+ "UNKNOWN",
+ "UBERX",
+ "BLACK"
+ ],
+ "default": "UNKNOWN"
+ }
+ },
+ {
+ "name": "rider",
+ "type": "string"
+ },
+ {
+ "name": "driver",
+ "type": "string"
+ },
+ {
+ "name": "begin_lat",
+ "type": "double"
+ },
+ {
+ "name": "begin_lon",
+ "type": "double"
+ },
+ {
+ "name": "end_lat",
+ "type": "double"
+ },
+ {
+ "name": "end_lon",
+ "type": "double"
+ },
+ {
+ "name": "distance_in_meters",
+ "type": "int"
+ },
+ {
+ "name": "seconds_since_epoch",
+ "type": "long"
+ },
+ {
+ "name": "weight",
+ "type": "float"
+ },
+ {
+ "name": "nation",
+ "type": "bytes"
+ },
+ {
+ "name": "current_date",
+ "type": {
+ "type": "int",
+ "logicalType": "date"
+ }
+ },
+ {
+ "name": "current_ts",
+ "type": {
+ "type": "long",
+ "logicalType": "timestamp-millis"
Review Comment:
Could we also add `timestamp-micros` (also supported in V1), and other timestamp type like `time-millis` and `local-time-micros` for testing?
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2353849944
##########
hudi-common/src/main/java/org/apache/hudi/stats/ValueMetadata.java:
##########
@@ -0,0 +1,242 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.Pair;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.parquet.schema.LogicalTypeTokenParser;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.io.Serializable;
+
+import static org.apache.hudi.avro.AvroSchemaUtils.resolveNullableSchema;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE_ADDITIONAL_INFO;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE_ORDINAL;
+
+public class ValueMetadata implements Serializable {
+ private final ValueType valueType;
+
+ protected ValueMetadata(ValueType valueType) {
+ this.valueType = valueType;
+ }
+
+ public ValueType getValueType() {
+ return valueType;
+ }
+
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ return HoodieValueTypeInfo.newBuilder()
+ .setTypeOrdinal(valueType.ordinal())
+ .setAdditionalInfo(getAdditionalInfo())
+ .build();
+ }
+
+ public String getAdditionalInfo() {
+ return null;
+ }
+
+ public Comparable<?> standardizeJavaTypeAndPromote(Object val) {
+ return this.getValueType().standardizeJavaTypeAndPromote(val, this);
+ }
+
+ public Object wrapValue(Comparable<?> value) {
+ return this.getValueType().wrapValue(value, this);
+ }
+
+ public Comparable<?> unwrapValue(Object value) {
+ return this.getValueType().unwrapValue(value, this);
+ }
+
+ public void validate(Object minVal, Object maxVal) {
+ if (getValueType() == ValueType.V1) {
+ return;
+ }
+ this.getValueType().validate(minVal);
+ this.getValueType().validate(maxVal);
+ }
+
+ public static class V1EmptyMetadata extends ValueMetadata {
+ private static final V1EmptyMetadata V_1_EMPTY_METADATA = new V1EmptyMetadata();
Review Comment:
```suggestion
private static final V1EmptyMetadata V1_EMPTY_METADATA = new V1EmptyMetadata();
```
##########
hudi-spark-datasource/hudi-spark/src/test/java/org/apache/hudi/functional/TestSparkSortAndSizeClustering.java:
##########
@@ -182,9 +183,9 @@ private void validateDateAndTimestampFields(List<Row> rows, long ts) {
assertTrue(actualDate.compareTo(startDate) > 0 && actualDate.compareTo(endDate) < 0);
}
if (!row.isNullAt(tsLocalMillisFieldIndex)) {
- assertEquals(ts, row.get(tsLocalMillisFieldIndex));
+ assertEquals(ValueType.toLocalTimestampMillis(ts, null), row.get(tsLocalMillisFieldIndex));
}
- assertEquals(ts * 1000L, row.get(tsLocalMicrosFieldIndex));
+ assertEquals(ValueType.toLocalTimestampMillis(ts, null), row.get(tsLocalMicrosFieldIndex));
Review Comment:
Should this be `toLocalTiestampMicros`?
##########
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/hudi/functional/ColumnStatIndexTestBase.scala:
##########
@@ -334,24 +334,24 @@ class ColumnStatIndexTestBase extends HoodieSparkClientTestBase {
val metadataConfig = HoodieMetadataConfig.newBuilder()
.fromProperties(toProperties(metadataOpts))
.build()
-
- val pStatsIndex = new PartitionStatsIndexSupport(spark, sourceTableSchema, metadataConfig, metaClient)
-
val schemaUtil = new TableSchemaResolver(metaClient)
val tableSchema = schemaUtil.getTableAvroSchema(false)
+ val localSourceTableSchema = AvroConversionUtils.convertAvroSchemaToStructType(tableSchema)
+
+ val pStatsIndex = new PartitionStatsIndexSupport(spark, localSourceTableSchema, metadataConfig, metaClient)
val indexedColumnswithMeta: Set[String] = metaClient.getIndexMetadata.get().getIndexDefinitions.get(PARTITION_NAME_COLUMN_STATS).getSourceFields.asScala.toSet
val pIndexedColumns = indexedColumnswithMeta.filter(colName => !HoodieTableMetadataUtil.META_COL_SET_TO_INDEX.contains(colName))
.toSeq.sorted
- val (pExpectedColStatsSchema, _) = composeIndexSchema(pIndexedColumns, pIndexedColumns, sourceTableSchema)
+ val (pExpectedColStatsSchema, _) = composeIndexSchema(pIndexedColumns, pIndexedColumns, localSourceTableSchema)
Review Comment:
Is `localSourceTableSchema` different from `sourceTableSchema`?
##########
hudi-spark-datasource/hudi-spark/src/test/resources/schema_with_logical_types.avsc:
##########
@@ -30,12 +30,11 @@
},
{
"name": "ts",
- "type": ["long", "null"]
+ "type": ["null", "long"]
},
{
"name": "_hoodie_is_deleted",
- "type": ["boolean", "null"],
- "default" : false
Review Comment:
Does this fail any test?
##########
hudi-spark-datasource/hudi-spark/src/test/resources/schema_with_logical_types.avsc:
##########
@@ -30,12 +30,11 @@
},
{
"name": "ts",
- "type": ["long", "null"]
Review Comment:
Similar here on whether the change can be avoided
##########
hudi-common/src/main/java/org/apache/hudi/stats/ValueMetadata.java:
##########
@@ -0,0 +1,242 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.Pair;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.parquet.schema.LogicalTypeTokenParser;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.io.Serializable;
+
+import static org.apache.hudi.avro.AvroSchemaUtils.resolveNullableSchema;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE_ADDITIONAL_INFO;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE_ORDINAL;
+
+public class ValueMetadata implements Serializable {
+ private final ValueType valueType;
+
+ protected ValueMetadata(ValueType valueType) {
+ this.valueType = valueType;
+ }
+
+ public ValueType getValueType() {
+ return valueType;
+ }
+
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ return HoodieValueTypeInfo.newBuilder()
+ .setTypeOrdinal(valueType.ordinal())
+ .setAdditionalInfo(getAdditionalInfo())
+ .build();
+ }
+
+ public String getAdditionalInfo() {
+ return null;
+ }
+
+ public Comparable<?> standardizeJavaTypeAndPromote(Object val) {
+ return this.getValueType().standardizeJavaTypeAndPromote(val, this);
+ }
+
+ public Object wrapValue(Comparable<?> value) {
+ return this.getValueType().wrapValue(value, this);
+ }
+
+ public Comparable<?> unwrapValue(Object value) {
+ return this.getValueType().unwrapValue(value, this);
+ }
+
+ public void validate(Object minVal, Object maxVal) {
+ if (getValueType() == ValueType.V1) {
+ return;
+ }
+ this.getValueType().validate(minVal);
+ this.getValueType().validate(maxVal);
+ }
+
+ public static class V1EmptyMetadata extends ValueMetadata {
+ private static final V1EmptyMetadata V_1_EMPTY_METADATA = new V1EmptyMetadata();
+ public static V1EmptyMetadata get() {
+ return V_1_EMPTY_METADATA;
+ }
+
+ private V1EmptyMetadata() {
+ super(ValueType.V1);
+ }
+
+ @Override
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ // V1 should never be persisted to the MDT. It is only for in memory
+ return null;
+ }
+ }
+
+ public static final ValueMetadata NULL_METADATA = new ValueMetadata(ValueType.NULL);
+
+ public interface DecimalValueMetadata {
+
+ int getPrecision();
+
+ int getScale();
+
+ static String encodeData(DecimalValueMetadata decimalValueMetadata) {
+ return String.format("%d,%d", decimalValueMetadata.getPrecision(), decimalValueMetadata.getScale());
+ }
+
+ static Pair<Integer, Integer> decodeData(String data) {
+ //TODO: decide if we want to store things in a better way
+ String[] splits = data.split(",");
+ return Pair.of(Integer.parseInt(splits[0]), Integer.parseInt(splits[1]));
Review Comment:
Let's document the encoding in Javadoc and Avro schema?
##########
hudi-common/src/main/java/org/apache/hudi/stats/ValueType.java:
##########
@@ -0,0 +1,668 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.avro.AvroSchemaUtils;
+import org.apache.hudi.avro.HoodieAvroWrapperUtils;
+import org.apache.hudi.common.util.DateTimeUtils;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.avro.util.Utf8;
+import org.apache.parquet.io.api.Binary;
+import org.apache.parquet.schema.LogicalTypeTokenParser;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.math.BigDecimal;
+import java.math.BigInteger;
+import java.math.MathContext;
+import java.math.RoundingMode;
+import java.nio.ByteBuffer;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.time.LocalDateTime;
+import java.time.LocalTime;
+import java.time.ZoneOffset;
+import java.util.Objects;
+import java.util.UUID;
+import java.util.function.BiFunction;
+import java.util.function.Function;
+
+import static org.apache.hudi.avro.HoodieAvroUtils.convertBytesToBigDecimal;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToMicros;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToNanos;
+import static org.apache.hudi.common.util.DateTimeUtils.microsToInstant;
+import static org.apache.hudi.common.util.DateTimeUtils.nanosToInstant;
+import static org.apache.hudi.common.util.StringUtils.getUTF8Bytes;
+
+public enum ValueType {
+ V1(HoodieAvroWrapperUtils.PrimitiveWrapperType.V1.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.V1,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ NULL(HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ BOOLEAN(HoodieAvroWrapperUtils.PrimitiveWrapperType.BOOLEAN, ValueType::castToBoolean),
+ INT(HoodieAvroWrapperUtils.PrimitiveWrapperType.INT, ValueType::castToInteger),
+ LONG(HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG, ValueType::castToLong),
+ FLOAT(HoodieAvroWrapperUtils.PrimitiveWrapperType.FLOAT, ValueType::castToFloat),
+ DOUBLE(HoodieAvroWrapperUtils.PrimitiveWrapperType.DOUBLE, ValueType::castToDouble),
+ STRING(HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING, ValueType::castToString),
+ BYTES(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToBytes),
+ FIXED(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToFixed),
+ DECIMAL(BigDecimal.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES,
+ ValueType::castToDecimal, ValueType::toDecimal, ValueType::fromDecimal),
+ UUID(UUID.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING,
+ ValueType::castToUUID, ValueType::toUUID, ValueType::fromUUID),
+ DATE(LocalDate.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToDate, ValueType::toDate, ValueType::fromDate),
+ TIME_MILLIS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToTimeMillis, ValueType::toTimeMillis, ValueType::fromTimeMillis),
+ TIME_MICROS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimeMicros, ValueType::toTimeMicros, ValueType::fromTimeMicros),
+ TIMESTAMP_MILLIS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMillis, ValueType::toTimestampMillis, ValueType::fromTimestampMillis),
+ TIMESTAMP_MICROS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMicros, ValueType::toTimestampMicros, ValueType::fromTimestampMicros),
+ TIMESTAMP_NANOS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampNanos, ValueType::toTimestampNanos, ValueType::fromTimestampNanos),
+ LOCAL_TIMESTAMP_MILLIS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMillis, ValueType::toLocalTimestampMillis, ValueType::fromLocalTimestampMillis),
+ LOCAL_TIMESTAMP_MICROS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMicros, ValueType::toLocalTimestampMicros, ValueType::fromLocalTimestampMicros),
+ LOCAL_TIMESTAMP_NANOS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampNanos, ValueType::toLocalTimestampNanos, ValueType::fromLocalTimestampNanos);
+
+ private final Class<?> internalType;
+ private final HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType;
+ private final BiFunction<Object, ValueMetadata, Comparable<?>> standardize;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toPrimitive;
+
+ ValueType(HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType, Function<Object, Object> single) {
+ this(primitiveWrapperType.getClazz(),
+ primitiveWrapperType,
+ (val, meta) -> (Comparable<?>) single.apply(val),
+ ValueType::passThrough,
+ ValueType::passThrough);
+ }
+
+ ValueType(Class<?> internalType,
+ HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType,
+ BiFunction<Object, ValueMetadata, Comparable<?>> standardize,
+ BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex,
+ BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toPrimitive) {
+ this.internalType = internalType;
+ this.primitiveWrapperType = primitiveWrapperType;
+ this.standardize = standardize;
+ this.toComplex = toComplex;
+ this.toPrimitive = toPrimitive;
+ }
+
+ Comparable<?> standardizeJavaTypeAndPromote(Object val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return standardize.apply(val, meta);
+ }
+
+ private Comparable<?> convertIntoPrimitive(Comparable<?> val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return toPrimitive.apply(val, meta);
+ }
+
+ private Comparable<?> convertIntoComplex(Comparable<?> val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return toComplex.apply(val, meta);
+ }
+
+ void validate(Object val) {
+ if (val == null) {
+ return;
+ }
+
+ if (!internalType.isInstance(val)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ internalType.getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ }
+
+ public Object wrapValue(Comparable<?> val, ValueMetadata meta) {
+ if (meta.getValueType() == V1) {
+ return primitiveWrapperType.wrap(val);
+ }
+
+ if (val == null) {
+ return null;
+ }
+ if (!this.internalType.isInstance(val)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ this.internalType.getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ return primitiveWrapperType.wrap(convertIntoPrimitive(val, meta));
+ }
+
+ public Comparable<?> unwrapValue(Object val, ValueMetadata meta) {
+ if (meta.getValueType() == V1) {
+ return primitiveWrapperType.unwrap(val);
+ }
+
+ if (val == null) {
+ return null;
+ }
+
+ if (!primitiveWrapperType.getWrapperClass().isInstance(val)) {
+ if (!(val instanceof GenericRecord)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ primitiveWrapperType.getWrapperClass().getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ } else if (((GenericRecord) val).getSchema().getField("value") != null) {
+ return standardizeJavaTypeAndPromote(HoodieAvroWrapperUtils.unwrapGenericRecord(val), meta);
+ } else {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ primitiveWrapperType.getWrapperClass().getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ }
+ return convertIntoComplex(primitiveWrapperType.unwrap(val), meta);
+ }
+
+ private static ValueType[] myEnumValues;
+
+ public static ValueType fromInt(int i) {
+ if (ValueType.myEnumValues == null) {
+ ValueType.myEnumValues = ValueType.values();
+ }
+ return ValueType.myEnumValues[i];
+ }
+
+ public static ValueType fromPrimitiveType(PrimitiveType primitiveType) {
+ if (primitiveType.getLogicalTypeAnnotation() != null) {
+ return LogicalTypeTokenParser.fromLogicalTypeAnnotation(primitiveType);
+ }
+ switch (primitiveType.getPrimitiveTypeName()) {
+ case INT64:
+ return ValueType.LONG;
+ case INT32:
+ return ValueType.INT;
+ case BOOLEAN:
+ return ValueType.BOOLEAN;
+ case BINARY:
+ return ValueType.BYTES;
+ case FLOAT:
+ return ValueType.FLOAT;
+ case DOUBLE:
+ return ValueType.DOUBLE;
+ case INT96:
+ // TODO: probably wrong
+ return ValueType.DECIMAL;
+ case FIXED_LEN_BYTE_ARRAY:
+ return ValueType.FIXED;
+ default:
+ throw new IllegalArgumentException("Unsupported primitive type: " + primitiveType.getPrimitiveTypeName());
+ }
+ }
+
+ public static ValueType fromSchema(Schema schema) {
+ switch (schema.getType()) {
+ case NULL:
+ if (schema.getLogicalType() == null) {
+ return ValueType.NULL;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Null: " + schema.getLogicalType());
+ case BOOLEAN:
+ if (schema.getLogicalType() == null) {
+ return ValueType.BOOLEAN;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Boolean: " + schema.getLogicalType());
+ case INT:
+ if (schema.getLogicalType() == null) {
+ return ValueType.INT;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.Date) {
+ return ValueType.DATE;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.TimeMillis) {
+ return ValueType.TIME_MILLIS;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Int: " + schema.getLogicalType());
+ case LONG:
+ if (schema.getLogicalType() == null) {
+ return ValueType.LONG;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.TimeMicros) {
+ return ValueType.TIME_MICROS;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.TimestampMillis) {
+ return ValueType.TIMESTAMP_MILLIS;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.TimestampMicros) {
+ return ValueType.TIMESTAMP_MICROS;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.LocalTimestampMillis) {
+ return ValueType.LOCAL_TIMESTAMP_MILLIS;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.LocalTimestampMicros) {
+ return ValueType.LOCAL_TIMESTAMP_MICROS;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Long: " + schema.getLogicalType());
+ case FLOAT:
+ if (schema.getLogicalType() == null) {
+ return ValueType.FLOAT;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Float: " + schema.getLogicalType());
+ case DOUBLE:
+ if (schema.getLogicalType() == null) {
+ return ValueType.DOUBLE;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Double: " + schema.getLogicalType());
+ case BYTES:
+ if (schema.getLogicalType() == null) {
+ return ValueType.BYTES;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.Decimal) {
+ return ValueType.DECIMAL;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Bytes: " + schema.getLogicalType());
+ case STRING:
+ if (schema.getLogicalType() == null) {
+ return ValueType.STRING;
+ } else if (Objects.equals(schema.getLogicalType().getName(), LogicalTypes.uuid().getName())) {
+ return ValueType.UUID;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for String: " + schema.getLogicalType());
+ case FIXED:
+ if (schema.getLogicalType() == null) {
+ return ValueType.FIXED;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.Decimal) {
+ return ValueType.DECIMAL;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Fixed: " + schema.getLogicalType());
+ case UNION:
+ return fromSchema(AvroSchemaUtils.resolveNullableSchema(schema));
+ default:
+ throw new IllegalArgumentException("Unsupported type: " + schema.getType());
+ }
+ }
+
+ // Casting to standardize types and also type promotion
+ private static Comparable<?> passThrough(Object val, ValueMetadata meta) {
+ return (Comparable<?>) val;
+ }
+
+ private static Boolean castToBoolean(Object val) {
+ if (val instanceof Boolean) {
+ return (Boolean) val;
+ } else {
+ throw new UnsupportedOperationException("Unable to convert boolean: " + val.getClass());
+ }
+ }
+
+ private static Integer castToInteger(Object val) {
+ if (val == null) {
+ return null;
+ }
+ if (val instanceof Integer) {
+ return (Integer) val;
+ } else if (val instanceof Long) {
+ return ((Long) val).intValue();
+ } else if (val instanceof Float) {
+ return ((Float) val).intValue();
+ } else if (val instanceof Double) {
+ return ((Double) val).intValue();
+ } else if (val instanceof Boolean) {
+ return ((Boolean) val) ? 1 : 0;
+ } else {
+ // best effort casting
+ return Integer.parseInt(val.toString());
+ }
+ }
+
+ private static Long castToLong(Object val) {
+ if (val == null) {
+ return null;
+ }
+ if (val instanceof Integer) {
+ return ((Integer) val).longValue();
+ } else if (val instanceof Long) {
+ return ((Long) val);
+ } else if (val instanceof Float) {
+ return ((Float) val).longValue();
+ } else if (val instanceof Double) {
+ return ((Double) val).longValue();
+ } else if (val instanceof Boolean) {
+ return ((Boolean) val) ? 1L : 0L;
+ } else {
+ // best effort casting
+ return Long.parseLong(val.toString());
+ }
+ }
+
+ private static Float castToFloat(Object val) {
+ if (val == null) {
+ return null;
+ }
+ if (val instanceof Integer) {
+ return ((Integer) val).floatValue();
+ } else if (val instanceof Long) {
+ return ((Long) val).floatValue();
+ } else if (val instanceof Float) {
+ return (Float) val;
+ } else if (val instanceof Double) {
+ return ((Double) val).floatValue();
Review Comment:
I remember there's particular issue around the precision on the conversion between double and float. Is that handled here?
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2353882726
##########
hudi-flink-datasource/hudi-flink/src/test/java/org/apache/hudi/utils/TestAvroSchemaConverter.java:
##########
@@ -34,6 +35,7 @@
* Test cases for {@link org.apache.hudi.util.AvroSchemaConverter}.
*/
public class TestAvroSchemaConverter {
+ @Disabled
Review Comment:
Is this test not going to work?
##########
hudi-common/src/test/java/org/apache/hudi/common/util/TestBaseFileUtils.java:
##########
@@ -79,14 +83,15 @@ public void testGetColumnRangeInPartitionWithNullMinMax() {
@Test
public void testGetColumnRangeInPartitionWithDifferentColumnNameThrowsException() {
+ HoodieIndexVersion indexVersion = HoodieIndexVersion.V1;
Review Comment:
Could we add tests for `HoodieIndexVersion.V2`?
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2354133973
##########
hudi-common/src/main/java/org/apache/hudi/stats/ValueType.java:
##########
@@ -0,0 +1,668 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.avro.AvroSchemaUtils;
+import org.apache.hudi.avro.HoodieAvroWrapperUtils;
+import org.apache.hudi.common.util.DateTimeUtils;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.avro.util.Utf8;
+import org.apache.parquet.io.api.Binary;
+import org.apache.parquet.schema.LogicalTypeTokenParser;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.math.BigDecimal;
+import java.math.BigInteger;
+import java.math.MathContext;
+import java.math.RoundingMode;
+import java.nio.ByteBuffer;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.time.LocalDateTime;
+import java.time.LocalTime;
+import java.time.ZoneOffset;
+import java.util.Objects;
+import java.util.UUID;
+import java.util.function.BiFunction;
+import java.util.function.Function;
+
+import static org.apache.hudi.avro.HoodieAvroUtils.convertBytesToBigDecimal;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToMicros;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToNanos;
+import static org.apache.hudi.common.util.DateTimeUtils.microsToInstant;
+import static org.apache.hudi.common.util.DateTimeUtils.nanosToInstant;
+import static org.apache.hudi.common.util.StringUtils.getUTF8Bytes;
+
+public enum ValueType {
+ V1(HoodieAvroWrapperUtils.PrimitiveWrapperType.V1.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.V1,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ NULL(HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ BOOLEAN(HoodieAvroWrapperUtils.PrimitiveWrapperType.BOOLEAN, ValueType::castToBoolean),
+ INT(HoodieAvroWrapperUtils.PrimitiveWrapperType.INT, ValueType::castToInteger),
+ LONG(HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG, ValueType::castToLong),
+ FLOAT(HoodieAvroWrapperUtils.PrimitiveWrapperType.FLOAT, ValueType::castToFloat),
+ DOUBLE(HoodieAvroWrapperUtils.PrimitiveWrapperType.DOUBLE, ValueType::castToDouble),
+ STRING(HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING, ValueType::castToString),
+ BYTES(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToBytes),
+ FIXED(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToFixed),
+ DECIMAL(BigDecimal.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES,
+ ValueType::castToDecimal, ValueType::toDecimal, ValueType::fromDecimal),
+ UUID(UUID.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING,
+ ValueType::castToUUID, ValueType::toUUID, ValueType::fromUUID),
+ DATE(LocalDate.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToDate, ValueType::toDate, ValueType::fromDate),
+ TIME_MILLIS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToTimeMillis, ValueType::toTimeMillis, ValueType::fromTimeMillis),
+ TIME_MICROS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimeMicros, ValueType::toTimeMicros, ValueType::fromTimeMicros),
+ TIMESTAMP_MILLIS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMillis, ValueType::toTimestampMillis, ValueType::fromTimestampMillis),
+ TIMESTAMP_MICROS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMicros, ValueType::toTimestampMicros, ValueType::fromTimestampMicros),
+ TIMESTAMP_NANOS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampNanos, ValueType::toTimestampNanos, ValueType::fromTimestampNanos),
+ LOCAL_TIMESTAMP_MILLIS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMillis, ValueType::toLocalTimestampMillis, ValueType::fromLocalTimestampMillis),
+ LOCAL_TIMESTAMP_MICROS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMicros, ValueType::toLocalTimestampMicros, ValueType::fromLocalTimestampMicros),
+ LOCAL_TIMESTAMP_NANOS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampNanos, ValueType::toLocalTimestampNanos, ValueType::fromLocalTimestampNanos);
+
+ private final Class<?> internalType;
+ private final HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType;
+ private final BiFunction<Object, ValueMetadata, Comparable<?>> standardize;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toPrimitive;
+
+ ValueType(HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType, Function<Object, Object> single) {
+ this(primitiveWrapperType.getClazz(),
+ primitiveWrapperType,
+ (val, meta) -> (Comparable<?>) single.apply(val),
+ ValueType::passThrough,
+ ValueType::passThrough);
+ }
+
+ ValueType(Class<?> internalType,
+ HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType,
+ BiFunction<Object, ValueMetadata, Comparable<?>> standardize,
+ BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex,
+ BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toPrimitive) {
+ this.internalType = internalType;
+ this.primitiveWrapperType = primitiveWrapperType;
+ this.standardize = standardize;
+ this.toComplex = toComplex;
+ this.toPrimitive = toPrimitive;
+ }
+
+ Comparable<?> standardizeJavaTypeAndPromote(Object val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return standardize.apply(val, meta);
+ }
+
+ private Comparable<?> convertIntoPrimitive(Comparable<?> val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return toPrimitive.apply(val, meta);
+ }
+
+ private Comparable<?> convertIntoComplex(Comparable<?> val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return toComplex.apply(val, meta);
+ }
+
+ void validate(Object val) {
+ if (val == null) {
+ return;
+ }
+
+ if (!internalType.isInstance(val)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ internalType.getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ }
+
+ public Object wrapValue(Comparable<?> val, ValueMetadata meta) {
+ if (meta.getValueType() == V1) {
+ return primitiveWrapperType.wrap(val);
+ }
+
+ if (val == null) {
+ return null;
+ }
+ if (!this.internalType.isInstance(val)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ this.internalType.getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ return primitiveWrapperType.wrap(convertIntoPrimitive(val, meta));
+ }
+
+ public Comparable<?> unwrapValue(Object val, ValueMetadata meta) {
+ if (meta.getValueType() == V1) {
+ return primitiveWrapperType.unwrap(val);
+ }
+
+ if (val == null) {
+ return null;
+ }
+
+ if (!primitiveWrapperType.getWrapperClass().isInstance(val)) {
+ if (!(val instanceof GenericRecord)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ primitiveWrapperType.getWrapperClass().getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ } else if (((GenericRecord) val).getSchema().getField("value") != null) {
+ return standardizeJavaTypeAndPromote(HoodieAvroWrapperUtils.unwrapGenericRecord(val), meta);
+ } else {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ primitiveWrapperType.getWrapperClass().getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ }
+ return convertIntoComplex(primitiveWrapperType.unwrap(val), meta);
+ }
+
+ private static ValueType[] myEnumValues;
+
+ public static ValueType fromInt(int i) {
+ if (ValueType.myEnumValues == null) {
+ ValueType.myEnumValues = ValueType.values();
+ }
+ return ValueType.myEnumValues[i];
+ }
+
+ public static ValueType fromPrimitiveType(PrimitiveType primitiveType) {
+ if (primitiveType.getLogicalTypeAnnotation() != null) {
+ return LogicalTypeTokenParser.fromLogicalTypeAnnotation(primitiveType);
+ }
+ switch (primitiveType.getPrimitiveTypeName()) {
+ case INT64:
+ return ValueType.LONG;
+ case INT32:
+ return ValueType.INT;
+ case BOOLEAN:
+ return ValueType.BOOLEAN;
+ case BINARY:
+ return ValueType.BYTES;
+ case FLOAT:
+ return ValueType.FLOAT;
+ case DOUBLE:
+ return ValueType.DOUBLE;
+ case INT96:
+ // TODO: probably wrong
+ return ValueType.DECIMAL;
+ case FIXED_LEN_BYTE_ARRAY:
+ return ValueType.FIXED;
+ default:
+ throw new IllegalArgumentException("Unsupported primitive type: " + primitiveType.getPrimitiveTypeName());
+ }
+ }
+
+ public static ValueType fromSchema(Schema schema) {
+ switch (schema.getType()) {
+ case NULL:
+ if (schema.getLogicalType() == null) {
+ return ValueType.NULL;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Null: " + schema.getLogicalType());
+ case BOOLEAN:
+ if (schema.getLogicalType() == null) {
+ return ValueType.BOOLEAN;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Boolean: " + schema.getLogicalType());
+ case INT:
+ if (schema.getLogicalType() == null) {
+ return ValueType.INT;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.Date) {
+ return ValueType.DATE;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.TimeMillis) {
+ return ValueType.TIME_MILLIS;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Int: " + schema.getLogicalType());
+ case LONG:
+ if (schema.getLogicalType() == null) {
+ return ValueType.LONG;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.TimeMicros) {
+ return ValueType.TIME_MICROS;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.TimestampMillis) {
+ return ValueType.TIMESTAMP_MILLIS;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.TimestampMicros) {
+ return ValueType.TIMESTAMP_MICROS;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.LocalTimestampMillis) {
+ return ValueType.LOCAL_TIMESTAMP_MILLIS;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.LocalTimestampMicros) {
+ return ValueType.LOCAL_TIMESTAMP_MICROS;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Long: " + schema.getLogicalType());
+ case FLOAT:
+ if (schema.getLogicalType() == null) {
+ return ValueType.FLOAT;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Float: " + schema.getLogicalType());
+ case DOUBLE:
+ if (schema.getLogicalType() == null) {
+ return ValueType.DOUBLE;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Double: " + schema.getLogicalType());
+ case BYTES:
+ if (schema.getLogicalType() == null) {
+ return ValueType.BYTES;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.Decimal) {
+ return ValueType.DECIMAL;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Bytes: " + schema.getLogicalType());
+ case STRING:
+ if (schema.getLogicalType() == null) {
+ return ValueType.STRING;
+ } else if (Objects.equals(schema.getLogicalType().getName(), LogicalTypes.uuid().getName())) {
+ return ValueType.UUID;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for String: " + schema.getLogicalType());
+ case FIXED:
+ if (schema.getLogicalType() == null) {
+ return ValueType.FIXED;
+ } else if (schema.getLogicalType() instanceof LogicalTypes.Decimal) {
+ return ValueType.DECIMAL;
+ }
+ throw new IllegalArgumentException("Unsupported logical type for Fixed: " + schema.getLogicalType());
+ case UNION:
+ return fromSchema(AvroSchemaUtils.resolveNullableSchema(schema));
+ default:
+ throw new IllegalArgumentException("Unsupported type: " + schema.getType());
+ }
+ }
+
+ // Casting to standardize types and also type promotion
+ private static Comparable<?> passThrough(Object val, ValueMetadata meta) {
+ return (Comparable<?>) val;
+ }
+
+ private static Boolean castToBoolean(Object val) {
+ if (val instanceof Boolean) {
+ return (Boolean) val;
+ } else {
+ throw new UnsupportedOperationException("Unable to convert boolean: " + val.getClass());
+ }
+ }
+
+ private static Integer castToInteger(Object val) {
+ if (val == null) {
+ return null;
+ }
+ if (val instanceof Integer) {
+ return (Integer) val;
+ } else if (val instanceof Long) {
+ return ((Long) val).intValue();
+ } else if (val instanceof Float) {
+ return ((Float) val).intValue();
+ } else if (val instanceof Double) {
+ return ((Double) val).intValue();
+ } else if (val instanceof Boolean) {
+ return ((Boolean) val) ? 1 : 0;
+ } else {
+ // best effort casting
+ return Integer.parseInt(val.toString());
+ }
+ }
+
+ private static Long castToLong(Object val) {
+ if (val == null) {
+ return null;
+ }
+ if (val instanceof Integer) {
+ return ((Integer) val).longValue();
+ } else if (val instanceof Long) {
+ return ((Long) val);
+ } else if (val instanceof Float) {
+ return ((Float) val).longValue();
+ } else if (val instanceof Double) {
+ return ((Double) val).longValue();
+ } else if (val instanceof Boolean) {
+ return ((Boolean) val) ? 1L : 0L;
+ } else {
+ // best effort casting
+ return Long.parseLong(val.toString());
+ }
+ }
+
+ private static Float castToFloat(Object val) {
+ if (val == null) {
+ return null;
+ }
+ if (val instanceof Integer) {
+ return ((Integer) val).floatValue();
+ } else if (val instanceof Long) {
+ return ((Long) val).floatValue();
+ } else if (val instanceof Float) {
+ return (Float) val;
+ } else if (val instanceof Double) {
+ return ((Double) val).floatValue();
Review Comment:
Yeah that's covered. That's from float -> double. This is double -> float, which actually maybe I should remove? I got this from HoodieTableMetadataUtil.coerceToComparable
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2354138082
##########
hudi-spark-datasource/hudi-spark/src/test/resources/schema_with_logical_types.avsc:
##########
@@ -30,12 +30,11 @@
},
{
"name": "ts",
- "type": ["long", "null"]
+ "type": ["null", "long"]
},
{
"name": "_hoodie_is_deleted",
- "type": ["boolean", "null"],
- "default" : false
Review Comment:
Yes, it's usually picked up by higher level stuff, but this test was using the write client directly so it didn't hit the validation. My additions made it fail
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2354149330
##########
hudi-flink-datasource/hudi-flink/src/test/java/org/apache/hudi/utils/TestAvroSchemaConverter.java:
##########
@@ -34,6 +35,7 @@
* Test cases for {@link org.apache.hudi.util.AvroSchemaConverter}.
*/
public class TestAvroSchemaConverter {
+ @Disabled
Review Comment:
The conversion should work fine, it's converting the col stats schema. And since I added an extra field it needs to be added to this test.
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3185251859
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2364525385
##########
hudi-common/src/main/java/org/apache/hudi/avro/HoodieAvroWrapperUtils.java:
##########
@@ -238,4 +234,120 @@ private static Pair<Boolean, String> getIsValueWrapperObfuscated(Object statsVal
}
return Pair.of(false, null);
}
+
+ public enum PrimitiveWrapperType {
+ V1(Object.class, HoodieAvroWrapperUtils::wrapValueIntoAvro, HoodieAvroWrapperUtils::unwrapAvroValueWrapper, GenericRecord.class),
+ NULL(Void.class, HoodieAvroWrapperUtils::wrapNull, HoodieAvroWrapperUtils::unwrapNull, Void.class),
+ BOOLEAN(Boolean.class, HoodieAvroWrapperUtils::wrapBoolean, HoodieAvroWrapperUtils::unwrapBoolean, BooleanWrapper.class),
+ INT(Integer.class, HoodieAvroWrapperUtils::wrapInt, HoodieAvroWrapperUtils::unwrapInt, IntWrapper.class),
+ LONG(Long.class, HoodieAvroWrapperUtils::wrapLong, HoodieAvroWrapperUtils::unwrapLong, LongWrapper.class),
+ FLOAT(Float.class, HoodieAvroWrapperUtils::wrapFloat, HoodieAvroWrapperUtils::unwrapFloat, FloatWrapper.class),
+ DOUBLE(Double.class, HoodieAvroWrapperUtils::wrapDouble, HoodieAvroWrapperUtils::unwrapDouble, DoubleWrapper.class),
+ STRING(String.class, HoodieAvroWrapperUtils::wrapString, HoodieAvroWrapperUtils::unwrapString, StringWrapper.class),
+ BYTES(ByteBuffer.class, HoodieAvroWrapperUtils::wrapBytes, HoodieAvroWrapperUtils::unwrapBytes, BytesWrapper.class);
+
+ private final Class<?> clazz;
+ private final Function<Comparable<?>, Object> wrapper;
+ private final Function<Object, Comparable<?>> unwrapper;
+ private final Class<?> wrapperClass;
+
+ PrimitiveWrapperType(Class<?> clazz, Function<Comparable<?>, Object> wrapper, Function<Object, Comparable<?>> unwrapper, Class<?> wrapperClass) {
+ this.clazz = clazz;
+ this.wrapper = wrapper;
+ this.unwrapper = unwrapper;
+ this.wrapperClass = wrapperClass;
+ }
+
+ public Class<?> getClazz() {
+ return clazz;
+ }
+
+ public Object wrap(Comparable<?> value) {
+ return wrapper.apply(value);
+ }
+
+ public Comparable<?> unwrap(Object value) {
+ return unwrapper.apply(value);
+ }
+
+ public Class<?> getWrapperClass() {
+ return wrapperClass;
+ }
+ }
+
+ private static Object wrapNull(Comparable<?> value) {
+ return value;
Review Comment:
yes
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3322431785
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2370969287
##########
hudi-common/src/main/java/org/apache/hudi/metadata/HoodieTableMetadataUtil.java:
##########
@@ -1570,28 +1624,32 @@ public static Map<String, Schema> getColumnsToIndex(HoodieCommitMetadata commitM
}};
@VisibleForTesting
- public static Map<String, Schema> getColumnsToIndex(HoodieTableConfig tableConfig,
+ public static Map<String, Schema> getColumnsToIndex(
+ HoodieTableConfig tableConfig,
HoodieMetadataConfig metadataConfig,
Lazy<Option<Schema>> tableSchemaLazyOpt,
- Option<HoodieRecordType> recordType) {
- return getColumnsToIndex(tableConfig, metadataConfig, tableSchemaLazyOpt, false, recordType);
+ Option<HoodieRecordType> recordType,
+ HoodieIndexVersion indexVersion) {
Review Comment:
nit: fix indentation
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3320191520
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* 17d5552e4fbc8627b6c78b6c824bff6ef36d1c49 Azure: [PENDING](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=8725)
* 62cfcb427dc6fa44df48e7a83b2f79431fc81424 UNKNOWN
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2370866540
##########
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/hudi/functional/TestPartitionStatsPruning.scala:
##########
@@ -57,6 +56,7 @@ class TestPartitionStatsPruning extends ColumnStatIndexTestBase {
"hoodie.upsert.shuffle.parallelism" -> "4",
HoodieWriteConfig.TBL_NAME.key -> "hoodie_test",
DataSourceWriteOptions.TABLE_TYPE.key -> testCase.tableType.toString,
+ HoodieWriteConfig.WRITE_TABLE_VERSION.key() -> testCase.tableVersion.toString,
Review Comment:
added validation in `org.apache.hudi.functional.ColumnStatIndexTestBase#doWriteAndValidateColumnStats`
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3267646957
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## CI report:
* 9a59641d2daa2edf1c1907129b34861273c9738a UNKNOWN
* add0ab0f0319088cf1302edb65f99fb5226f5912 Azure: [FAILURE](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=8388)
* 672ce5bdd591130363ac984e77e7a31cc1424369 UNKNOWN
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3276331715
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* 0d38bbe38fab4725bcc0843389b892d635acde64 UNKNOWN
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3275943884
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* 73f230393a8e2c8aa839df912efc6eda2a44ca2b Azure: [FAILURE](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=8426)
* bad18ede98556d1c56cdee41c8503659921bc2f2 Azure: [PENDING](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=8456)
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3276456126
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* 0d38bbe38fab4725bcc0843389b892d635acde64 Azure: [PENDING](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=8461)
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3179934395
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## CI report:
* d211a2ca8764ae4b631b05c4af1550fb9e75fb0f Azure: [FAILURE](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=7748)
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3221102767
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2302229412
##########
hudi-common/src/main/java/org/apache/hudi/metadata/HoodieIndexVersion.java:
##########
@@ -85,27 +85,36 @@ public static HoodieIndexVersion getCurrentVersion(HoodieTableVersion tableVersi
* @return the appropriate HoodieIndexVersion for the given parameters
*/
public static HoodieIndexVersion getCurrentVersion(HoodieTableVersion tableVersion, MetadataPartitionType partitionType) {
- if (partitionType == MetadataPartitionType.RECORD_INDEX) {
- return V1;
- } else if (partitionType == MetadataPartitionType.COLUMN_STATS) {
- return V1;
- } else if (partitionType == MetadataPartitionType.BLOOM_FILTERS) {
- return V1;
- } else if (partitionType == MetadataPartitionType.EXPRESSION_INDEX) {
- return V1;
- } else if (partitionType == MetadataPartitionType.SECONDARY_INDEX) {
- if (tableVersion.greaterThanOrEquals(HoodieTableVersion.NINE)) {
+ switch (partitionType) {
+ case RECORD_INDEX:
+ return V1;
+
+ case COLUMN_STATS:
+ case PARTITION_STATS:
+ case EXPRESSION_INDEX:
+ // column stats, partition stats, expression index must be updated together
+ if (tableVersion.lesserThan(HoodieTableVersion.NINE)) {
+ return V1;
+ }
return V2;
- }
- return V1;
- } else if (partitionType == MetadataPartitionType.FILES) {
- return V1;
- } else if (partitionType == MetadataPartitionType.PARTITION_STATS) {
- return V1;
- } else if (partitionType == MetadataPartitionType.ALL_PARTITIONS) {
- return V1;
- } else {
- throw new HoodieException("Unknown metadata partition type: " + partitionType);
+
+ case BLOOM_FILTERS:
+ return V1;
+
+ case SECONDARY_INDEX:
+ if (tableVersion.greaterThanOrEquals(HoodieTableVersion.NINE)) {
+ return V2;
+ }
+ return V1;
+
+ case FILES:
+ return V1;
+
+ case ALL_PARTITIONS:
+ return V1;
+
+ default:
+ throw new HoodieException("Unknown metadata partition type: " + partitionType);
Review Comment:
Could we add index version to `MetadataPartitionType` instead of having the util method here?
##########
hudi-common/src/main/java/org/apache/hudi/metadata/HoodieIndexVersion.java:
##########
@@ -85,27 +85,36 @@ public static HoodieIndexVersion getCurrentVersion(HoodieTableVersion tableVersi
* @return the appropriate HoodieIndexVersion for the given parameters
*/
public static HoodieIndexVersion getCurrentVersion(HoodieTableVersion tableVersion, MetadataPartitionType partitionType) {
- if (partitionType == MetadataPartitionType.RECORD_INDEX) {
- return V1;
- } else if (partitionType == MetadataPartitionType.COLUMN_STATS) {
- return V1;
- } else if (partitionType == MetadataPartitionType.BLOOM_FILTERS) {
- return V1;
- } else if (partitionType == MetadataPartitionType.EXPRESSION_INDEX) {
- return V1;
- } else if (partitionType == MetadataPartitionType.SECONDARY_INDEX) {
- if (tableVersion.greaterThanOrEquals(HoodieTableVersion.NINE)) {
+ switch (partitionType) {
+ case RECORD_INDEX:
+ return V1;
+
+ case COLUMN_STATS:
+ case PARTITION_STATS:
+ case EXPRESSION_INDEX:
+ // column stats, partition stats, expression index must be updated together
+ if (tableVersion.lesserThan(HoodieTableVersion.NINE)) {
+ return V1;
+ }
return V2;
- }
- return V1;
- } else if (partitionType == MetadataPartitionType.FILES) {
- return V1;
- } else if (partitionType == MetadataPartitionType.PARTITION_STATS) {
- return V1;
- } else if (partitionType == MetadataPartitionType.ALL_PARTITIONS) {
- return V1;
- } else {
- throw new HoodieException("Unknown metadata partition type: " + partitionType);
+
+ case BLOOM_FILTERS:
+ return V1;
+
+ case SECONDARY_INDEX:
+ if (tableVersion.greaterThanOrEquals(HoodieTableVersion.NINE)) {
+ return V2;
+ }
+ return V1;
+
+ case FILES:
+ return V1;
+
+ case ALL_PARTITIONS:
+ return V1;
+
+ default:
+ throw new HoodieException("Unknown metadata partition type: " + partitionType);
Review Comment:
The problem of the current approach is that, if a new metadata partition type is added, both `HoodieIndexVersion` and `MetadataPartitionType` have to be updated. Instead, a developer should only update `MetadataPartitionType` for basic info for new partition type.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2302110253
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/table/upgrade/UpgradeDowngradeUtils.java:
##########
@@ -285,23 +284,15 @@ static boolean isMetadataTableBehindDataTable(HoodieWriteConfig config,
* @param table Hoodie table
* @param operationType Type of operation (upgrade/downgrade)
*/
- public static void dropNonV1SecondaryIndexPartitions(HoodieWriteConfig config, HoodieEngineContext context,
- HoodieTable table, SupportsUpgradeDowngrade upgradeDowngradeHelper, String operationType) {
+ public static void dropNonV1IndexPartitions(HoodieWriteConfig config, HoodieEngineContext context,
+ HoodieTable table, SupportsUpgradeDowngrade upgradeDowngradeHelper, String operationType) {
HoodieTableMetaClient metaClient = table.getMetaClient();
try (BaseHoodieWriteClient writeClient = upgradeDowngradeHelper.getWriteClient(config, context)) {
List<String> mdtPartitions = metaClient.getTableConfig().getMetadataPartitions()
.stream()
- .filter(partition -> {
- // Only drop secondary indexes that are not V1
- return metaClient.getIndexForMetadataPartition(partition)
- .map(indexDef -> {
- if (MetadataPartitionType.fromPartitionPath(indexDef.getIndexName()).equals(MetadataPartitionType.SECONDARY_INDEX)) {
- return HoodieIndexVersion.V1.lowerThan(indexDef.getVersion());
- }
- return false;
- })
- .orElse(false);
- })
+ .filter(partition -> metaClient.getIndexForMetadataPartition(partition)
+ .map(indexDef -> HoodieIndexVersion.V1.lowerThan(indexDef.getVersion()))
Review Comment:
Could we abstract index upgrade process and move the logic to a central place so it's easier to handle index layout upgrade/downgrade?
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2302100103
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/table/upgrade/EightToNineUpgradeHandler.java:
##########
@@ -209,4 +229,24 @@ static void populateIndexVersionIfMissing(Option<HoodieIndexMetadata> indexDefOp
}
}));
}
+
+ /**
+ * Drop logical type indexes since we support them correctly now.
+ */
+ static List<String> mdtPartitionsToDrop(Option<HoodieIndexMetadata> indexDefOption, Schema tableSchema) {
+ Set<String> partitionsToDrop = new HashSet<>();
+ indexDefOption.ifPresent(idxDefs ->
+ idxDefs.getIndexDefinitions().forEach((indexName, idxDef) -> {
+ if (idxDef.getVersion() == null || idxDef.getVersion().lowerThan(HoodieIndexVersion.V2)) {
+ idxDef.getSourceFields().stream().filter(field -> {
+ Option<Schema> schema = AvroSchemaUtils.findNestedFieldSchema(tableSchema, field);
+ if (schema.isEmpty()) {
Review Comment:
@jonvex is this fixed?
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3193078966
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* b41b39fc5025b32b2acfa3aa667261c03e0e2aed UNKNOWN
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3189935811
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* a852c2ac4a43bf15dc0678fd822bc0a31e403d2c UNKNOWN
* 714e47eb6dcc8aee75a2e4de69a751b2014c7ceb UNKNOWN
* 71d846c08f030f7dbe03445c61d1cfacf2122c3d Azure: [FAILURE](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=7824)
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3193887039
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* 714e47eb6dcc8aee75a2e4de69a751b2014c7ceb UNKNOWN
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2353730435
##########
hudi-common/src/main/java/org/apache/hudi/internal/schema/utils/SchemaChangeUtils.java:
##########
@@ -72,38 +72,59 @@ private static boolean isTypeUpdateAllowInternal(Type src, Type dsr) {
switch (src.typeId()) {
case INT:
return dsr == Types.LongType.get() || dsr == Types.FloatType.get()
- || dsr == Types.DoubleType.get() || dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL;
+ || dsr == Types.DoubleType.get() || dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL || dsr.typeId() == Type.TypeID.DECIMAL_FIXED;
case LONG:
- return dsr == Types.FloatType.get() || dsr == Types.DoubleType.get() || dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL;
+ return dsr == Types.FloatType.get() || dsr == Types.DoubleType.get() || dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL || dsr.typeId() == Type.TypeID.DECIMAL_FIXED;
case FLOAT:
- return dsr == Types.DoubleType.get() || dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL;
+ return dsr == Types.DoubleType.get() || dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL || dsr.typeId() == Type.TypeID.DECIMAL_FIXED;
case DOUBLE:
- return dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL;
+ return dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL || dsr.typeId() == Type.TypeID.DECIMAL_FIXED;
case DATE:
case BINARY:
return dsr == Types.StringType.get();
+ case DECIMAL_BYTES:
+ return isDecimalBytesUpdateAllowInternal(src, dsr);
case DECIMAL:
- if (dsr.typeId() == Type.TypeID.DECIMAL) {
- Types.DecimalType decimalSrc = (Types.DecimalType)src;
- Types.DecimalType decimalDsr = (Types.DecimalType)dsr;
- if (decimalDsr.isWiderThan(decimalSrc)) {
- return true;
- }
- if (decimalDsr.precision() >= decimalSrc.precision() && decimalDsr.scale() == decimalSrc.scale()) {
- return true;
- }
- } else if (dsr.typeId() == Type.TypeID.STRING) {
- return true;
- }
- break;
+ case DECIMAL_FIXED:
+ return isDecimalFixedUpdateAllowInternal(src, dsr);
case STRING:
- return dsr == Types.DateType.get() || dsr.typeId() == Type.TypeID.DECIMAL || dsr == Types.BinaryType.get();
+ return dsr == Types.DateType.get() || dsr.typeId() == Type.TypeID.DECIMAL || dsr.typeId() == Type.TypeID.DECIMAL_FIXED || dsr == Types.BinaryType.get();
default:
return false;
}
+ }
+
+ private static boolean isDecimalBytesUpdateAllowInternal(Type src, Type dsr) {
Review Comment:
oh lol, that's totally what that is. I used dsr because that is what the above method did.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3276769666
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3286554696
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3288960265
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3288783931
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3288929274
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3309407348
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2357280614
##########
hudi-utilities/src/test/java/org/apache/hudi/utilities/deltastreamer/TestHoodieDeltaStreamer.java:
##########
@@ -670,6 +672,286 @@ public void testSchemaEvolution(String tableType, boolean useUserProvidedSchema,
defaultSchemaProviderClassName = FilebasedSchemaProvider.class.getName();
}
+ @Test
+ public void testTimestampMillis() throws Exception {
+ // if (zookeeperTestService != null) {
+ // zookeeperTestService.stop();
+ // zookeeperTestService = null;
+ // }
+ String tableBasePath = basePath + "/testTimestampMillis";
+ defaultSchemaProviderClassName = FilebasedSchemaProvider.class.getName();
+ // Insert data produced with Schema A, pass Schema A
+ HoodieDeltaStreamer.Config cfg = TestHelpers.makeConfig(tableBasePath, WriteOperationType.INSERT, Collections.singletonList(TestIdentityTransformer.class.getName()),
+ PROPS_FILENAME_TEST_SOURCE, false, true, false, null, HoodieTableType.MERGE_ON_READ.name());
+ cfg.payloadClassName = DefaultHoodieRecordPayload.class.getName();
+ cfg.recordMergeStrategyId = HoodieRecordMerger.EVENT_TIME_BASED_MERGE_STRATEGY_UUID;
+ cfg.recordMergeMode = RecordMergeMode.EVENT_TIME_ORDERING;
+ cfg.configs.add("hoodie.streamer.schemaprovider.source.schema.file=" + basePath + "/source-timestamp-millis.avsc");
+ cfg.configs.add("hoodie.streamer.schemaprovider.target.schema.file=" + basePath + "/source-timestamp-millis.avsc");
+ cfg.configs.add(String.format("%s=%s", HoodieCompactionConfig.PARQUET_SMALL_FILE_LIMIT.key(), "0"));
+
+
+ new HoodieDeltaStreamer(cfg, jsc).sync();
+ assertUseV2Checkpoint(HoodieTestUtils.createMetaClient(storage, tableBasePath));
+ assertRecordCount(1000, tableBasePath, sqlContext);
+ TestHelpers.assertCommitMetadata("00000", tableBasePath, 1);
+ TableSchemaResolver tableSchemaResolver = new TableSchemaResolver(
+ HoodieTestUtils.createMetaClient(storage, tableBasePath));
+ Schema tableSchema = tableSchemaResolver.getTableAvroSchema(false);
+ assertEquals("timestamp-millis", tableSchema.getField("current_ts").schema().getLogicalType().getName());
+ assertEquals(1000, sqlContext.read().options(hudiOpts).format("org.apache.hudi").load(tableBasePath).filter("current_ts > '1980-01-01'").count());
+
+ cfg = TestHelpers.makeConfig(tableBasePath, WriteOperationType.UPSERT, Collections.singletonList(TestIdentityTransformer.class.getName()),
+ PROPS_FILENAME_TEST_SOURCE, false, true, false, null, HoodieTableType.MERGE_ON_READ.name());
+ cfg.payloadClassName = DefaultHoodieRecordPayload.class.getName();
+ cfg.recordMergeStrategyId = HoodieRecordMerger.EVENT_TIME_BASED_MERGE_STRATEGY_UUID;
+ cfg.recordMergeMode = RecordMergeMode.EVENT_TIME_ORDERING;
+ cfg.configs.add("hoodie.streamer.schemaprovider.source.schema.file=" + basePath + "/source-timestamp-millis.avsc");
+ cfg.configs.add("hoodie.streamer.schemaprovider.target.schema.file=" + basePath + "/source-timestamp-millis.avsc");
+ cfg.configs.add(String.format("%s=%s", HoodieCompactionConfig.PARQUET_SMALL_FILE_LIMIT.key(), "0"));
+
+ new HoodieDeltaStreamer(cfg, jsc).sync();
+ assertUseV2Checkpoint(HoodieTestUtils.createMetaClient(storage, tableBasePath));
+ assertRecordCount(1450, tableBasePath, sqlContext);
+ TestHelpers.assertCommitMetadata("00001", tableBasePath, 2);
+ tableSchemaResolver = new TableSchemaResolver(
+ HoodieTestUtils.createMetaClient(storage, tableBasePath));
+ tableSchema = tableSchemaResolver.getTableAvroSchema(false);
+ assertEquals("timestamp-millis", tableSchema.getField("current_ts").schema().getLogicalType().getName());
+ sqlContext.clearCache();
+ assertEquals(1450, sqlContext.read().options(hudiOpts).format("org.apache.hudi").load(tableBasePath).filter("current_ts > '1980-01-01'").count());
+ assertEquals(1450, sqlContext.read().options(hudiOpts).format("org.apache.hudi").load(tableBasePath).filter("current_ts < '2080-01-01'").count());
+ assertEquals(0, sqlContext.read().options(hudiOpts).format("org.apache.hudi").load(tableBasePath).filter("current_ts < '1980-01-01'").count());
+ }
+
+ @Test
+ public void testLogicalTypes() throws Exception {
Review Comment:
for 6 and 8 skip validation of the broken types
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3294258829
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
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URL: https://github.com/apache/hudi/pull/13711#issuecomment-3294366628
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* 672ce5bdd591130363ac984e77e7a31cc1424369 UNKNOWN
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* 3630ba26e8964bfa0f052261ef2367977cb08d16 Azure: [FAILURE](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=8543)
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2350298656
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/utils/SparkValueMetadata.java:
##########
@@ -0,0 +1,230 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.client.utils;
+
+import org.apache.hudi.SparkAdapterSupport$;
+import org.apache.hudi.avro.ValueMetadata;
+import org.apache.hudi.avro.ValueType;
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.ArrayComparable;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.spark.sql.types.ArrayType;
+import org.apache.spark.sql.types.BinaryType;
+import org.apache.spark.sql.types.BooleanType;
+import org.apache.spark.sql.types.ByteType;
+import org.apache.spark.sql.types.CharType;
+import org.apache.spark.sql.types.DataType;
+import org.apache.spark.sql.types.DateType;
+import org.apache.spark.sql.types.Decimal;
+import org.apache.spark.sql.types.DecimalType;
+import org.apache.spark.sql.types.DoubleType;
+import org.apache.spark.sql.types.FloatType;
+import org.apache.spark.sql.types.IntegerType;
+import org.apache.spark.sql.types.LongType;
+import org.apache.spark.sql.types.NullType;
+import org.apache.spark.sql.types.ShortType;
+import org.apache.spark.sql.types.StringType;
+import org.apache.spark.sql.types.TimestampType;
+import org.apache.spark.sql.types.VarcharType;
+
+import java.sql.Date;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.util.Arrays;
+
+public class SparkValueMetadata extends ValueMetadata {
+
+ private final DataType dataType;
+
+ protected SparkValueMetadata(ValueType valueType, DataType dataType) {
+ super(valueType);
+ this.dataType = dataType;
+ }
+
+ public Comparable convertSparkToJava(Object value) {
+ return convertSparkToJava(value, true);
+ }
+
+ public static SparkValueMetadata getValueMetadata(DataType dataType, HoodieIndexVersion indexVersion) {
+ if (indexVersion.lowerThan(HoodieIndexVersion.V2)) {
+ return SparkV1EmptyMetadata.get();
+ }
+ if (dataType == null) {
+ return new SparkValueMetadata(ValueType.NULL, null);
+ }
+ ValueType valueType = fromDataType(dataType);
+ if (valueType == ValueType.DECIMAL) {
+ return new SparkDecimalMetadata((DecimalType) dataType);
+ } else {
+ return new SparkValueMetadata(valueType, dataType);
+ }
+ }
+
+ private static ValueType fromDataType(DataType dataType) {
+ return fromDataType(dataType, true);
+ }
+
+ private static ValueType fromDataType(DataType dataType, boolean root) {
+ if (dataType instanceof NullType) {
+ return ValueType.NULL;
+ } else if (dataType instanceof BooleanType) {
+ return ValueType.BOOLEAN;
+ } else if (dataType instanceof IntegerType || dataType instanceof ShortType || dataType instanceof ByteType) {
+ return ValueType.INT;
+ } else if (dataType instanceof LongType) {
+ return ValueType.LONG;
+ } else if (dataType instanceof FloatType) {
+ return ValueType.FLOAT;
+ } else if (dataType instanceof DoubleType) {
+ return ValueType.DOUBLE;
+ } else if (dataType instanceof StringType || dataType instanceof CharType || dataType instanceof VarcharType) {
+ return ValueType.STRING;
+ } else if (dataType instanceof TimestampType) {
+ return ValueType.TIMESTAMP_MICROS;
+ } else if (dataType instanceof DecimalType) {
+ return ValueType.DECIMAL;
+ } else if (dataType instanceof DateType) {
+ return ValueType.DATE;
+ } else if (dataType instanceof BinaryType) {
+ return ValueType.BYTES;
+ } else if (dataType instanceof ArrayType) {
+ if (root) {
+ return fromDataType(((ArrayType) dataType).elementType(), false);
+ } else {
+ throw new IllegalArgumentException("Array of Array is not supported");
+ }
+ } else if (SparkAdapterSupport$.MODULE$.sparkAdapter().isTimestampNTZType(dataType)) {
+ return ValueType.LOCAL_TIMESTAMP_MICROS;
Review Comment:
Similar question around `local-timestamp-millis` if `TimestampNTZType` is used; is this a valid case to handle?
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/utils/SparkValueMetadata.java:
##########
@@ -0,0 +1,230 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.client.utils;
+
+import org.apache.hudi.SparkAdapterSupport$;
+import org.apache.hudi.avro.ValueMetadata;
+import org.apache.hudi.avro.ValueType;
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.ArrayComparable;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.spark.sql.types.ArrayType;
+import org.apache.spark.sql.types.BinaryType;
+import org.apache.spark.sql.types.BooleanType;
+import org.apache.spark.sql.types.ByteType;
+import org.apache.spark.sql.types.CharType;
+import org.apache.spark.sql.types.DataType;
+import org.apache.spark.sql.types.DateType;
+import org.apache.spark.sql.types.Decimal;
+import org.apache.spark.sql.types.DecimalType;
+import org.apache.spark.sql.types.DoubleType;
+import org.apache.spark.sql.types.FloatType;
+import org.apache.spark.sql.types.IntegerType;
+import org.apache.spark.sql.types.LongType;
+import org.apache.spark.sql.types.NullType;
+import org.apache.spark.sql.types.ShortType;
+import org.apache.spark.sql.types.StringType;
+import org.apache.spark.sql.types.TimestampType;
+import org.apache.spark.sql.types.VarcharType;
+
+import java.sql.Date;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.util.Arrays;
+
+public class SparkValueMetadata extends ValueMetadata {
+
+ private final DataType dataType;
+
+ protected SparkValueMetadata(ValueType valueType, DataType dataType) {
+ super(valueType);
+ this.dataType = dataType;
+ }
+
+ public Comparable convertSparkToJava(Object value) {
+ return convertSparkToJava(value, true);
+ }
+
+ public static SparkValueMetadata getValueMetadata(DataType dataType, HoodieIndexVersion indexVersion) {
+ if (indexVersion.lowerThan(HoodieIndexVersion.V2)) {
+ return SparkV1EmptyMetadata.get();
+ }
+ if (dataType == null) {
+ return new SparkValueMetadata(ValueType.NULL, null);
+ }
+ ValueType valueType = fromDataType(dataType);
+ if (valueType == ValueType.DECIMAL) {
+ return new SparkDecimalMetadata((DecimalType) dataType);
+ } else {
+ return new SparkValueMetadata(valueType, dataType);
+ }
+ }
+
+ private static ValueType fromDataType(DataType dataType) {
+ return fromDataType(dataType, true);
+ }
+
+ private static ValueType fromDataType(DataType dataType, boolean root) {
+ if (dataType instanceof NullType) {
+ return ValueType.NULL;
+ } else if (dataType instanceof BooleanType) {
+ return ValueType.BOOLEAN;
+ } else if (dataType instanceof IntegerType || dataType instanceof ShortType || dataType instanceof ByteType) {
+ return ValueType.INT;
+ } else if (dataType instanceof LongType) {
+ return ValueType.LONG;
+ } else if (dataType instanceof FloatType) {
+ return ValueType.FLOAT;
+ } else if (dataType instanceof DoubleType) {
+ return ValueType.DOUBLE;
+ } else if (dataType instanceof StringType || dataType instanceof CharType || dataType instanceof VarcharType) {
+ return ValueType.STRING;
+ } else if (dataType instanceof TimestampType) {
+ return ValueType.TIMESTAMP_MICROS;
+ } else if (dataType instanceof DecimalType) {
+ return ValueType.DECIMAL;
+ } else if (dataType instanceof DateType) {
+ return ValueType.DATE;
+ } else if (dataType instanceof BinaryType) {
+ return ValueType.BYTES;
+ } else if (dataType instanceof ArrayType) {
+ if (root) {
+ return fromDataType(((ArrayType) dataType).elementType(), false);
+ } else {
+ throw new IllegalArgumentException("Array of Array is not supported");
+ }
+ } else if (SparkAdapterSupport$.MODULE$.sparkAdapter().isTimestampNTZType(dataType)) {
+ return ValueType.LOCAL_TIMESTAMP_MICROS;
+ } else {
+ throw new IllegalArgumentException("Unsupported data type: " + dataType);
+ }
+ }
+
+ private static class SparkV1EmptyMetadata extends SparkValueMetadata {
Review Comment:
Add Javadocs. Is this used for V1 column stats by setting `valueType` as null in the metadata record?
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/utils/SparkValueMetadata.java:
##########
@@ -0,0 +1,230 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.client.utils;
+
+import org.apache.hudi.SparkAdapterSupport$;
+import org.apache.hudi.avro.ValueMetadata;
+import org.apache.hudi.avro.ValueType;
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.ArrayComparable;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.spark.sql.types.ArrayType;
+import org.apache.spark.sql.types.BinaryType;
+import org.apache.spark.sql.types.BooleanType;
+import org.apache.spark.sql.types.ByteType;
+import org.apache.spark.sql.types.CharType;
+import org.apache.spark.sql.types.DataType;
+import org.apache.spark.sql.types.DateType;
+import org.apache.spark.sql.types.Decimal;
+import org.apache.spark.sql.types.DecimalType;
+import org.apache.spark.sql.types.DoubleType;
+import org.apache.spark.sql.types.FloatType;
+import org.apache.spark.sql.types.IntegerType;
+import org.apache.spark.sql.types.LongType;
+import org.apache.spark.sql.types.NullType;
+import org.apache.spark.sql.types.ShortType;
+import org.apache.spark.sql.types.StringType;
+import org.apache.spark.sql.types.TimestampType;
+import org.apache.spark.sql.types.VarcharType;
+
+import java.sql.Date;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.util.Arrays;
+
+public class SparkValueMetadata extends ValueMetadata {
+
+ private final DataType dataType;
+
+ protected SparkValueMetadata(ValueType valueType, DataType dataType) {
+ super(valueType);
+ this.dataType = dataType;
+ }
+
+ public Comparable convertSparkToJava(Object value) {
+ return convertSparkToJava(value, true);
+ }
+
+ public static SparkValueMetadata getValueMetadata(DataType dataType, HoodieIndexVersion indexVersion) {
+ if (indexVersion.lowerThan(HoodieIndexVersion.V2)) {
+ return SparkV1EmptyMetadata.get();
+ }
+ if (dataType == null) {
+ return new SparkValueMetadata(ValueType.NULL, null);
+ }
+ ValueType valueType = fromDataType(dataType);
+ if (valueType == ValueType.DECIMAL) {
+ return new SparkDecimalMetadata((DecimalType) dataType);
+ } else {
+ return new SparkValueMetadata(valueType, dataType);
+ }
+ }
+
+ private static ValueType fromDataType(DataType dataType) {
+ return fromDataType(dataType, true);
+ }
+
+ private static ValueType fromDataType(DataType dataType, boolean root) {
+ if (dataType instanceof NullType) {
+ return ValueType.NULL;
+ } else if (dataType instanceof BooleanType) {
+ return ValueType.BOOLEAN;
+ } else if (dataType instanceof IntegerType || dataType instanceof ShortType || dataType instanceof ByteType) {
+ return ValueType.INT;
+ } else if (dataType instanceof LongType) {
+ return ValueType.LONG;
+ } else if (dataType instanceof FloatType) {
+ return ValueType.FLOAT;
+ } else if (dataType instanceof DoubleType) {
+ return ValueType.DOUBLE;
+ } else if (dataType instanceof StringType || dataType instanceof CharType || dataType instanceof VarcharType) {
+ return ValueType.STRING;
+ } else if (dataType instanceof TimestampType) {
+ return ValueType.TIMESTAMP_MICROS;
+ } else if (dataType instanceof DecimalType) {
+ return ValueType.DECIMAL;
+ } else if (dataType instanceof DateType) {
+ return ValueType.DATE;
+ } else if (dataType instanceof BinaryType) {
+ return ValueType.BYTES;
+ } else if (dataType instanceof ArrayType) {
+ if (root) {
+ return fromDataType(((ArrayType) dataType).elementType(), false);
+ } else {
+ throw new IllegalArgumentException("Array of Array is not supported");
+ }
+ } else if (SparkAdapterSupport$.MODULE$.sparkAdapter().isTimestampNTZType(dataType)) {
+ return ValueType.LOCAL_TIMESTAMP_MICROS;
+ } else {
+ throw new IllegalArgumentException("Unsupported data type: " + dataType);
+ }
+ }
+
+ private static class SparkV1EmptyMetadata extends SparkValueMetadata {
+ private static final SparkV1EmptyMetadata V_1_EMPTY_METADATA = new SparkV1EmptyMetadata();
+ public static SparkV1EmptyMetadata get() {
+ return V_1_EMPTY_METADATA;
+ }
+
+ private SparkV1EmptyMetadata() {
+ super(ValueType.V1, null);
+ }
+
+ @Override
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ return null;
+ }
+ }
+
+ private static class SparkDecimalMetadata extends SparkValueMetadata implements ValueMetadata.DecimalValueMetadata {
+
+ private final int precision;
+ private final int scale;
+
+ protected SparkDecimalMetadata(DecimalType decimalType) {
+ super(ValueType.DECIMAL, decimalType);
+ this.precision = decimalType.precision();
+ this.scale = decimalType.scale();
+ }
+
+ @Override
+ public int getPrecision() {
+ return precision;
+ }
+
+ @Override
+ public int getScale() {
+ return scale;
+ }
+
+ @Override
+ public String getAdditionalInfo() {
+ return DecimalValueMetadata.encodeData(this);
+ }
+ }
+
+ private Comparable convertSparkToJava(Object value, boolean rootLevel) {
+ if (value == null) {
+ return null;
+ }
+
+ if (value instanceof org.apache.spark.sql.catalyst.util.ArrayData) {
+ if (rootLevel) {
+ return new ArrayComparable(Arrays.stream(((org.apache.spark.sql.catalyst.util.ArrayData) value)
+ .toObjectArray(((org.apache.spark.sql.types.ArrayType) dataType).elementType()))
+ .map(v -> convertSparkToJava(v, false)).toArray(Comparable[]::new));
+ } else {
+ throw new IllegalArgumentException("array of arrays not supported");
+ }
+ }
Review Comment:
Is this for both V1 and V2 column stats index? Should we add `ARRAY` as `ValueType` here?
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/utils/SparkValueMetadata.java:
##########
@@ -0,0 +1,230 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.client.utils;
+
+import org.apache.hudi.SparkAdapterSupport$;
+import org.apache.hudi.avro.ValueMetadata;
+import org.apache.hudi.avro.ValueType;
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.ArrayComparable;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.spark.sql.types.ArrayType;
+import org.apache.spark.sql.types.BinaryType;
+import org.apache.spark.sql.types.BooleanType;
+import org.apache.spark.sql.types.ByteType;
+import org.apache.spark.sql.types.CharType;
+import org.apache.spark.sql.types.DataType;
+import org.apache.spark.sql.types.DateType;
+import org.apache.spark.sql.types.Decimal;
+import org.apache.spark.sql.types.DecimalType;
+import org.apache.spark.sql.types.DoubleType;
+import org.apache.spark.sql.types.FloatType;
+import org.apache.spark.sql.types.IntegerType;
+import org.apache.spark.sql.types.LongType;
+import org.apache.spark.sql.types.NullType;
+import org.apache.spark.sql.types.ShortType;
+import org.apache.spark.sql.types.StringType;
+import org.apache.spark.sql.types.TimestampType;
+import org.apache.spark.sql.types.VarcharType;
+
+import java.sql.Date;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.util.Arrays;
+
+public class SparkValueMetadata extends ValueMetadata {
+
+ private final DataType dataType;
+
+ protected SparkValueMetadata(ValueType valueType, DataType dataType) {
+ super(valueType);
+ this.dataType = dataType;
+ }
+
+ public Comparable convertSparkToJava(Object value) {
+ return convertSparkToJava(value, true);
+ }
+
+ public static SparkValueMetadata getValueMetadata(DataType dataType, HoodieIndexVersion indexVersion) {
+ if (indexVersion.lowerThan(HoodieIndexVersion.V2)) {
+ return SparkV1EmptyMetadata.get();
+ }
+ if (dataType == null) {
+ return new SparkValueMetadata(ValueType.NULL, null);
+ }
+ ValueType valueType = fromDataType(dataType);
+ if (valueType == ValueType.DECIMAL) {
+ return new SparkDecimalMetadata((DecimalType) dataType);
+ } else {
+ return new SparkValueMetadata(valueType, dataType);
+ }
+ }
+
+ private static ValueType fromDataType(DataType dataType) {
+ return fromDataType(dataType, true);
+ }
+
+ private static ValueType fromDataType(DataType dataType, boolean root) {
+ if (dataType instanceof NullType) {
+ return ValueType.NULL;
+ } else if (dataType instanceof BooleanType) {
+ return ValueType.BOOLEAN;
+ } else if (dataType instanceof IntegerType || dataType instanceof ShortType || dataType instanceof ByteType) {
+ return ValueType.INT;
+ } else if (dataType instanceof LongType) {
+ return ValueType.LONG;
+ } else if (dataType instanceof FloatType) {
+ return ValueType.FLOAT;
+ } else if (dataType instanceof DoubleType) {
+ return ValueType.DOUBLE;
+ } else if (dataType instanceof StringType || dataType instanceof CharType || dataType instanceof VarcharType) {
+ return ValueType.STRING;
+ } else if (dataType instanceof TimestampType) {
+ return ValueType.TIMESTAMP_MICROS;
+ } else if (dataType instanceof DecimalType) {
+ return ValueType.DECIMAL;
+ } else if (dataType instanceof DateType) {
+ return ValueType.DATE;
+ } else if (dataType instanceof BinaryType) {
+ return ValueType.BYTES;
+ } else if (dataType instanceof ArrayType) {
+ if (root) {
+ return fromDataType(((ArrayType) dataType).elementType(), false);
+ } else {
+ throw new IllegalArgumentException("Array of Array is not supported");
+ }
+ } else if (SparkAdapterSupport$.MODULE$.sparkAdapter().isTimestampNTZType(dataType)) {
+ return ValueType.LOCAL_TIMESTAMP_MICROS;
+ } else {
+ throw new IllegalArgumentException("Unsupported data type: " + dataType);
+ }
+ }
+
+ private static class SparkV1EmptyMetadata extends SparkValueMetadata {
+ private static final SparkV1EmptyMetadata V_1_EMPTY_METADATA = new SparkV1EmptyMetadata();
Review Comment:
```suggestion
private static final SparkV1EmptyMetadata V1_EMPTY_METADATA = new SparkV1EmptyMetadata();
```
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/utils/SparkValueMetadata.java:
##########
@@ -0,0 +1,230 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.client.utils;
+
+import org.apache.hudi.SparkAdapterSupport$;
+import org.apache.hudi.avro.ValueMetadata;
+import org.apache.hudi.avro.ValueType;
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.ArrayComparable;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.spark.sql.types.ArrayType;
+import org.apache.spark.sql.types.BinaryType;
+import org.apache.spark.sql.types.BooleanType;
+import org.apache.spark.sql.types.ByteType;
+import org.apache.spark.sql.types.CharType;
+import org.apache.spark.sql.types.DataType;
+import org.apache.spark.sql.types.DateType;
+import org.apache.spark.sql.types.Decimal;
+import org.apache.spark.sql.types.DecimalType;
+import org.apache.spark.sql.types.DoubleType;
+import org.apache.spark.sql.types.FloatType;
+import org.apache.spark.sql.types.IntegerType;
+import org.apache.spark.sql.types.LongType;
+import org.apache.spark.sql.types.NullType;
+import org.apache.spark.sql.types.ShortType;
+import org.apache.spark.sql.types.StringType;
+import org.apache.spark.sql.types.TimestampType;
+import org.apache.spark.sql.types.VarcharType;
+
+import java.sql.Date;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.util.Arrays;
+
+public class SparkValueMetadata extends ValueMetadata {
+
+ private final DataType dataType;
+
+ protected SparkValueMetadata(ValueType valueType, DataType dataType) {
+ super(valueType);
+ this.dataType = dataType;
+ }
+
+ public Comparable convertSparkToJava(Object value) {
+ return convertSparkToJava(value, true);
+ }
+
+ public static SparkValueMetadata getValueMetadata(DataType dataType, HoodieIndexVersion indexVersion) {
+ if (indexVersion.lowerThan(HoodieIndexVersion.V2)) {
+ return SparkV1EmptyMetadata.get();
+ }
+ if (dataType == null) {
+ return new SparkValueMetadata(ValueType.NULL, null);
+ }
+ ValueType valueType = fromDataType(dataType);
+ if (valueType == ValueType.DECIMAL) {
+ return new SparkDecimalMetadata((DecimalType) dataType);
+ } else {
+ return new SparkValueMetadata(valueType, dataType);
+ }
+ }
+
+ private static ValueType fromDataType(DataType dataType) {
+ return fromDataType(dataType, true);
+ }
+
+ private static ValueType fromDataType(DataType dataType, boolean root) {
+ if (dataType instanceof NullType) {
+ return ValueType.NULL;
+ } else if (dataType instanceof BooleanType) {
+ return ValueType.BOOLEAN;
+ } else if (dataType instanceof IntegerType || dataType instanceof ShortType || dataType instanceof ByteType) {
+ return ValueType.INT;
+ } else if (dataType instanceof LongType) {
+ return ValueType.LONG;
+ } else if (dataType instanceof FloatType) {
+ return ValueType.FLOAT;
+ } else if (dataType instanceof DoubleType) {
+ return ValueType.DOUBLE;
+ } else if (dataType instanceof StringType || dataType instanceof CharType || dataType instanceof VarcharType) {
+ return ValueType.STRING;
+ } else if (dataType instanceof TimestampType) {
+ return ValueType.TIMESTAMP_MICROS;
+ } else if (dataType instanceof DecimalType) {
+ return ValueType.DECIMAL;
+ } else if (dataType instanceof DateType) {
+ return ValueType.DATE;
+ } else if (dataType instanceof BinaryType) {
+ return ValueType.BYTES;
+ } else if (dataType instanceof ArrayType) {
+ if (root) {
+ return fromDataType(((ArrayType) dataType).elementType(), false);
+ } else {
+ throw new IllegalArgumentException("Array of Array is not supported");
+ }
+ } else if (SparkAdapterSupport$.MODULE$.sparkAdapter().isTimestampNTZType(dataType)) {
+ return ValueType.LOCAL_TIMESTAMP_MICROS;
+ } else {
+ throw new IllegalArgumentException("Unsupported data type: " + dataType);
+ }
+ }
+
+ private static class SparkV1EmptyMetadata extends SparkValueMetadata {
+ private static final SparkV1EmptyMetadata V_1_EMPTY_METADATA = new SparkV1EmptyMetadata();
+ public static SparkV1EmptyMetadata get() {
+ return V_1_EMPTY_METADATA;
+ }
+
+ private SparkV1EmptyMetadata() {
+ super(ValueType.V1, null);
+ }
+
+ @Override
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ return null;
+ }
+ }
+
+ private static class SparkDecimalMetadata extends SparkValueMetadata implements ValueMetadata.DecimalValueMetadata {
+
+ private final int precision;
+ private final int scale;
+
+ protected SparkDecimalMetadata(DecimalType decimalType) {
+ super(ValueType.DECIMAL, decimalType);
+ this.precision = decimalType.precision();
+ this.scale = decimalType.scale();
+ }
+
+ @Override
+ public int getPrecision() {
+ return precision;
+ }
+
+ @Override
+ public int getScale() {
+ return scale;
+ }
+
+ @Override
+ public String getAdditionalInfo() {
+ return DecimalValueMetadata.encodeData(this);
+ }
+ }
+
+ private Comparable convertSparkToJava(Object value, boolean rootLevel) {
+ if (value == null) {
+ return null;
+ }
+
+ if (value instanceof org.apache.spark.sql.catalyst.util.ArrayData) {
+ if (rootLevel) {
+ return new ArrayComparable(Arrays.stream(((org.apache.spark.sql.catalyst.util.ArrayData) value)
+ .toObjectArray(((org.apache.spark.sql.types.ArrayType) dataType).elementType()))
+ .map(v -> convertSparkToJava(v, false)).toArray(Comparable[]::new));
+ } else {
+ throw new IllegalArgumentException("array of arrays not supported");
+ }
+ }
+
+ switch (getValueType()) {
+ case V1:
+ return (Comparable) value;
+ case NULL:
+ return null;
+ case BOOLEAN:
+ return (Boolean) value;
+ case INT:
+ return (Integer) value;
+ case LONG:
+ return (Long) value;
+ case FLOAT:
+ return (Float) value;
+ case DOUBLE:
+ return (Double) value;
+ case STRING:
+ return (String) value;
+ case BYTES:
+ return ValueType.castToBytes(value);
+ case DECIMAL:
+ return ((Decimal) value).toJavaBigDecimal();
+ case DATE:
+ return ValueType.castToDate(value, this);
+ case TIMESTAMP_MICROS:
+ return ValueType.castToTimestampMicros(value, this);
+ case LOCAL_TIMESTAMP_MICROS:
+ return ValueType.castToLocalTimestampMicros(value, this);
+ case FIXED:
+ case UUID:
+ case TIME_MILLIS:
+ case TIME_MICROS:
+ case TIMESTAMP_MILLIS:
+ case TIMESTAMP_NANOS:
+ case LOCAL_TIMESTAMP_MILLIS:
+ case LOCAL_TIMESTAMP_NANOS:
+ default:
+ throw new IllegalStateException("Spark value metadata for expression index should never be " + getValueType().name());
+ }
+ }
+
+ public static Object convertJavaTypeToSparkType(Comparable<?> javaVal, boolean useJava8api) {
+ if (!useJava8api) {
+ if (javaVal instanceof Instant) {
+ return Timestamp.from((Instant) javaVal);
+ } else if (javaVal instanceof LocalDate) {
+ return Date.valueOf((LocalDate) javaVal);
+ }
+ }
+ return javaVal;
Review Comment:
Is this for handling Java 8 vs 11/17?
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3313111975
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2356072699
##########
hudi-common/src/main/java/org/apache/hudi/avro/HoodieAvroWrapperUtils.java:
##########
@@ -238,4 +234,120 @@ private static Pair<Boolean, String> getIsValueWrapperObfuscated(Object statsVal
}
return Pair.of(false, null);
}
+
+ public enum PrimitiveWrapperType {
+ V1(Object.class, HoodieAvroWrapperUtils::wrapValueIntoAvro, HoodieAvroWrapperUtils::unwrapAvroValueWrapper, GenericRecord.class),
+ NULL(Void.class, HoodieAvroWrapperUtils::wrapNull, HoodieAvroWrapperUtils::unwrapNull, Void.class),
Review Comment:
I don't think it's used, but not 100%
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3304030429
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3314202925
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3310339249
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2302273332
##########
hudi-common/src/main/java/org/apache/hudi/metadata/HoodieTableMetadataUtil.java:
##########
@@ -257,7 +257,8 @@ public static Map<String, HoodieColumnRangeMetadata<Comparable>> collectColumnRa
List<Pair<String, Schema.Field>> targetFields,
String filePath,
Schema recordSchema,
- StorageConfiguration<?> storageConfig) {
+ StorageConfiguration<?> storageConfig,
+ HoodieIndexVersion indexVersion) {
Review Comment:
Could the col stats V1 and V2 logic be separated into two methods, `collectColumnRangeMetadataV1` and `collectColumnRangeMetadataV2`? In the future after #13226 is landed, the logic should be contained in `ColumnStatsIndexer` and there will be version-specific indexer implementation. So by doing this, it's easier for future refactoring.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2305219195
##########
hudi-common/src/main/avro/HoodieMetadata.avsc:
##########
@@ -417,6 +417,35 @@
"name": "isTightBound",
"type": "boolean",
"default": false
+ },
+ {
+ "doc": "Value type information containing enum ordinal and optional additional information",
+ "name": "valueType",
+ "type": [
+ "null",
+ {
+ "type": "record",
+ "name": "HoodieValueTypeInfo",
+ "namespace": "org.apache.hudi.avro.model",
+ "fields": [
+ {
+ "doc": "Enum type ordinal representing the value type",
+ "name": "typeOrdinal",
+ "type": "int"
Review Comment:
TODO: we will add tests to assert that the java enums don't change
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3288847036
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3288913747
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3294268934
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3286453725
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3286749462
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3288866658
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## CI report:
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* 96874893a0003d12141450a509c57ad2c81f8386 Azure: [FAILURE](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=8523)
* 5e6b116090215ab08add75d10ad46596bec0d984 UNKNOWN
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2353694941
##########
hudi-common/src/main/java/org/apache/hudi/internal/schema/utils/SchemaChangeUtils.java:
##########
@@ -72,38 +72,59 @@ private static boolean isTypeUpdateAllowInternal(Type src, Type dsr) {
switch (src.typeId()) {
case INT:
return dsr == Types.LongType.get() || dsr == Types.FloatType.get()
- || dsr == Types.DoubleType.get() || dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL;
+ || dsr == Types.DoubleType.get() || dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL || dsr.typeId() == Type.TypeID.DECIMAL_FIXED;
case LONG:
- return dsr == Types.FloatType.get() || dsr == Types.DoubleType.get() || dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL;
+ return dsr == Types.FloatType.get() || dsr == Types.DoubleType.get() || dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL || dsr.typeId() == Type.TypeID.DECIMAL_FIXED;
case FLOAT:
- return dsr == Types.DoubleType.get() || dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL;
+ return dsr == Types.DoubleType.get() || dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL || dsr.typeId() == Type.TypeID.DECIMAL_FIXED;
case DOUBLE:
- return dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL;
+ return dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL || dsr.typeId() == Type.TypeID.DECIMAL_FIXED;
case DATE:
case BINARY:
return dsr == Types.StringType.get();
+ case DECIMAL_BYTES:
+ return isDecimalBytesUpdateAllowInternal(src, dsr);
case DECIMAL:
- if (dsr.typeId() == Type.TypeID.DECIMAL) {
- Types.DecimalType decimalSrc = (Types.DecimalType)src;
- Types.DecimalType decimalDsr = (Types.DecimalType)dsr;
- if (decimalDsr.isWiderThan(decimalSrc)) {
- return true;
- }
- if (decimalDsr.precision() >= decimalSrc.precision() && decimalDsr.scale() == decimalSrc.scale()) {
- return true;
- }
- } else if (dsr.typeId() == Type.TypeID.STRING) {
- return true;
- }
- break;
+ case DECIMAL_FIXED:
+ return isDecimalFixedUpdateAllowInternal(src, dsr);
Review Comment:
Is there internal schema evolution test coverage on `DECIMAL_BYTES` and `DECIMAL_FIXED`?
##########
hudi-common/src/main/java/org/apache/hudi/internal/schema/convert/AvroInternalSchemaConverter.java:
##########
@@ -567,32 +587,27 @@ private static Schema visitInternalPrimitiveToBuildAvroPrimitiveType(Type.Primit
return Schema.createFixed(name, null, null, fixed.getFixedSize());
}
- case DECIMAL: {
- Types.DecimalType decimal = (Types.DecimalType) primitive;
+ case DECIMAL:
+ case DECIMAL_FIXED: {
+ Types.DecimalTypeFixed decimal = (Types.DecimalTypeFixed) primitive;
// NOTE: All schemas corresponding to Avro's type [[FIXED]] are generated
// with the "fixed" name to stay compatible w/ [[SchemaConverters]]
String name = recordName + AVRO_NAME_DELIMITER + "fixed";
Schema fixedSchema = Schema.createFixed(name,
- null, null, computeMinBytesForPrecision(decimal.precision()));
+ null, null, decimal.getFixedSize());
Review Comment:
Is `decimal.getFixedSize()` the same as `computeMinBytesForPrecision`?
##########
hudi-common/src/main/java/org/apache/hudi/internal/schema/utils/SchemaChangeUtils.java:
##########
@@ -72,38 +72,59 @@ private static boolean isTypeUpdateAllowInternal(Type src, Type dsr) {
switch (src.typeId()) {
case INT:
return dsr == Types.LongType.get() || dsr == Types.FloatType.get()
- || dsr == Types.DoubleType.get() || dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL;
+ || dsr == Types.DoubleType.get() || dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL || dsr.typeId() == Type.TypeID.DECIMAL_FIXED;
case LONG:
- return dsr == Types.FloatType.get() || dsr == Types.DoubleType.get() || dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL;
+ return dsr == Types.FloatType.get() || dsr == Types.DoubleType.get() || dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL || dsr.typeId() == Type.TypeID.DECIMAL_FIXED;
case FLOAT:
- return dsr == Types.DoubleType.get() || dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL;
+ return dsr == Types.DoubleType.get() || dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL || dsr.typeId() == Type.TypeID.DECIMAL_FIXED;
case DOUBLE:
- return dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL;
+ return dsr == Types.StringType.get() || dsr.typeId() == Type.TypeID.DECIMAL || dsr.typeId() == Type.TypeID.DECIMAL_FIXED;
case DATE:
case BINARY:
return dsr == Types.StringType.get();
+ case DECIMAL_BYTES:
+ return isDecimalBytesUpdateAllowInternal(src, dsr);
case DECIMAL:
- if (dsr.typeId() == Type.TypeID.DECIMAL) {
- Types.DecimalType decimalSrc = (Types.DecimalType)src;
- Types.DecimalType decimalDsr = (Types.DecimalType)dsr;
- if (decimalDsr.isWiderThan(decimalSrc)) {
- return true;
- }
- if (decimalDsr.precision() >= decimalSrc.precision() && decimalDsr.scale() == decimalSrc.scale()) {
- return true;
- }
- } else if (dsr.typeId() == Type.TypeID.STRING) {
- return true;
- }
- break;
+ case DECIMAL_FIXED:
+ return isDecimalFixedUpdateAllowInternal(src, dsr);
case STRING:
- return dsr == Types.DateType.get() || dsr.typeId() == Type.TypeID.DECIMAL || dsr == Types.BinaryType.get();
+ return dsr == Types.DateType.get() || dsr.typeId() == Type.TypeID.DECIMAL || dsr.typeId() == Type.TypeID.DECIMAL_FIXED || dsr == Types.BinaryType.get();
default:
return false;
}
+ }
+
+ private static boolean isDecimalBytesUpdateAllowInternal(Type src, Type dsr) {
Review Comment:
nit: is `dsr` a typo, i.e., it should be `dst`?
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2359345608
##########
hudi-common/src/test/resources/nullWrong.avsc:
##########
@@ -197,7 +197,48 @@
},
"null"
]
- }
+ },
+ {
+ "name": "timeMicroField",
Review Comment:
Got it. As long as there is a reason for it, we can keep the fields here.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2353726715
##########
hudi-common/src/main/java/org/apache/hudi/internal/schema/convert/AvroInternalSchemaConverter.java:
##########
@@ -567,32 +587,27 @@ private static Schema visitInternalPrimitiveToBuildAvroPrimitiveType(Type.Primit
return Schema.createFixed(name, null, null, fixed.getFixedSize());
}
- case DECIMAL: {
- Types.DecimalType decimal = (Types.DecimalType) primitive;
+ case DECIMAL:
+ case DECIMAL_FIXED: {
+ Types.DecimalTypeFixed decimal = (Types.DecimalTypeFixed) primitive;
// NOTE: All schemas corresponding to Avro's type [[FIXED]] are generated
// with the "fixed" name to stay compatible w/ [[SchemaConverters]]
String name = recordName + AVRO_NAME_DELIMITER + "fixed";
Schema fixedSchema = Schema.createFixed(name,
- null, null, computeMinBytesForPrecision(decimal.precision()));
+ null, null, decimal.getFixedSize());
Review Comment:
Yes
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2354145201
##########
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/hudi/functional/ColumnStatIndexTestBase.scala:
##########
@@ -334,24 +334,24 @@ class ColumnStatIndexTestBase extends HoodieSparkClientTestBase {
val metadataConfig = HoodieMetadataConfig.newBuilder()
.fromProperties(toProperties(metadataOpts))
.build()
-
- val pStatsIndex = new PartitionStatsIndexSupport(spark, sourceTableSchema, metadataConfig, metaClient)
-
val schemaUtil = new TableSchemaResolver(metaClient)
val tableSchema = schemaUtil.getTableAvroSchema(false)
+ val localSourceTableSchema = AvroConversionUtils.convertAvroSchemaToStructType(tableSchema)
+
+ val pStatsIndex = new PartitionStatsIndexSupport(spark, localSourceTableSchema, metadataConfig, metaClient)
val indexedColumnswithMeta: Set[String] = metaClient.getIndexMetadata.get().getIndexDefinitions.get(PARTITION_NAME_COLUMN_STATS).getSourceFields.asScala.toSet
val pIndexedColumns = indexedColumnswithMeta.filter(colName => !HoodieTableMetadataUtil.META_COL_SET_TO_INDEX.contains(colName))
.toSeq.sorted
- val (pExpectedColStatsSchema, _) = composeIndexSchema(pIndexedColumns, pIndexedColumns, sourceTableSchema)
+ val (pExpectedColStatsSchema, _) = composeIndexSchema(pIndexedColumns, pIndexedColumns, localSourceTableSchema)
Review Comment:
Yes. And if you go to the above method, the same change was made there, but forgot in this one
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2354122882
##########
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/spark/sql/hudi/feature/index/TestExpressionIndex.scala:
##########
@@ -1548,28 +1550,28 @@ class TestExpressionIndex extends HoodieSparkSqlTestBase {
spark.sql(s"create index idx_to_timestamp_default on $tableName using column_stats(date) options(expr='to_timestamp')")
metaClient = HoodieTableMetaClient.reload(metaClient)
val toTimestampDefault = resolveExpr(spark, unapply(functions.to_timestamp(functions.col("date"))).get, tableSchema)
- dataFilter = EqualTo(toTimestampDefault, lit(1732924800000000L).expr)
+ dataFilter = EqualTo(toTimestampDefault, lit(SparkValueMetadata.convertJavaTypeToSparkType(ValueType.toTimestampMicros(1732924800000000L, null), false)).expr)
verifyFilePruning(opts, dataFilter, metaClient, isDataSkippingExpected = true)
spark.sql(s"drop index idx_to_timestamp_default on $tableName")
spark.sql(s"create index idx_to_timestamp on $tableName using column_stats(date) options(expr='to_timestamp', format='yyyy-MM-dd')")
metaClient = HoodieTableMetaClient.reload(metaClient)
val toTimestamp = resolveExpr(spark, unapply(functions.to_timestamp(functions.col("date"), "yyyy-MM-dd")).get, tableSchema)
- dataFilter = EqualTo(toTimestamp, lit(1732924800000000L).expr)
+ dataFilter = EqualTo(toTimestamp, lit(SparkValueMetadata.convertJavaTypeToSparkType(ValueType.toTimestampMicros(1732924800000000L, null), false)).expr)
verifyFilePruning(opts, dataFilter, metaClient, isDataSkippingExpected = true)
spark.sql(s"drop index idx_to_timestamp on $tableName")
spark.sql(s"create index idx_date_add on $tableName using column_stats(date) options(expr='date_add', days='10')")
metaClient = HoodieTableMetaClient.reload(metaClient)
val dateAdd = resolveExpr(spark, unapply(functions.date_add(functions.col("date"), 10)).get, tableSchema)
- dataFilter = EqualTo(dateAdd, lit(18606).expr)
+ dataFilter = EqualTo(dateAdd, lit(HoodieAvroUtils.toJavaDate(18606)).expr)
verifyFilePruning(opts, dataFilter, metaClient, isDataSkippingExpected = true)
spark.sql(s"drop index idx_date_add on $tableName")
spark.sql(s"create index idx_date_sub on $tableName using column_stats(date) options(expr='date_sub', days='10')")
metaClient = HoodieTableMetaClient.reload(metaClient)
val dateSub = resolveExpr(spark, unapply(functions.date_sub(functions.col("date"), 10)).get, tableSchema)
- dataFilter = EqualTo(dateSub, lit(18586).expr)
+ dataFilter = EqualTo(dateSub, lit(HoodieAvroUtils.toJavaDate(18586)).expr)
Review Comment:
I think it was wrong before. If you look at `functions.date_add` it says it returns a date, not a long. All the changes in this file are where the return type didn't match and I had to fix it
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2359667885
##########
hudi-common/src/main/java/org/apache/hudi/stats/ValueType.java:
##########
@@ -0,0 +1,668 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.avro.AvroSchemaUtils;
+import org.apache.hudi.avro.HoodieAvroWrapperUtils;
+import org.apache.hudi.common.util.DateTimeUtils;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.avro.util.Utf8;
+import org.apache.parquet.io.api.Binary;
+import org.apache.parquet.schema.LogicalTypeTokenParser;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.math.BigDecimal;
+import java.math.BigInteger;
+import java.math.MathContext;
+import java.math.RoundingMode;
+import java.nio.ByteBuffer;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.time.LocalDateTime;
+import java.time.LocalTime;
+import java.time.ZoneOffset;
+import java.util.Objects;
+import java.util.UUID;
+import java.util.function.BiFunction;
+import java.util.function.Function;
+
+import static org.apache.hudi.avro.HoodieAvroUtils.convertBytesToBigDecimal;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToMicros;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToNanos;
+import static org.apache.hudi.common.util.DateTimeUtils.microsToInstant;
+import static org.apache.hudi.common.util.DateTimeUtils.nanosToInstant;
+import static org.apache.hudi.common.util.StringUtils.getUTF8Bytes;
+
+public enum ValueType {
+ V1(HoodieAvroWrapperUtils.PrimitiveWrapperType.V1.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.V1,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ NULL(HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ BOOLEAN(HoodieAvroWrapperUtils.PrimitiveWrapperType.BOOLEAN, ValueType::castToBoolean),
+ INT(HoodieAvroWrapperUtils.PrimitiveWrapperType.INT, ValueType::castToInteger),
+ LONG(HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG, ValueType::castToLong),
+ FLOAT(HoodieAvroWrapperUtils.PrimitiveWrapperType.FLOAT, ValueType::castToFloat),
+ DOUBLE(HoodieAvroWrapperUtils.PrimitiveWrapperType.DOUBLE, ValueType::castToDouble),
+ STRING(HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING, ValueType::castToString),
+ BYTES(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToBytes),
+ FIXED(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToFixed),
+ DECIMAL(BigDecimal.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES,
+ ValueType::castToDecimal, ValueType::toDecimal, ValueType::fromDecimal),
+ UUID(UUID.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING,
+ ValueType::castToUUID, ValueType::toUUID, ValueType::fromUUID),
+ DATE(LocalDate.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToDate, ValueType::toDate, ValueType::fromDate),
+ TIME_MILLIS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToTimeMillis, ValueType::toTimeMillis, ValueType::fromTimeMillis),
+ TIME_MICROS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimeMicros, ValueType::toTimeMicros, ValueType::fromTimeMicros),
+ TIMESTAMP_MILLIS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMillis, ValueType::toTimestampMillis, ValueType::fromTimestampMillis),
+ TIMESTAMP_MICROS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMicros, ValueType::toTimestampMicros, ValueType::fromTimestampMicros),
+ TIMESTAMP_NANOS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampNanos, ValueType::toTimestampNanos, ValueType::fromTimestampNanos),
+ LOCAL_TIMESTAMP_MILLIS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMillis, ValueType::toLocalTimestampMillis, ValueType::fromLocalTimestampMillis),
+ LOCAL_TIMESTAMP_MICROS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMicros, ValueType::toLocalTimestampMicros, ValueType::fromLocalTimestampMicros),
+ LOCAL_TIMESTAMP_NANOS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampNanos, ValueType::toLocalTimestampNanos, ValueType::fromLocalTimestampNanos);
+
+ private final Class<?> internalType;
+ private final HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType;
+ private final BiFunction<Object, ValueMetadata, Comparable<?>> standardize;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex;
Review Comment:
Or we could use `toComposite` if it's not entirely for logical types. Also, adding docs to the methods will make it clear.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2352774263
##########
hudi-client/hudi-spark-client/src/main/scala/org/apache/hudi/BaseSparkInternalRecordContext.java:
##########
@@ -56,17 +68,59 @@ public BaseSparkInternalRecordContext(HoodieTableConfig tableConfig) {
}
public static Object getFieldValueFromInternalRow(InternalRow row, Schema recordSchema, String fieldName) {
+ return getFieldValueFromInternalRowInternal(row, recordSchema, fieldName, false);
+ }
+
+ public static Object getFieldValueFromInternalRowAsJava(InternalRow row, Schema recordSchema, String fieldName) {
+ return getFieldValueFromInternalRowInternal(row, recordSchema, fieldName, true);
+ }
+
+ private static Object getFieldValueFromInternalRowInternal(InternalRow row, Schema recordSchema, String fieldName, boolean convertToJavaType) {
StructType structType = getCachedSchema(recordSchema);
scala.Option<HoodieUnsafeRowUtils.NestedFieldPath> cachedNestedFieldPath =
HoodieInternalRowUtils.getCachedPosList(structType, fieldName);
if (cachedNestedFieldPath.isDefined()) {
HoodieUnsafeRowUtils.NestedFieldPath nestedFieldPath = cachedNestedFieldPath.get();
- return HoodieUnsafeRowUtils.getNestedInternalRowValue(row, nestedFieldPath);
+ Object value = HoodieUnsafeRowUtils.getNestedInternalRowValue(row, nestedFieldPath);
+ if (!convertToJavaType) {
+ return value;
+ }
+ return sparkTypeToJavaType(value, nestedFieldPath.parts()[nestedFieldPath.parts().length - 1]._2.dataType());
} else {
return null;
}
}
+
+ public static Object sparkTypeToJavaType(Object value, DataType dataType) {
+ if (value == null) {
+ return null;
+ } else if (value instanceof UTF8String) {
+ return ((UTF8String) value).toString();
+ } else if (value instanceof Decimal) {
+ return ((Decimal) value).toJavaBigDecimal();
+ } else if (value instanceof byte[]) {
+ return ByteBuffer.wrap((byte[]) value);
+ } else if (value instanceof org.apache.spark.sql.catalyst.util.ArrayData) {
+ Comparable[] values = Arrays.stream(((org.apache.spark.sql.catalyst.util.ArrayData) value)
+ .toObjectArray(((org.apache.spark.sql.types.ArrayType) dataType).elementType()))
+ .map(v -> {
+ if (v instanceof ArrayData) {
+ throw new UnsupportedOperationException("cannot have nested arrays?");
+ } else {
+ return (Comparable) sparkTypeToJavaType(v, null);
+ }
+ }).toArray(Comparable[]::new);
+ return new ArrayComparable(values);
Review Comment:
I think there is no standard way to store min and max values of Array or List type field and how the min and max should be leveraged when doing data skipping (i.e., what should be expected ordering when comparing arrays or lists), so I suggest that for column stats index, such fields should be excluded from generating the min and max to avoid confusion.
##########
hudi-client/hudi-spark-client/src/main/scala/org/apache/hudi/BaseSparkInternalRecordContext.java:
##########
@@ -56,17 +68,59 @@ public BaseSparkInternalRecordContext(HoodieTableConfig tableConfig) {
}
public static Object getFieldValueFromInternalRow(InternalRow row, Schema recordSchema, String fieldName) {
+ return getFieldValueFromInternalRowInternal(row, recordSchema, fieldName, false);
+ }
+
+ public static Object getFieldValueFromInternalRowAsJava(InternalRow row, Schema recordSchema, String fieldName) {
Review Comment:
Is `getFieldValueFromInternalRowAsJava` only used by column stat, secondary index, and ordering value / event time?
##########
hudi-client/hudi-spark-client/src/main/scala/org/apache/hudi/BaseSparkInternalRecordContext.java:
##########
@@ -56,17 +68,59 @@ public BaseSparkInternalRecordContext(HoodieTableConfig tableConfig) {
}
public static Object getFieldValueFromInternalRow(InternalRow row, Schema recordSchema, String fieldName) {
+ return getFieldValueFromInternalRowInternal(row, recordSchema, fieldName, false);
+ }
+
+ public static Object getFieldValueFromInternalRowAsJava(InternalRow row, Schema recordSchema, String fieldName) {
+ return getFieldValueFromInternalRowInternal(row, recordSchema, fieldName, true);
+ }
+
+ private static Object getFieldValueFromInternalRowInternal(InternalRow row, Schema recordSchema, String fieldName, boolean convertToJavaType) {
StructType structType = getCachedSchema(recordSchema);
scala.Option<HoodieUnsafeRowUtils.NestedFieldPath> cachedNestedFieldPath =
HoodieInternalRowUtils.getCachedPosList(structType, fieldName);
if (cachedNestedFieldPath.isDefined()) {
HoodieUnsafeRowUtils.NestedFieldPath nestedFieldPath = cachedNestedFieldPath.get();
- return HoodieUnsafeRowUtils.getNestedInternalRowValue(row, nestedFieldPath);
+ Object value = HoodieUnsafeRowUtils.getNestedInternalRowValue(row, nestedFieldPath);
+ if (!convertToJavaType) {
+ return value;
+ }
+ return sparkTypeToJavaType(value, nestedFieldPath.parts()[nestedFieldPath.parts().length - 1]._2.dataType());
Review Comment:
Could `HoodieUnsafeRowUtils.getNestedInternalRowValue(row, nestedFieldPath)` or a new method return both the value and the data type to avoid invoking `nestedFieldPath.parts()[nestedFieldPath.parts().length - 1]._2.dataType()`?
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3305274564
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2359581074
##########
hudi-common/src/main/java/org/apache/hudi/avro/AvroSchemaUtils.java:
##########
@@ -423,22 +428,24 @@ private static Schema pruneDataSchemaInternal(Schema dataSchema, Schema required
}
List<Schema.Field> newFields = new ArrayList<>();
for (Schema.Field requiredSchemaField : requiredSchema.getFields()) {
- Schema.Field dataSchemaField = dataSchema.getField(requiredSchemaField.name());
- if (dataSchemaField != null) {
- Schema.Field newField = new Schema.Field(
- dataSchemaField.name(),
- pruneDataSchema(dataSchemaField.schema(), requiredSchemaField.schema(), Collections.emptySet()),
- dataSchemaField.doc(),
- dataSchemaField.defaultVal()
- );
- newFields.add(newField);
- } else if (mandatoryFields.contains(requiredSchemaField.name())) {
+ if (mandatoryFields.contains(requiredSchemaField.name())) {
Review Comment:
Got it. This might be a bug around timestamp partition column.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3309166330
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3299833677
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3300206666
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3309306421
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3322280701
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3310433083
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3312573978
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3321306343
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2370847093
##########
hudi-common/src/main/java/org/apache/hudi/stats/ValueMetadata.java:
##########
@@ -0,0 +1,254 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.ParquetAdapter;
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.Pair;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.io.Serializable;
+
+import static org.apache.hudi.avro.AvroSchemaUtils.resolveNullableSchema;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE_ADDITIONAL_INFO;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE_ORDINAL;
+
+/**
+ * Holder for VaueType and additional info
+ * Used for wrapping and unwrapping col stat values
+ * as well as for type promotion
+ */
+public class ValueMetadata implements Serializable {
+
+ private static final ParquetAdapter PARQUET_ADAPTER = ParquetAdapter.getAdapter();
+
+ private final ValueType valueType;
+
+ protected ValueMetadata(ValueType valueType) {
+ this.valueType = valueType;
+ }
+
+ public ValueType getValueType() {
+ return valueType;
+ }
+
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ return HoodieValueTypeInfo.newBuilder()
+ .setTypeOrdinal(valueType.ordinal())
+ .setAdditionalInfo(getAdditionalInfo())
+ .build();
+ }
+
+ String getAdditionalInfo() {
+ return null;
+ }
+
+ public Comparable<?> standardizeJavaTypeAndPromote(Object val) {
+ return this.getValueType().standardizeJavaTypeAndPromote(val, this);
+ }
+
+ public Object wrapValue(Comparable<?> value) {
+ return this.getValueType().wrapValue(value, this);
+ }
+
+ public Comparable<?> unwrapValue(Object value) {
+ return this.getValueType().unwrapValue(value, this);
+ }
+
+ public void validate(Object minVal, Object maxVal) {
+ if (getValueType() == ValueType.V1) {
+ return;
+ }
+ this.getValueType().validate(minVal);
+ this.getValueType().validate(maxVal);
+ }
+
+ public boolean isV1() {
+ return this.getValueType() == ValueType.V1;
+ }
+
+ public static class V1EmptyMetadata extends ValueMetadata {
+ private static final V1EmptyMetadata V1_EMPTY_METADATA = new V1EmptyMetadata();
+ public static V1EmptyMetadata get() {
+ return V1_EMPTY_METADATA;
+ }
+
+ private V1EmptyMetadata() {
+ super(ValueType.V1);
+ }
+
+ @Override
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ // V1 should never be persisted to the MDT. It is only for in memory
+ return null;
+ }
+ }
+
+ public static final ValueMetadata NULL_METADATA = new ValueMetadata(ValueType.NULL);
+
+ interface DecimalValueMetadata {
+
+ int getPrecision();
+
+ int getScale();
+
+ static String encodeData(DecimalValueMetadata decimalValueMetadata) {
+ return String.format("%d,%d", decimalValueMetadata.getPrecision(), decimalValueMetadata.getScale());
+ }
+
+ static Pair<Integer, Integer> decodeData(String data) {
+ //TODO: decide if we want to store things in a better way
+ String[] splits = data.split(",");
+ return Pair.of(Integer.parseInt(splits[0]), Integer.parseInt(splits[1]));
+ }
+ }
+
+ static class DecimalMetadata extends ValueMetadata implements DecimalValueMetadata {
+
+ static DecimalMetadata create(String additionalInfo) {
+ if (additionalInfo == null) {
+ throw new IllegalArgumentException("additionalInfo cannot be null");
+ }
+ Pair<Integer, Integer> data = DecimalValueMetadata.decodeData(additionalInfo);
+ return new DecimalMetadata(data.getLeft(), data.getRight());
+ }
+
+ static DecimalMetadata create(LogicalTypes.Decimal decimal) {
+ return new DecimalMetadata(decimal.getPrecision(), decimal.getScale());
+ }
+
+ static DecimalMetadata create(PrimitiveType primitiveType) {
+ return new DecimalMetadata(PARQUET_ADAPTER.getPrecision(primitiveType), PARQUET_ADAPTER.getScale(primitiveType));
+ }
+
+ static DecimalMetadata create(int precision, int scale) {
+ return new DecimalMetadata(precision, scale);
+ }
+
+ private final int precision;
+ private final int scale;
+
+ private DecimalMetadata(int precision, int scale) {
+ super(ValueType.DECIMAL);
+ this.precision = precision;
+ this.scale = scale;
+ }
+
+ @Override
+ public int getPrecision() {
+ return precision;
+ }
+
+ @Override
+ public int getScale() {
+ return scale;
+ }
+
+ @Override
+ String getAdditionalInfo() {
+ return DecimalValueMetadata.encodeData(this);
+ }
+ }
+
+ public static ValueMetadata getEmptyValueMetadata(HoodieIndexVersion indexVersion) {
+ if (indexVersion.lowerThan(HoodieIndexVersion.V2)) {
+ return V1EmptyMetadata.get();
+ }
+ return NULL_METADATA;
+ }
+
+ public static ValueMetadata getValueMetadata(HoodieValueTypeInfo valueTypeInfo) {
+ // valueTypeInfo will always be null when version is v1
+ if (valueTypeInfo == null) {
+ return V1EmptyMetadata.get();
+ }
+
+ ValueType valueType = ValueType.fromOrdinal(valueTypeInfo.getTypeOrdinal());
+ if (valueType == ValueType.V1) {
+ return V1EmptyMetadata.get();
+ } else if (valueType == ValueType.DECIMAL) {
+ return DecimalMetadata.create(valueTypeInfo.getAdditionalInfo());
+ } else {
+ return new ValueMetadata(valueType);
+ }
+ }
+
+ public static ValueMetadata getValueMetadata(GenericRecord columnStatsRecord) {
+ if (columnStatsRecord == null) {
+ // TODO: Should we return V1EmptyMetadata here?
+ return NULL_METADATA;
Review Comment:
I decided to throw illegal state. Currently, the only caller is `org.apache.hudi.metadata.MetadataPartitionType#constructColumnStatsMetadataPayload` and it has handling for null so it should never be null here
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3185156271
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* 755ea1e08c3b8ab35bd499c3412fabae61612805 Azure: [FAILURE](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=7784)
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3185576161
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## CI report:
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "the-other-tim-brown (via GitHub)" <gi...@apache.org>.
the-other-tim-brown commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2283754652
##########
hudi-common/src/main/java/org/apache/hudi/avro/ValueMetadata.java:
##########
@@ -0,0 +1,218 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.avro;
Review Comment:
If this class is specific to col-stats, we can consider making a sub-package `stats` instead of `avro`
##########
hudi-client/hudi-spark-client/src/main/scala/org/apache/hudi/BaseSparkInternalRecordContext.java:
##########
@@ -67,6 +73,30 @@ public static Object getFieldValueFromInternalRow(InternalRow row, Schema record
}
}
+ public static Object getFieldValueFromInternalRowAsJava(InternalRow row, Schema recordSchema, String fieldName) {
+ Object value = getFieldValueFromInternalRow(row, recordSchema, fieldName);
+ return sparkTypeToJavaType(value);
+ }
+
+ public static Object sparkTypeToJavaType(Object value) {
Review Comment:
Just want to confirm, do timestamps get handled as `long` in spark?
##########
hudi-common/src/main/avro/HoodieMetadata.avsc:
##########
@@ -417,6 +417,35 @@
"name": "isTightBound",
"type": "boolean",
"default": false
+ },
+ {
+ "doc": "Value type information containing enum ordinal and optional additional information",
+ "name": "valueType",
+ "type": [
+ "null",
+ {
+ "type": "record",
+ "name": "HoodieValueTypeInfo",
+ "namespace": "org.apache.hudi.avro.model",
+ "fields": [
+ {
+ "doc": "Enum type ordinal representing the value type",
+ "name": "typeOrdinal",
+ "type": "int"
Review Comment:
Do we want to define the enum here in the schema or how doe we know what this corresponds to and ensure it is compatible between releases?
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3197864320
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2299053300
##########
hudi-common/src/main/avro/HoodieMetadata.avsc:
##########
@@ -417,6 +417,35 @@
"name": "isTightBound",
"type": "boolean",
"default": false
+ },
+ {
+ "doc": "Value type information containing enum ordinal and optional additional information",
Review Comment:
Given that the min and max values stored in column stats are changed and versioned, could you check how XTable can use the same utils or new functionality for reading column stats from Hudi in a backward compatible way?
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3267814958
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3271290790
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3271449060
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3276327975
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3282931117
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3184966740
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## CI report:
* d211a2ca8764ae4b631b05c4af1550fb9e75fb0f Azure: [FAILURE](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=7748)
* 755ea1e08c3b8ab35bd499c3412fabae61612805 Azure: [PENDING](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=7784)
* 7089c121f35cf1e233e6c9028efd1e36900b83df UNKNOWN
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3185380148
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3267450949
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## CI report:
* fc598f6fa98284db6d6d61bfd85e80771397206a Azure: [FAILURE](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=8385)
* 9a59641d2daa2edf1c1907129b34861273c9738a UNKNOWN
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3271482119
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* d655091e2aed36628565f8c9dbcd5773e6c9334c UNKNOWN
* e8d5675097d942e3c860ae550a3c88202bbe10eb Azure: [FAILURE](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=8419)
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3275978228
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3282657416
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "the-other-tim-brown (via GitHub)" <gi...@apache.org>.
the-other-tim-brown commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2286711258
##########
hudi-common/src/main/java/org/apache/hudi/avro/ValueType.java:
##########
@@ -0,0 +1,637 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.avro;
+
+import org.apache.hudi.avro.model.ArrayWrapper;
+import org.apache.hudi.common.util.DateTimeUtils;
+import org.apache.hudi.common.util.collection.ArrayComparable;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.avro.util.Utf8;
+import org.apache.parquet.io.api.Binary;
+import org.apache.parquet.schema.LogicalTypeTokenParser;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.math.BigDecimal;
+import java.math.BigInteger;
+import java.math.MathContext;
+import java.math.RoundingMode;
+import java.nio.ByteBuffer;
+import java.sql.Date;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.time.LocalDateTime;
+import java.time.LocalTime;
+import java.time.ZoneOffset;
+import java.util.Objects;
+import java.util.UUID;
+import java.util.function.BiFunction;
+import java.util.function.Function;
+
+import static org.apache.hudi.avro.HoodieAvroUtils.convertBytesToBigDecimal;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToMicros;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToNanos;
+import static org.apache.hudi.common.util.DateTimeUtils.microsToInstant;
+import static org.apache.hudi.common.util.DateTimeUtils.nanosToInstant;
+import static org.apache.hudi.common.util.StringUtils.getUTF8Bytes;
+
+public enum ValueType {
+ V1(HoodieAvroWrapperUtils.PrimitiveWrapperType.V1.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.V1,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ NULL(HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ BOOLEAN(HoodieAvroWrapperUtils.PrimitiveWrapperType.BOOLEAN, ValueType::castToBoolean),
+ INT(HoodieAvroWrapperUtils.PrimitiveWrapperType.INT, ValueType::castToInteger),
+ LONG(HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG, ValueType::castToLong),
+ FLOAT(HoodieAvroWrapperUtils.PrimitiveWrapperType.FLOAT, ValueType::castToFloat),
+ DOUBLE(HoodieAvroWrapperUtils.PrimitiveWrapperType.DOUBLE, ValueType::castToDouble),
+ STRING(HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING, ValueType::castToString),
+ BYTES(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToBytes),
+ FIXED(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToFixed),
+ DECIMAL(BigDecimal.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES,
+ ValueType::castToDecimal, ValueType::toDecimal, ValueType::fromDecimal),
+ UUID(UUID.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING,
+ ValueType::castToUUID, ValueType::toUUID, ValueType::fromUUID),
+ DATE(Date.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToDate, ValueType::toDate, ValueType::fromDate),
+ TIME_MILLIS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToTimeMillis, ValueType::toTimeMillis, ValueType::fromTimeMillis),
+ TIME_MICROS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimeMicros, ValueType::toTimeMicros, ValueType::fromTimeMicros),
+ TIMESTAMP_MILLIS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMillis, ValueType::toTimestampMillis, ValueType::fromTimestampMillis),
+ TIMESTAMP_MICROS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMicros, ValueType::toTimestampMicros, ValueType::fromTimestampMicros),
+ TIMESTAMP_NANOS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampNanos, ValueType::toTimestampNanos, ValueType::fromTimestampNanos),
+ LOCAL_TIMESTAMP_MILLIS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMillis, ValueType::toLocalTimestampMillis, ValueType::fromLocalTimestampMillis),
+ LOCAL_TIMESTAMP_MICROS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMicros, ValueType::toLocalTimestampMicros, ValueType::fromLocalTimestampMicros),
+ LOCAL_TIMESTAMP_NANOS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampNanos, ValueType::toLocalTimestampNanos, ValueType::fromLocalTimestampNanos);
+
+ private final Class<?> internalType;
+ private final HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType;
+ private final BiFunction<Object, ValueMetadata, Comparable<?>> standardize;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toPrimitive;
Review Comment:
Can you add some java doc explaining the differences between these methods?
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3194693935
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3194668824
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3197682322
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3197718573
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3179923800
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3259511809
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3282804859
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3310259368
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2350125129
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/utils/SparkMetadataWriterUtils.java:
##########
@@ -206,6 +212,16 @@ public static ExpressionIndexComputationMetadata getExpressionIndexRecordsUsingC
: new ExpressionIndexComputationMetadata(colStatRecords);
}
+ private static SparkValueMetadata getValueMetadataFromColumnRangeDataset(Dataset<Row> dataset, HoodieIndexVersion indexVersion) {
Review Comment:
nit: pass in `StructType` schema instead of `Dataset<Row>`?
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2352914972
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/io/storage/row/HoodieRowParquetWriteSupport.java:
##########
@@ -451,7 +451,7 @@ private Type convertField(Schema avroFieldSchema, StructField structField, Type.
.as(LogicalTypeAnnotation.timestampType(false, LogicalTypeAnnotation.TimeUnit.MICROS)).named(structField.name());
} else if (logicalType.getName().equals(LogicalTypes.localTimestampMillis().getName())) {
return Types.primitive(INT64, repetition)
- .as(LogicalTypeAnnotation.timestampType(false, LogicalTypeAnnotation.TimeUnit.MICROS)).named(structField.name());
+ .as(LogicalTypeAnnotation.timestampType(false, LogicalTypeAnnotation.TimeUnit.MILLIS)).named(structField.name());
Review Comment:
Yes, Tim's test was failing. He fixed the writer, but was validating with the spark reader, which also has issues that I fixed. So that's why the test is passing on master
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2354123452
##########
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/spark/sql/hudi/dml/others/TestMergeIntoTable.scala:
##########
@@ -21,7 +21,7 @@ package org.apache.spark.sql.hudi.dml.others
import org.apache.hudi.{DataSourceReadOptions, DataSourceWriteOptions, ScalaAssertionSupport}
import org.apache.hudi.DataSourceWriteOptions.SPARK_SQL_OPTIMIZED_WRITES
-import org.apache.hudi.common.config.{HoodieReaderConfig, HoodieStorageConfig}
+import org.apache.hudi.common.config.{HoodieMetadataConfig, HoodieReaderConfig, HoodieStorageConfig}
Review Comment:
no
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2353725863
##########
hudi-common/src/main/java/org/apache/hudi/common/util/FileFormatUtils.java:
##########
@@ -64,10 +66,24 @@ public abstract class FileFormatUtils {
* @param fileColumnRanges List of column range statistics for each file in a partition
*/
public static <T extends Comparable<T>> HoodieColumnRangeMetadata<T> getColumnRangeInPartition(String relativePartitionPath,
+ String columnName,
@Nonnull List<HoodieColumnRangeMetadata<T>> fileColumnRanges,
- Map<String, Schema> colsToIndexSchemaMap) {
+ Map<String, Schema> colsToIndexSchemaMap,
+ HoodieIndexVersion indexVersion) {
ValidationUtils.checkArgument(!fileColumnRanges.isEmpty(), "fileColumnRanges should not be empty.");
+ if (indexVersion.greaterThanOrEquals(HoodieIndexVersion.V2)) {
+ ValueMetadata valueMetadata = ValueMetadata.getValueMetadata(colsToIndexSchemaMap.get(columnName), indexVersion);
+ return fileColumnRanges.stream()
+ .map(e -> {
+ T minValue = (T) valueMetadata.standardizeJavaTypeAndPromote(e.getMinValue());
+ T maxValue = (T) valueMetadata.standardizeJavaTypeAndPromote(e.getMaxValue());
+ return HoodieColumnRangeMetadata.create(
+ relativePartitionPath, e.getColumnName(), minValue, maxValue, e.getNullCount(), e.getValueCount(), e.getTotalSize(),
+ e.getTotalUncompressedSize(), valueMetadata);
+ }).reduce(HoodieColumnRangeMetadata::merge).orElseThrow(() -> new HoodieException("MergingColumnRanges failed."));
+ }
+ // we are reducing using merge so IDK why we think there are multiple cols that need to go through schema evolution
Review Comment:
My point was that "colToIndex" should be the same for every range in fileColumnRanges. And that the code acknowledges that fact by merging all of them together right after this. So I was saying that it's weird that this code acts like they could be different and uses a map schemaSeenForColsToIndex when there will at most be 1 key. In fact in HoodieColumnRangeMetadata.merge we even validate that the col names are the same
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2359417068
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/utils/SparkValueMetadata.java:
##########
@@ -0,0 +1,230 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.client.utils;
+
+import org.apache.hudi.SparkAdapterSupport$;
+import org.apache.hudi.avro.ValueMetadata;
+import org.apache.hudi.avro.ValueType;
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.ArrayComparable;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.spark.sql.types.ArrayType;
+import org.apache.spark.sql.types.BinaryType;
+import org.apache.spark.sql.types.BooleanType;
+import org.apache.spark.sql.types.ByteType;
+import org.apache.spark.sql.types.CharType;
+import org.apache.spark.sql.types.DataType;
+import org.apache.spark.sql.types.DateType;
+import org.apache.spark.sql.types.Decimal;
+import org.apache.spark.sql.types.DecimalType;
+import org.apache.spark.sql.types.DoubleType;
+import org.apache.spark.sql.types.FloatType;
+import org.apache.spark.sql.types.IntegerType;
+import org.apache.spark.sql.types.LongType;
+import org.apache.spark.sql.types.NullType;
+import org.apache.spark.sql.types.ShortType;
+import org.apache.spark.sql.types.StringType;
+import org.apache.spark.sql.types.TimestampType;
+import org.apache.spark.sql.types.VarcharType;
+
+import java.sql.Date;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.util.Arrays;
+
+public class SparkValueMetadata extends ValueMetadata {
+
+ private final DataType dataType;
+
+ protected SparkValueMetadata(ValueType valueType, DataType dataType) {
+ super(valueType);
+ this.dataType = dataType;
+ }
+
+ public Comparable convertSparkToJava(Object value) {
+ return convertSparkToJava(value, true);
+ }
+
+ public static SparkValueMetadata getValueMetadata(DataType dataType, HoodieIndexVersion indexVersion) {
+ if (indexVersion.lowerThan(HoodieIndexVersion.V2)) {
+ return SparkV1EmptyMetadata.get();
+ }
+ if (dataType == null) {
+ return new SparkValueMetadata(ValueType.NULL, null);
+ }
+ ValueType valueType = fromDataType(dataType);
+ if (valueType == ValueType.DECIMAL) {
+ return new SparkDecimalMetadata((DecimalType) dataType);
+ } else {
+ return new SparkValueMetadata(valueType, dataType);
+ }
+ }
+
+ private static ValueType fromDataType(DataType dataType) {
+ return fromDataType(dataType, true);
+ }
+
+ private static ValueType fromDataType(DataType dataType, boolean root) {
+ if (dataType instanceof NullType) {
+ return ValueType.NULL;
+ } else if (dataType instanceof BooleanType) {
+ return ValueType.BOOLEAN;
+ } else if (dataType instanceof IntegerType || dataType instanceof ShortType || dataType instanceof ByteType) {
+ return ValueType.INT;
+ } else if (dataType instanceof LongType) {
+ return ValueType.LONG;
+ } else if (dataType instanceof FloatType) {
+ return ValueType.FLOAT;
+ } else if (dataType instanceof DoubleType) {
+ return ValueType.DOUBLE;
+ } else if (dataType instanceof StringType || dataType instanceof CharType || dataType instanceof VarcharType) {
+ return ValueType.STRING;
+ } else if (dataType instanceof TimestampType) {
+ return ValueType.TIMESTAMP_MICROS;
+ } else if (dataType instanceof DecimalType) {
+ return ValueType.DECIMAL;
+ } else if (dataType instanceof DateType) {
+ return ValueType.DATE;
+ } else if (dataType instanceof BinaryType) {
+ return ValueType.BYTES;
+ } else if (dataType instanceof ArrayType) {
+ if (root) {
+ return fromDataType(((ArrayType) dataType).elementType(), false);
+ } else {
+ throw new IllegalArgumentException("Array of Array is not supported");
+ }
+ } else if (SparkAdapterSupport$.MODULE$.sparkAdapter().isTimestampNTZType(dataType)) {
+ return ValueType.LOCAL_TIMESTAMP_MICROS;
+ } else {
+ throw new IllegalArgumentException("Unsupported data type: " + dataType);
+ }
+ }
+
+ private static class SparkV1EmptyMetadata extends SparkValueMetadata {
+ private static final SparkV1EmptyMetadata V_1_EMPTY_METADATA = new SparkV1EmptyMetadata();
+ public static SparkV1EmptyMetadata get() {
+ return V_1_EMPTY_METADATA;
+ }
+
+ private SparkV1EmptyMetadata() {
+ super(ValueType.V1, null);
+ }
+
+ @Override
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ return null;
+ }
+ }
+
+ private static class SparkDecimalMetadata extends SparkValueMetadata implements ValueMetadata.DecimalValueMetadata {
+
+ private final int precision;
+ private final int scale;
+
+ protected SparkDecimalMetadata(DecimalType decimalType) {
+ super(ValueType.DECIMAL, decimalType);
+ this.precision = decimalType.precision();
+ this.scale = decimalType.scale();
+ }
+
+ @Override
+ public int getPrecision() {
+ return precision;
+ }
+
+ @Override
+ public int getScale() {
+ return scale;
+ }
+
+ @Override
+ public String getAdditionalInfo() {
+ return DecimalValueMetadata.encodeData(this);
+ }
+ }
+
+ private Comparable convertSparkToJava(Object value, boolean rootLevel) {
+ if (value == null) {
+ return null;
+ }
+
+ if (value instanceof org.apache.spark.sql.catalyst.util.ArrayData) {
+ if (rootLevel) {
+ return new ArrayComparable(Arrays.stream(((org.apache.spark.sql.catalyst.util.ArrayData) value)
+ .toObjectArray(((org.apache.spark.sql.types.ArrayType) dataType).elementType()))
+ .map(v -> convertSparkToJava(v, false)).toArray(Comparable[]::new));
+ } else {
+ throw new IllegalArgumentException("array of arrays not supported");
+ }
+ }
+
+ switch (getValueType()) {
+ case V1:
+ return (Comparable) value;
+ case NULL:
+ return null;
+ case BOOLEAN:
+ return (Boolean) value;
+ case INT:
+ return (Integer) value;
+ case LONG:
+ return (Long) value;
+ case FLOAT:
+ return (Float) value;
+ case DOUBLE:
+ return (Double) value;
+ case STRING:
+ return (String) value;
+ case BYTES:
+ return ValueType.castToBytes(value);
+ case DECIMAL:
+ return ((Decimal) value).toJavaBigDecimal();
+ case DATE:
+ return ValueType.castToDate(value, this);
+ case TIMESTAMP_MICROS:
+ return ValueType.castToTimestampMicros(value, this);
+ case LOCAL_TIMESTAMP_MICROS:
+ return ValueType.castToLocalTimestampMicros(value, this);
+ case FIXED:
+ case UUID:
+ case TIME_MILLIS:
+ case TIME_MICROS:
+ case TIMESTAMP_MILLIS:
+ case TIMESTAMP_NANOS:
+ case LOCAL_TIMESTAMP_MILLIS:
+ case LOCAL_TIMESTAMP_NANOS:
+ default:
+ throw new IllegalStateException("Spark value metadata for expression index should never be " + getValueType().name());
+ }
+ }
+
+ public static Object convertJavaTypeToSparkType(Comparable<?> javaVal, boolean useJava8api) {
+ if (!useJava8api) {
+ if (javaVal instanceof Instant) {
+ return Timestamp.from((Instant) javaVal);
+ } else if (javaVal instanceof LocalDate) {
+ return Date.valueOf((LocalDate) javaVal);
+ }
+ }
+ return javaVal;
Review Comment:
Got it. As long as the default config setting works it's OK.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2359456617
##########
hudi-common/src/main/java/org/apache/hudi/avro/processors/Parser.java:
##########
@@ -46,21 +48,19 @@ public Pair<Boolean, Object> handleStringValue(String value) {
public static class DateParser extends Parser {
- private static final long MILLI_SECONDS_PER_DAY = 86400000;
-
@Override
public Pair<Boolean, Object> handleNumberValue(Number value) {
- return Pair.of(true, new java.sql.Date(value.intValue() * MILLI_SECONDS_PER_DAY));
+ return Pair.of(true, LocalDate.ofEpochDay(value.intValue()));
Review Comment:
Got it, thanks for the explanation!
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2359713783
##########
hudi-spark-datasource/hudi-spark/src/test/java/org/apache/hudi/functional/TestSparkSortAndSizeClustering.java:
##########
@@ -182,9 +183,9 @@ private void validateDateAndTimestampFields(List<Row> rows, long ts) {
assertTrue(actualDate.compareTo(startDate) > 0 && actualDate.compareTo(endDate) < 0);
}
if (!row.isNullAt(tsLocalMillisFieldIndex)) {
- assertEquals(ts, row.get(tsLocalMillisFieldIndex));
+ assertEquals(ValueType.toLocalTimestampMillis(ts, null), row.get(tsLocalMillisFieldIndex));
}
- assertEquals(ts * 1000L, row.get(tsLocalMicrosFieldIndex));
+ assertEquals(ValueType.toLocalTimestampMillis(ts, null), row.get(tsLocalMicrosFieldIndex));
Review Comment:
I see. Let's change that for clarity
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3308029391
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3293523704
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2355892453
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/utils/SparkValueMetadata.java:
##########
@@ -0,0 +1,230 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.client.utils;
+
+import org.apache.hudi.SparkAdapterSupport$;
+import org.apache.hudi.avro.ValueMetadata;
+import org.apache.hudi.avro.ValueType;
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.ArrayComparable;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.spark.sql.types.ArrayType;
+import org.apache.spark.sql.types.BinaryType;
+import org.apache.spark.sql.types.BooleanType;
+import org.apache.spark.sql.types.ByteType;
+import org.apache.spark.sql.types.CharType;
+import org.apache.spark.sql.types.DataType;
+import org.apache.spark.sql.types.DateType;
+import org.apache.spark.sql.types.Decimal;
+import org.apache.spark.sql.types.DecimalType;
+import org.apache.spark.sql.types.DoubleType;
+import org.apache.spark.sql.types.FloatType;
+import org.apache.spark.sql.types.IntegerType;
+import org.apache.spark.sql.types.LongType;
+import org.apache.spark.sql.types.NullType;
+import org.apache.spark.sql.types.ShortType;
+import org.apache.spark.sql.types.StringType;
+import org.apache.spark.sql.types.TimestampType;
+import org.apache.spark.sql.types.VarcharType;
+
+import java.sql.Date;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.util.Arrays;
+
+public class SparkValueMetadata extends ValueMetadata {
+
+ private final DataType dataType;
+
+ protected SparkValueMetadata(ValueType valueType, DataType dataType) {
+ super(valueType);
+ this.dataType = dataType;
+ }
+
+ public Comparable convertSparkToJava(Object value) {
+ return convertSparkToJava(value, true);
+ }
+
+ public static SparkValueMetadata getValueMetadata(DataType dataType, HoodieIndexVersion indexVersion) {
+ if (indexVersion.lowerThan(HoodieIndexVersion.V2)) {
+ return SparkV1EmptyMetadata.get();
+ }
+ if (dataType == null) {
+ return new SparkValueMetadata(ValueType.NULL, null);
+ }
+ ValueType valueType = fromDataType(dataType);
+ if (valueType == ValueType.DECIMAL) {
+ return new SparkDecimalMetadata((DecimalType) dataType);
+ } else {
+ return new SparkValueMetadata(valueType, dataType);
+ }
+ }
+
+ private static ValueType fromDataType(DataType dataType) {
+ return fromDataType(dataType, true);
+ }
+
+ private static ValueType fromDataType(DataType dataType, boolean root) {
+ if (dataType instanceof NullType) {
+ return ValueType.NULL;
+ } else if (dataType instanceof BooleanType) {
+ return ValueType.BOOLEAN;
+ } else if (dataType instanceof IntegerType || dataType instanceof ShortType || dataType instanceof ByteType) {
+ return ValueType.INT;
+ } else if (dataType instanceof LongType) {
+ return ValueType.LONG;
+ } else if (dataType instanceof FloatType) {
+ return ValueType.FLOAT;
+ } else if (dataType instanceof DoubleType) {
+ return ValueType.DOUBLE;
+ } else if (dataType instanceof StringType || dataType instanceof CharType || dataType instanceof VarcharType) {
+ return ValueType.STRING;
+ } else if (dataType instanceof TimestampType) {
+ return ValueType.TIMESTAMP_MICROS;
+ } else if (dataType instanceof DecimalType) {
+ return ValueType.DECIMAL;
+ } else if (dataType instanceof DateType) {
+ return ValueType.DATE;
+ } else if (dataType instanceof BinaryType) {
+ return ValueType.BYTES;
+ } else if (dataType instanceof ArrayType) {
+ if (root) {
+ return fromDataType(((ArrayType) dataType).elementType(), false);
+ } else {
+ throw new IllegalArgumentException("Array of Array is not supported");
+ }
+ } else if (SparkAdapterSupport$.MODULE$.sparkAdapter().isTimestampNTZType(dataType)) {
+ return ValueType.LOCAL_TIMESTAMP_MICROS;
+ } else {
+ throw new IllegalArgumentException("Unsupported data type: " + dataType);
+ }
+ }
+
+ private static class SparkV1EmptyMetadata extends SparkValueMetadata {
+ private static final SparkV1EmptyMetadata V_1_EMPTY_METADATA = new SparkV1EmptyMetadata();
Review Comment:
no more spark value metadata
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/utils/SparkValueMetadata.java:
##########
@@ -0,0 +1,230 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.client.utils;
+
+import org.apache.hudi.SparkAdapterSupport$;
+import org.apache.hudi.avro.ValueMetadata;
+import org.apache.hudi.avro.ValueType;
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.ArrayComparable;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.spark.sql.types.ArrayType;
+import org.apache.spark.sql.types.BinaryType;
+import org.apache.spark.sql.types.BooleanType;
+import org.apache.spark.sql.types.ByteType;
+import org.apache.spark.sql.types.CharType;
+import org.apache.spark.sql.types.DataType;
+import org.apache.spark.sql.types.DateType;
+import org.apache.spark.sql.types.Decimal;
+import org.apache.spark.sql.types.DecimalType;
+import org.apache.spark.sql.types.DoubleType;
+import org.apache.spark.sql.types.FloatType;
+import org.apache.spark.sql.types.IntegerType;
+import org.apache.spark.sql.types.LongType;
+import org.apache.spark.sql.types.NullType;
+import org.apache.spark.sql.types.ShortType;
+import org.apache.spark.sql.types.StringType;
+import org.apache.spark.sql.types.TimestampType;
+import org.apache.spark.sql.types.VarcharType;
+
+import java.sql.Date;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.util.Arrays;
+
+public class SparkValueMetadata extends ValueMetadata {
+
+ private final DataType dataType;
+
+ protected SparkValueMetadata(ValueType valueType, DataType dataType) {
+ super(valueType);
+ this.dataType = dataType;
+ }
+
+ public Comparable convertSparkToJava(Object value) {
+ return convertSparkToJava(value, true);
+ }
+
+ public static SparkValueMetadata getValueMetadata(DataType dataType, HoodieIndexVersion indexVersion) {
+ if (indexVersion.lowerThan(HoodieIndexVersion.V2)) {
+ return SparkV1EmptyMetadata.get();
+ }
+ if (dataType == null) {
+ return new SparkValueMetadata(ValueType.NULL, null);
+ }
+ ValueType valueType = fromDataType(dataType);
+ if (valueType == ValueType.DECIMAL) {
+ return new SparkDecimalMetadata((DecimalType) dataType);
+ } else {
+ return new SparkValueMetadata(valueType, dataType);
+ }
+ }
+
+ private static ValueType fromDataType(DataType dataType) {
+ return fromDataType(dataType, true);
+ }
+
+ private static ValueType fromDataType(DataType dataType, boolean root) {
+ if (dataType instanceof NullType) {
+ return ValueType.NULL;
+ } else if (dataType instanceof BooleanType) {
+ return ValueType.BOOLEAN;
+ } else if (dataType instanceof IntegerType || dataType instanceof ShortType || dataType instanceof ByteType) {
+ return ValueType.INT;
+ } else if (dataType instanceof LongType) {
+ return ValueType.LONG;
+ } else if (dataType instanceof FloatType) {
+ return ValueType.FLOAT;
+ } else if (dataType instanceof DoubleType) {
+ return ValueType.DOUBLE;
+ } else if (dataType instanceof StringType || dataType instanceof CharType || dataType instanceof VarcharType) {
+ return ValueType.STRING;
+ } else if (dataType instanceof TimestampType) {
+ return ValueType.TIMESTAMP_MICROS;
+ } else if (dataType instanceof DecimalType) {
+ return ValueType.DECIMAL;
+ } else if (dataType instanceof DateType) {
+ return ValueType.DATE;
+ } else if (dataType instanceof BinaryType) {
+ return ValueType.BYTES;
+ } else if (dataType instanceof ArrayType) {
+ if (root) {
+ return fromDataType(((ArrayType) dataType).elementType(), false);
+ } else {
+ throw new IllegalArgumentException("Array of Array is not supported");
+ }
+ } else if (SparkAdapterSupport$.MODULE$.sparkAdapter().isTimestampNTZType(dataType)) {
+ return ValueType.LOCAL_TIMESTAMP_MICROS;
+ } else {
+ throw new IllegalArgumentException("Unsupported data type: " + dataType);
+ }
+ }
+
+ private static class SparkV1EmptyMetadata extends SparkValueMetadata {
Review Comment:
removed
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2357282079
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/utils/SparkValueMetadata.java:
##########
@@ -0,0 +1,229 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.client.utils;
+
+import org.apache.hudi.avro.ValueMetadata;
+import org.apache.hudi.avro.ValueType;
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.ArrayComparable;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.spark.sql.types.ArrayType;
+import org.apache.spark.sql.types.BinaryType;
+import org.apache.spark.sql.types.BooleanType;
+import org.apache.spark.sql.types.ByteType;
+import org.apache.spark.sql.types.CharType;
+import org.apache.spark.sql.types.DataType;
+import org.apache.spark.sql.types.DateType;
+import org.apache.spark.sql.types.Decimal;
+import org.apache.spark.sql.types.DecimalType;
+import org.apache.spark.sql.types.DoubleType;
+import org.apache.spark.sql.types.FloatType;
+import org.apache.spark.sql.types.IntegerType;
+import org.apache.spark.sql.types.LongType;
+import org.apache.spark.sql.types.NullType;
+import org.apache.spark.sql.types.ShortType;
+import org.apache.spark.sql.types.StringType;
+import org.apache.spark.sql.types.TimestampType;
+import org.apache.spark.sql.types.VarcharType;
+
+import java.sql.Date;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.util.Arrays;
+
+public class SparkValueMetadata extends ValueMetadata {
+
+ private final DataType dataType;
+
+ protected SparkValueMetadata(ValueType valueType, DataType dataType) {
+ super(valueType);
+ this.dataType = dataType;
+ }
+
+ public Comparable convertSparkToJava(Object value) {
+ return convertSparkToJava(value, true);
+ }
+
+ public static SparkValueMetadata getValueMetadata(DataType dataType, HoodieIndexVersion indexVersion) {
+ if (indexVersion.lowerThan(HoodieIndexVersion.V2)) {
+ return SparkV1EmptyMetadata.get();
+ }
+ if (dataType == null) {
+ return new SparkValueMetadata(ValueType.NULL, null);
+ }
+ ValueType valueType = fromDataType(dataType);
+ if (valueType == ValueType.DECIMAL) {
+ return new SparkDecimalMetadata((DecimalType) dataType);
+ } else {
+ return new SparkValueMetadata(valueType, dataType);
+ }
+ }
+
+ private static ValueType fromDataType(DataType dataType) {
+ return fromDataType(dataType, true);
+ }
+
+ private static ValueType fromDataType(DataType dataType, boolean root) {
+ if (dataType instanceof NullType) {
+ return ValueType.NULL;
+ } else if (dataType instanceof BooleanType) {
+ return ValueType.BOOLEAN;
+ } else if (dataType instanceof IntegerType || dataType instanceof ShortType || dataType instanceof ByteType) {
+ return ValueType.INT;
+ } else if (dataType instanceof LongType) {
+ return ValueType.LONG;
+ } else if (dataType instanceof FloatType) {
+ return ValueType.FLOAT;
+ } else if (dataType instanceof DoubleType) {
+ return ValueType.DOUBLE;
+ } else if (dataType instanceof StringType || dataType instanceof CharType || dataType instanceof VarcharType) {
+ return ValueType.STRING;
+ } else if (dataType instanceof TimestampType) {
+ return ValueType.TIMESTAMP_MICROS;
+ } else if (dataType instanceof DecimalType) {
+ return ValueType.DECIMAL;
+ } else if (dataType instanceof DateType) {
+ return ValueType.DATE;
+ } else if (dataType instanceof BinaryType) {
+ return ValueType.BYTES;
+ } else if (dataType instanceof ArrayType) {
+ if (root) {
+ return fromDataType(((ArrayType) dataType).elementType(), false);
+ } else {
+ throw new IllegalArgumentException("Array of Array is not supported");
+ }
+ } else if (dataType.getClass().getName().contains("TimestampNTZType")) {
+ return ValueType.LOCAL_TIMESTAMP_MICROS;
+ } else {
+ throw new IllegalArgumentException("Unsupported data type: " + dataType);
+ }
+ }
+
+ private static class SparkV1EmptyMetadata extends SparkValueMetadata {
+ private static final SparkV1EmptyMetadata V_1_EMPTY_METADATA = new SparkV1EmptyMetadata();
+ public static SparkV1EmptyMetadata get() {
+ return V_1_EMPTY_METADATA;
+ }
+
+ private SparkV1EmptyMetadata() {
+ super(ValueType.V1, null);
+ }
+
+ @Override
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ return null;
+ }
+ }
+
+ private static class SparkDecimalMetadata extends SparkValueMetadata implements ValueMetadata.DecimalValueMetadata {
+
+ private final int precision;
+ private final int scale;
+
+ protected SparkDecimalMetadata(DecimalType decimalType) {
+ super(ValueType.DECIMAL, decimalType);
+ this.precision = decimalType.precision();
+ this.scale = decimalType.scale();
+ }
+
+ @Override
+ public int getPrecision() {
+ return precision;
+ }
+
+ @Override
+ public int getScale() {
+ return scale;
+ }
+
+ @Override
+ public String getAdditionalInfo() {
+ return DecimalValueMetadata.encodeData(this);
+ }
+ }
Review Comment:
removed this class
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2301104401
##########
hudi-common/src/main/avro/HoodieMetadata.avsc:
##########
@@ -417,6 +417,35 @@
"name": "isTightBound",
"type": "boolean",
"default": false
+ },
+ {
+ "doc": "Value type information containing enum ordinal and optional additional information",
Review Comment:
ValueMetadata has several static methods `getValueMetadata` that can be used on avro schema, avro parquet type, or `HoodieValueTypeInfo` contained in a HoodieMetadata col stats record.
https://github.com/apache/incubator-xtable/blob/9f989bf1988bf9ce29f66bd2a9fe04bb4db73c6a/xtable-api/src/main/java/org/apache/xtable/model/stat/Range.java#L60
The docs here say that timestamps are using some internal type. So seems like some conversion will be necessary in xtable.
And the utils here need to be updated:
https://github.com/apache/incubator-xtable/blob/main/xtable-core/src/main/java/org/apache/xtable/hudi/HudiFileStatsExtractor.java
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3322182717
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Re: [PR] feat(metadata): Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua merged PR #13711:
URL: https://github.com/apache/hudi/pull/13711
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2370735519
##########
hudi-hadoop-common/src/main/java/org/apache/parquet/avro/AvroSchemaConverterWithNTZ.java:
##########
@@ -0,0 +1,598 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.parquet.avro;
+
+import org.apache.avro.LogicalType;
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.parquet.schema.ConversionPatterns;
+import org.apache.parquet.schema.GroupType;
+import org.apache.parquet.schema.LogicalTypeAnnotation;
+import org.apache.parquet.schema.LogicalTypeAnnotation.UUIDLogicalTypeAnnotation;
+import org.apache.parquet.schema.MessageType;
+import org.apache.parquet.schema.PrimitiveType;
+import org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName;
+import org.apache.parquet.schema.Type;
+import org.apache.parquet.schema.Types;
+
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.List;
+import java.util.Map;
+import java.util.Set;
+
+import static org.apache.avro.JsonProperties.NULL_VALUE;
+import static org.apache.parquet.avro.AvroReadSupport.READ_INT96_AS_FIXED;
+import static org.apache.parquet.avro.AvroReadSupport.READ_INT96_AS_FIXED_DEFAULT;
+import static org.apache.parquet.avro.AvroWriteSupport.WRITE_OLD_LIST_STRUCTURE;
+import static org.apache.parquet.avro.AvroWriteSupport.WRITE_OLD_LIST_STRUCTURE_DEFAULT;
+import static org.apache.parquet.avro.AvroWriteSupport.WRITE_PARQUET_UUID;
+import static org.apache.parquet.avro.AvroWriteSupport.WRITE_PARQUET_UUID_DEFAULT;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.TimeUnit.MICROS;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.TimeUnit.MILLIS;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.dateType;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.decimalType;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.enumType;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.stringType;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.timeType;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.timestampType;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.uuidType;
+import static org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.BINARY;
+import static org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.BOOLEAN;
+import static org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.DOUBLE;
+import static org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.FIXED_LEN_BYTE_ARRAY;
+import static org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.FLOAT;
+import static org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.INT32;
+import static org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.INT64;
+import static org.apache.parquet.schema.Type.Repetition.REPEATED;
+
+/**
+ * <p>
+ * Converts an Avro schema into a Parquet schema, or vice versa. See package
+ * documentation for details of the mapping.
+ * </p>
+ * This was taken from parquet-java 1.13.1 AvroSchemaConverter and modified
+ * to support local timestamp types by copying a few methods from 1.14.0 AvroSchemaConverter.
+ */
+@SuppressWarnings("all")
+public class AvroSchemaConverterWithNTZ extends HoodieAvroParquetSchemaConverter {
Review Comment:
Also rename the hardcoded class name
##########
hudi-hadoop-common/src/main/java/org/apache/parquet/avro/AvroSchemaConverterWithNTZ.java:
##########
@@ -0,0 +1,598 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.parquet.avro;
+
+import org.apache.avro.LogicalType;
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.parquet.schema.ConversionPatterns;
+import org.apache.parquet.schema.GroupType;
+import org.apache.parquet.schema.LogicalTypeAnnotation;
+import org.apache.parquet.schema.LogicalTypeAnnotation.UUIDLogicalTypeAnnotation;
+import org.apache.parquet.schema.MessageType;
+import org.apache.parquet.schema.PrimitiveType;
+import org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName;
+import org.apache.parquet.schema.Type;
+import org.apache.parquet.schema.Types;
+
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.List;
+import java.util.Map;
+import java.util.Set;
+
+import static org.apache.avro.JsonProperties.NULL_VALUE;
+import static org.apache.parquet.avro.AvroReadSupport.READ_INT96_AS_FIXED;
+import static org.apache.parquet.avro.AvroReadSupport.READ_INT96_AS_FIXED_DEFAULT;
+import static org.apache.parquet.avro.AvroWriteSupport.WRITE_OLD_LIST_STRUCTURE;
+import static org.apache.parquet.avro.AvroWriteSupport.WRITE_OLD_LIST_STRUCTURE_DEFAULT;
+import static org.apache.parquet.avro.AvroWriteSupport.WRITE_PARQUET_UUID;
+import static org.apache.parquet.avro.AvroWriteSupport.WRITE_PARQUET_UUID_DEFAULT;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.TimeUnit.MICROS;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.TimeUnit.MILLIS;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.dateType;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.decimalType;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.enumType;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.stringType;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.timeType;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.timestampType;
+import static org.apache.parquet.schema.LogicalTypeAnnotation.uuidType;
+import static org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.BINARY;
+import static org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.BOOLEAN;
+import static org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.DOUBLE;
+import static org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.FIXED_LEN_BYTE_ARRAY;
+import static org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.FLOAT;
+import static org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.INT32;
+import static org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.INT64;
+import static org.apache.parquet.schema.Type.Repetition.REPEATED;
+
+/**
+ * <p>
+ * Converts an Avro schema into a Parquet schema, or vice versa. See package
+ * documentation for details of the mapping.
+ * </p>
+ * This was taken from parquet-java 1.13.1 AvroSchemaConverter and modified
+ * to support local timestamp types by copying a few methods from 1.14.0 AvroSchemaConverter.
+ */
+@SuppressWarnings("all")
+public class AvroSchemaConverterWithNTZ extends HoodieAvroParquetSchemaConverter {
Review Comment:
```suggestion
public class AvroSchemaConverterWithTimestampNTZ extends HoodieAvroParquetSchemaConverter {
```
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Re: [PR] feat(metadata): Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3323524568
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2370842255
##########
hudi-common/src/main/java/org/apache/hudi/stats/ValueMetadata.java:
##########
@@ -0,0 +1,242 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.Pair;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.parquet.schema.LogicalTypeTokenParser;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.io.Serializable;
+
+import static org.apache.hudi.avro.AvroSchemaUtils.resolveNullableSchema;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE_ADDITIONAL_INFO;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE_ORDINAL;
+
+public class ValueMetadata implements Serializable {
+ private final ValueType valueType;
+
+ protected ValueMetadata(ValueType valueType) {
+ this.valueType = valueType;
+ }
+
+ public ValueType getValueType() {
+ return valueType;
+ }
+
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ return HoodieValueTypeInfo.newBuilder()
+ .setTypeOrdinal(valueType.ordinal())
+ .setAdditionalInfo(getAdditionalInfo())
+ .build();
+ }
+
+ public String getAdditionalInfo() {
+ return null;
+ }
+
+ public Comparable<?> standardizeJavaTypeAndPromote(Object val) {
+ return this.getValueType().standardizeJavaTypeAndPromote(val, this);
+ }
+
+ public Object wrapValue(Comparable<?> value) {
+ return this.getValueType().wrapValue(value, this);
+ }
+
+ public Comparable<?> unwrapValue(Object value) {
+ return this.getValueType().unwrapValue(value, this);
+ }
+
+ public void validate(Object minVal, Object maxVal) {
+ if (getValueType() == ValueType.V1) {
+ return;
+ }
+ this.getValueType().validate(minVal);
+ this.getValueType().validate(maxVal);
+ }
+
+ public static class V1EmptyMetadata extends ValueMetadata {
+ private static final V1EmptyMetadata V_1_EMPTY_METADATA = new V1EmptyMetadata();
+ public static V1EmptyMetadata get() {
+ return V_1_EMPTY_METADATA;
+ }
+
+ private V1EmptyMetadata() {
+ super(ValueType.V1);
+ }
+
+ @Override
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ // V1 should never be persisted to the MDT. It is only for in memory
+ return null;
+ }
+ }
+
+ public static final ValueMetadata NULL_METADATA = new ValueMetadata(ValueType.NULL);
+
+ public interface DecimalValueMetadata {
+
+ int getPrecision();
+
+ int getScale();
+
+ static String encodeData(DecimalValueMetadata decimalValueMetadata) {
+ return String.format("%d,%d", decimalValueMetadata.getPrecision(), decimalValueMetadata.getScale());
+ }
+
+ static Pair<Integer, Integer> decodeData(String data) {
+ //TODO: decide if we want to store things in a better way
+ String[] splits = data.split(",");
+ return Pair.of(Integer.parseInt(splits[0]), Integer.parseInt(splits[1]));
Review Comment:
ok added javadoc comment. I also have a test class TestValueMetadata to ensure that this doesn't get changed without care in handling. I also added a few comments saying not to change this without handling upgrade/downgrade and backwards compat
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2281046060
##########
hudi-common/src/main/java/org/apache/hudi/avro/HoodieAvroWrapperUtils.java:
##########
@@ -238,4 +231,121 @@ private static Pair<Boolean, String> getIsValueWrapperObfuscated(Object statsVal
}
return Pair.of(false, null);
}
+
+ public enum PrimitiveWrapperType {
+ V1(Object.class, HoodieAvroWrapperUtils::wrapValueIntoAvro, HoodieAvroWrapperUtils::unwrapAvroValueWrapper),
+ NULL(Void.class, HoodieAvroWrapperUtils::wrapNull, HoodieAvroWrapperUtils::unwrapNull),
+ BOOLEAN(Boolean.class, HoodieAvroWrapperUtils::wrapBoolean, HoodieAvroWrapperUtils::unwrapBoolean),
+ INT(Integer.class, HoodieAvroWrapperUtils::wrapInt, HoodieAvroWrapperUtils::unwrapInt),
+ LONG(Long.class, HoodieAvroWrapperUtils::wrapLong, HoodieAvroWrapperUtils::unwrapLong),
+ FLOAT(Float.class, HoodieAvroWrapperUtils::wrapFloat, HoodieAvroWrapperUtils::unwrapFloat),
+ DOUBLE(Double.class, HoodieAvroWrapperUtils::wrapDouble, HoodieAvroWrapperUtils::unwrapDouble),
+ STRING(String.class, HoodieAvroWrapperUtils::wrapString, HoodieAvroWrapperUtils::unwrapString),
+ BYTES(ByteBuffer.class, HoodieAvroWrapperUtils::wrapBytes, HoodieAvroWrapperUtils::unwrapBytes);
+
+ private final Class<?> clazz;
+ private final Function<Comparable<?>, Object> wrapper;
+ private final Function<Object, Comparable<?>> unwrapper;
+
+ PrimitiveWrapperType(Class<?> clazz, Function<Comparable<?>, Object> wrapper, Function<Object, Comparable<?>> unwrapper) {
+ this.clazz = clazz;
+ this.wrapper = wrapper;
+ this.unwrapper = unwrapper;
+ }
+
+ Class<?> getClazz() {
+ return clazz;
+ }
+
+ Object wrap(Comparable<?> value) {
+ return wrapper.apply(value);
+ }
+
+ Comparable<?> unwrap(Object value) {
+ return unwrapper.apply(value);
+ }
+ }
+
+ private static Object wrapNull(Comparable<?> value) {
+ return value;
+ }
+
+ private static Object wrapBoolean(Comparable<?> value) {
+ return BooleanWrapper.newBuilder(BOOLEAN_WRAPPER_BUILDER_STUB.get()).setValue((Boolean) value).build();
+ }
+
+ private static Object wrapInt(Comparable<?> value) {
+ return IntWrapper.newBuilder(INT_WRAPPER_BUILDER_STUB.get()).setValue((Integer) value).build();
+ }
+
+ private static Object wrapLong(Comparable<?> value) {
+ return LongWrapper.newBuilder(LONG_WRAPPER_BUILDER_STUB.get()).setValue((Long) value).build();
+ }
+
+ private static Object wrapFloat(Comparable<?> value) {
+ return FloatWrapper.newBuilder(FLOAT_WRAPPER_BUILDER_STUB.get()).setValue((Float) value).build();
+ }
+
+ private static Object wrapDouble(Comparable<?> value) {
+ return DoubleWrapper.newBuilder(DOUBLE_WRAPPER_BUILDER_STUB.get()).setValue((Double) value).build();
+ }
+
+ private static Object wrapString(Comparable<?> value) {
+ return StringWrapper.newBuilder(STRING_WRAPPER_BUILDER_STUB.get()).setValue((String) value).build();
+ }
+
+ private static Object wrapBytes(Comparable<?> value) {
+ return BytesWrapper.newBuilder(BYTES_WRAPPER_BUILDER_STUB.get()).setValue((ByteBuffer) value).build();
+ }
+
+ public static Object wrapArray(Comparable<?> value, Function<Comparable<?>, Object> wrapper) {
+ List<Object> avroValues = OrderingValues.getValues((ArrayComparable) value).stream().map(wrapper::apply).collect(Collectors.toList());
+ return ArrayWrapper.newBuilder(ARRAY_WRAPPER_BUILDER_STUB.get()).setWrappedValues(avroValues).build();
+ }
+
+ private static Comparable<?> unwrapNull(Object val) {
+ return (Comparable<?>) val;
+ }
+
+ private static Comparable<?> unwrapBoolean(Object val) {
+ return ((BooleanWrapper) val).getValue();
+ }
+
+ private static Comparable<?> unwrapInt(Object val) {
+ return ((IntWrapper) val).getValue();
+ }
+
+ private static Comparable<?> unwrapLong(Object val) {
+ return ((LongWrapper) val).getValue();
+ }
+
+ private static Comparable<?> unwrapFloat(Object val) {
+ return ((FloatWrapper) val).getValue();
+ }
+
+ private static Comparable<?> unwrapDouble(Object val) {
+ return ((DoubleWrapper) val).getValue();
+ }
+
+ private static Comparable<?> unwrapString(Object val) {
+ return ((StringWrapper) val).getValue();
+ }
+
+ private static Comparable<?> unwrapBytes(Object val) {
+ return ((BytesWrapper) val).getValue();
+ }
+
+ public static Comparable<?> unwrapArray(Object val, Function<Object, Comparable<?>> unwrapper) {
+ ArrayWrapper arrayWrapper = (ArrayWrapper) val;
+ return OrderingValues.create(arrayWrapper.getWrappedValues().stream()
+ .map(unwrapper::apply)
+ .toArray(Comparable[]::new));
+ }
+
+ // NOTE: This branch could be hit b/c Avro records could be reconstructed
+ // as {@code GenericRecord)
+ public static Comparable<?> unwrapGenericRecord(Object val) {
Review Comment:
Investigate more and see if we can improve this
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3194692884
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3197619672
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2323108108
##########
hudi-common/src/main/java/org/apache/hudi/avro/ValueType.java:
##########
@@ -0,0 +1,637 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.avro;
+
+import org.apache.hudi.avro.model.ArrayWrapper;
+import org.apache.hudi.common.util.DateTimeUtils;
+import org.apache.hudi.common.util.collection.ArrayComparable;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.avro.util.Utf8;
+import org.apache.parquet.io.api.Binary;
+import org.apache.parquet.schema.LogicalTypeTokenParser;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.math.BigDecimal;
+import java.math.BigInteger;
+import java.math.MathContext;
+import java.math.RoundingMode;
+import java.nio.ByteBuffer;
+import java.sql.Date;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.time.LocalDateTime;
+import java.time.LocalTime;
+import java.time.ZoneOffset;
+import java.util.Objects;
+import java.util.UUID;
+import java.util.function.BiFunction;
+import java.util.function.Function;
+
+import static org.apache.hudi.avro.HoodieAvroUtils.convertBytesToBigDecimal;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToMicros;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToNanos;
+import static org.apache.hudi.common.util.DateTimeUtils.microsToInstant;
+import static org.apache.hudi.common.util.DateTimeUtils.nanosToInstant;
+import static org.apache.hudi.common.util.StringUtils.getUTF8Bytes;
+
+public enum ValueType {
Review Comment:
cc @vinothchandar @bvaradar @balaji-varadarajan-ai
For support of column stats on all primitive and logical types with comprehensiveness and consistency across engines and schema systems, this PR introduces a new `ValueType` for defining the "type" of min and max values to store inside the column stats index. Since RFC-99 is going to introduce a new type system, this enum class serves as an interim solution for Hudi 1.1 to make the type management maintainable. This class is designed to keep the migration to the new type system in mind, so that callers should just replace the existing calls with the new type system when ready to reduce migration overhead. Also this is a use case to check to make sure all same functionality are still supported by the new type system as well.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3282528301
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3185878585
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3193990783
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2302167486
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/metadata/HoodieBackedTableMetadataWriter.java:
##########
@@ -575,10 +576,11 @@ private Pair<List<String>, Pair<Integer, HoodieData<HoodieRecord>>> initializeCo
if (partitionIdToAllFilesMap.isEmpty()) {
return Pair.of(Collections.emptyList(), Pair.of(fileGroupCount, engineContext.emptyHoodieData()));
}
+ HoodieIndexVersion columnStatsIndexVersion = existingIndexVersionOrDefault(PARTITION_NAME_COLUMN_STATS, dataMetaClient);
// Find the columns to index
final List<String> columnsToIndex = new ArrayList<>(HoodieTableMetadataUtil.getColumnsToIndex(dataMetaClient.getTableConfig(),
dataWriteConfig.getMetadataConfig(), tableSchema, true,
- Option.of(dataWriteConfig.getRecordMerger().getRecordType())).keySet());
+ Option.of(dataWriteConfig.getRecordMerger().getRecordType()), columnStatsIndexVersion).keySet());
Review Comment:
Avoid deriving the index version here and pass the meta client to `getColumnsToIndex` so that the logic of getting index version can be hided inside `getColumnsToIndex`?
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2305184833
##########
hudi-utilities/src/test/java/org/apache/hudi/utilities/deltastreamer/TestHoodieDeltaStreamer.java:
##########
@@ -670,6 +672,286 @@ public void testSchemaEvolution(String tableType, boolean useUserProvidedSchema,
defaultSchemaProviderClassName = FilebasedSchemaProvider.class.getName();
}
+ @Test
+ public void testTimestampMillis() throws Exception {
+ // if (zookeeperTestService != null) {
+ // zookeeperTestService.stop();
+ // zookeeperTestService = null;
+ // }
+ String tableBasePath = basePath + "/testTimestampMillis";
+ defaultSchemaProviderClassName = FilebasedSchemaProvider.class.getName();
+ // Insert data produced with Schema A, pass Schema A
+ HoodieDeltaStreamer.Config cfg = TestHelpers.makeConfig(tableBasePath, WriteOperationType.INSERT, Collections.singletonList(TestIdentityTransformer.class.getName()),
+ PROPS_FILENAME_TEST_SOURCE, false, true, false, null, HoodieTableType.MERGE_ON_READ.name());
+ cfg.payloadClassName = DefaultHoodieRecordPayload.class.getName();
+ cfg.recordMergeStrategyId = HoodieRecordMerger.EVENT_TIME_BASED_MERGE_STRATEGY_UUID;
+ cfg.recordMergeMode = RecordMergeMode.EVENT_TIME_ORDERING;
+ cfg.configs.add("hoodie.streamer.schemaprovider.source.schema.file=" + basePath + "/source-timestamp-millis.avsc");
+ cfg.configs.add("hoodie.streamer.schemaprovider.target.schema.file=" + basePath + "/source-timestamp-millis.avsc");
+ cfg.configs.add(String.format("%s=%s", HoodieCompactionConfig.PARQUET_SMALL_FILE_LIMIT.key(), "0"));
+
+
+ new HoodieDeltaStreamer(cfg, jsc).sync();
+ assertUseV2Checkpoint(HoodieTestUtils.createMetaClient(storage, tableBasePath));
+ assertRecordCount(1000, tableBasePath, sqlContext);
+ TestHelpers.assertCommitMetadata("00000", tableBasePath, 1);
+ TableSchemaResolver tableSchemaResolver = new TableSchemaResolver(
+ HoodieTestUtils.createMetaClient(storage, tableBasePath));
+ Schema tableSchema = tableSchemaResolver.getTableAvroSchema(false);
+ assertEquals("timestamp-millis", tableSchema.getField("current_ts").schema().getLogicalType().getName());
+ assertEquals(1000, sqlContext.read().options(hudiOpts).format("org.apache.hudi").load(tableBasePath).filter("current_ts > '1980-01-01'").count());
+
+ cfg = TestHelpers.makeConfig(tableBasePath, WriteOperationType.UPSERT, Collections.singletonList(TestIdentityTransformer.class.getName()),
+ PROPS_FILENAME_TEST_SOURCE, false, true, false, null, HoodieTableType.MERGE_ON_READ.name());
+ cfg.payloadClassName = DefaultHoodieRecordPayload.class.getName();
+ cfg.recordMergeStrategyId = HoodieRecordMerger.EVENT_TIME_BASED_MERGE_STRATEGY_UUID;
+ cfg.recordMergeMode = RecordMergeMode.EVENT_TIME_ORDERING;
+ cfg.configs.add("hoodie.streamer.schemaprovider.source.schema.file=" + basePath + "/source-timestamp-millis.avsc");
+ cfg.configs.add("hoodie.streamer.schemaprovider.target.schema.file=" + basePath + "/source-timestamp-millis.avsc");
+ cfg.configs.add(String.format("%s=%s", HoodieCompactionConfig.PARQUET_SMALL_FILE_LIMIT.key(), "0"));
+
+ new HoodieDeltaStreamer(cfg, jsc).sync();
+ assertUseV2Checkpoint(HoodieTestUtils.createMetaClient(storage, tableBasePath));
+ assertRecordCount(1450, tableBasePath, sqlContext);
+ TestHelpers.assertCommitMetadata("00001", tableBasePath, 2);
+ tableSchemaResolver = new TableSchemaResolver(
+ HoodieTestUtils.createMetaClient(storage, tableBasePath));
+ tableSchema = tableSchemaResolver.getTableAvroSchema(false);
+ assertEquals("timestamp-millis", tableSchema.getField("current_ts").schema().getLogicalType().getName());
+ sqlContext.clearCache();
+ assertEquals(1450, sqlContext.read().options(hudiOpts).format("org.apache.hudi").load(tableBasePath).filter("current_ts > '1980-01-01'").count());
+ assertEquals(1450, sqlContext.read().options(hudiOpts).format("org.apache.hudi").load(tableBasePath).filter("current_ts < '2080-01-01'").count());
+ assertEquals(0, sqlContext.read().options(hudiOpts).format("org.apache.hudi").load(tableBasePath).filter("current_ts < '1980-01-01'").count());
+ }
+
+ @Test
+ public void testLogicalTypes() throws Exception {
Review Comment:
parameterize and test with table version 6 and 8 and current
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3220919523
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2350277672
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/utils/SparkValueMetadata.java:
##########
@@ -0,0 +1,229 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.client.utils;
+
+import org.apache.hudi.avro.ValueMetadata;
+import org.apache.hudi.avro.ValueType;
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.ArrayComparable;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.spark.sql.types.ArrayType;
+import org.apache.spark.sql.types.BinaryType;
+import org.apache.spark.sql.types.BooleanType;
+import org.apache.spark.sql.types.ByteType;
+import org.apache.spark.sql.types.CharType;
+import org.apache.spark.sql.types.DataType;
+import org.apache.spark.sql.types.DateType;
+import org.apache.spark.sql.types.Decimal;
+import org.apache.spark.sql.types.DecimalType;
+import org.apache.spark.sql.types.DoubleType;
+import org.apache.spark.sql.types.FloatType;
+import org.apache.spark.sql.types.IntegerType;
+import org.apache.spark.sql.types.LongType;
+import org.apache.spark.sql.types.NullType;
+import org.apache.spark.sql.types.ShortType;
+import org.apache.spark.sql.types.StringType;
+import org.apache.spark.sql.types.TimestampType;
+import org.apache.spark.sql.types.VarcharType;
+
+import java.sql.Date;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.util.Arrays;
+
+public class SparkValueMetadata extends ValueMetadata {
+
+ private final DataType dataType;
+
+ protected SparkValueMetadata(ValueType valueType, DataType dataType) {
+ super(valueType);
+ this.dataType = dataType;
+ }
+
+ public Comparable convertSparkToJava(Object value) {
+ return convertSparkToJava(value, true);
+ }
+
+ public static SparkValueMetadata getValueMetadata(DataType dataType, HoodieIndexVersion indexVersion) {
+ if (indexVersion.lowerThan(HoodieIndexVersion.V2)) {
+ return SparkV1EmptyMetadata.get();
+ }
+ if (dataType == null) {
+ return new SparkValueMetadata(ValueType.NULL, null);
+ }
+ ValueType valueType = fromDataType(dataType);
+ if (valueType == ValueType.DECIMAL) {
+ return new SparkDecimalMetadata((DecimalType) dataType);
+ } else {
+ return new SparkValueMetadata(valueType, dataType);
+ }
+ }
+
+ private static ValueType fromDataType(DataType dataType) {
+ return fromDataType(dataType, true);
+ }
+
+ private static ValueType fromDataType(DataType dataType, boolean root) {
+ if (dataType instanceof NullType) {
+ return ValueType.NULL;
+ } else if (dataType instanceof BooleanType) {
+ return ValueType.BOOLEAN;
+ } else if (dataType instanceof IntegerType || dataType instanceof ShortType || dataType instanceof ByteType) {
+ return ValueType.INT;
+ } else if (dataType instanceof LongType) {
+ return ValueType.LONG;
+ } else if (dataType instanceof FloatType) {
+ return ValueType.FLOAT;
+ } else if (dataType instanceof DoubleType) {
+ return ValueType.DOUBLE;
+ } else if (dataType instanceof StringType || dataType instanceof CharType || dataType instanceof VarcharType) {
+ return ValueType.STRING;
+ } else if (dataType instanceof TimestampType) {
+ return ValueType.TIMESTAMP_MICROS;
+ } else if (dataType instanceof DecimalType) {
+ return ValueType.DECIMAL;
+ } else if (dataType instanceof DateType) {
+ return ValueType.DATE;
+ } else if (dataType instanceof BinaryType) {
+ return ValueType.BYTES;
+ } else if (dataType instanceof ArrayType) {
+ if (root) {
+ return fromDataType(((ArrayType) dataType).elementType(), false);
+ } else {
+ throw new IllegalArgumentException("Array of Array is not supported");
+ }
+ } else if (dataType.getClass().getName().contains("TimestampNTZType")) {
+ return ValueType.LOCAL_TIMESTAMP_MICROS;
+ } else {
+ throw new IllegalArgumentException("Unsupported data type: " + dataType);
+ }
+ }
+
+ private static class SparkV1EmptyMetadata extends SparkValueMetadata {
+ private static final SparkV1EmptyMetadata V_1_EMPTY_METADATA = new SparkV1EmptyMetadata();
+ public static SparkV1EmptyMetadata get() {
+ return V_1_EMPTY_METADATA;
+ }
+
+ private SparkV1EmptyMetadata() {
+ super(ValueType.V1, null);
+ }
+
+ @Override
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ return null;
+ }
+ }
+
+ private static class SparkDecimalMetadata extends SparkValueMetadata implements ValueMetadata.DecimalValueMetadata {
+
+ private final int precision;
+ private final int scale;
+
+ protected SparkDecimalMetadata(DecimalType decimalType) {
+ super(ValueType.DECIMAL, decimalType);
+ this.precision = decimalType.precision();
+ this.scale = decimalType.scale();
+ }
+
+ @Override
+ public int getPrecision() {
+ return precision;
+ }
+
+ @Override
+ public int getScale() {
+ return scale;
+ }
+
+ @Override
+ public String getAdditionalInfo() {
+ return DecimalValueMetadata.encodeData(this);
+ }
+ }
Review Comment:
Could we directly construct `DecimalValueMetadata` when needed instead of creating a new `SparkDecimalMetadata`? This is to avoid any discrepancy potentially introduced by `SparkDecimalMetadata` at the code level, i.e., there should not be any difference on storage for encoding decimal min/max across engines.
##########
hudi-common/src/test/java/org/apache/hudi/avro/TestValueType.java:
##########
@@ -0,0 +1,57 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.avro;
+
+import org.junit.jupiter.api.Test;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+
+public class TestValueType {
+
+ @Test
+ public void testValueTypeNumbering() {
Review Comment:
+1 on the test
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/utils/SparkValueMetadata.java:
##########
@@ -0,0 +1,230 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.client.utils;
+
+import org.apache.hudi.SparkAdapterSupport$;
+import org.apache.hudi.avro.ValueMetadata;
+import org.apache.hudi.avro.ValueType;
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.ArrayComparable;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.spark.sql.types.ArrayType;
+import org.apache.spark.sql.types.BinaryType;
+import org.apache.spark.sql.types.BooleanType;
+import org.apache.spark.sql.types.ByteType;
+import org.apache.spark.sql.types.CharType;
+import org.apache.spark.sql.types.DataType;
+import org.apache.spark.sql.types.DateType;
+import org.apache.spark.sql.types.Decimal;
+import org.apache.spark.sql.types.DecimalType;
+import org.apache.spark.sql.types.DoubleType;
+import org.apache.spark.sql.types.FloatType;
+import org.apache.spark.sql.types.IntegerType;
+import org.apache.spark.sql.types.LongType;
+import org.apache.spark.sql.types.NullType;
+import org.apache.spark.sql.types.ShortType;
+import org.apache.spark.sql.types.StringType;
+import org.apache.spark.sql.types.TimestampType;
+import org.apache.spark.sql.types.VarcharType;
+
+import java.sql.Date;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.util.Arrays;
+
+public class SparkValueMetadata extends ValueMetadata {
+
+ private final DataType dataType;
+
+ protected SparkValueMetadata(ValueType valueType, DataType dataType) {
+ super(valueType);
+ this.dataType = dataType;
+ }
+
+ public Comparable convertSparkToJava(Object value) {
+ return convertSparkToJava(value, true);
+ }
+
+ public static SparkValueMetadata getValueMetadata(DataType dataType, HoodieIndexVersion indexVersion) {
+ if (indexVersion.lowerThan(HoodieIndexVersion.V2)) {
+ return SparkV1EmptyMetadata.get();
+ }
+ if (dataType == null) {
+ return new SparkValueMetadata(ValueType.NULL, null);
+ }
+ ValueType valueType = fromDataType(dataType);
+ if (valueType == ValueType.DECIMAL) {
+ return new SparkDecimalMetadata((DecimalType) dataType);
+ } else {
+ return new SparkValueMetadata(valueType, dataType);
+ }
+ }
+
+ private static ValueType fromDataType(DataType dataType) {
+ return fromDataType(dataType, true);
+ }
+
+ private static ValueType fromDataType(DataType dataType, boolean root) {
+ if (dataType instanceof NullType) {
+ return ValueType.NULL;
+ } else if (dataType instanceof BooleanType) {
+ return ValueType.BOOLEAN;
+ } else if (dataType instanceof IntegerType || dataType instanceof ShortType || dataType instanceof ByteType) {
+ return ValueType.INT;
+ } else if (dataType instanceof LongType) {
+ return ValueType.LONG;
+ } else if (dataType instanceof FloatType) {
+ return ValueType.FLOAT;
+ } else if (dataType instanceof DoubleType) {
+ return ValueType.DOUBLE;
+ } else if (dataType instanceof StringType || dataType instanceof CharType || dataType instanceof VarcharType) {
+ return ValueType.STRING;
+ } else if (dataType instanceof TimestampType) {
Review Comment:
If the Avro schema stores `timestamp-millis` as the logical type (for which `TimestampType` is used in StructType schema), should the column stats index uses the type `ValueType.TIMESTAMP_MILLIS` for storing min and max?
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2350361345
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/io/storage/row/HoodieRowParquetWriteSupport.java:
##########
@@ -451,7 +451,7 @@ private Type convertField(Schema avroFieldSchema, StructField structField, Type.
.as(LogicalTypeAnnotation.timestampType(false, LogicalTypeAnnotation.TimeUnit.MICROS)).named(structField.name());
} else if (logicalType.getName().equals(LogicalTypes.localTimestampMillis().getName())) {
return Types.primitive(INT64, repetition)
- .as(LogicalTypeAnnotation.timestampType(false, LogicalTypeAnnotation.TimeUnit.MICROS)).named(structField.name());
+ .as(LogicalTypeAnnotation.timestampType(false, LogicalTypeAnnotation.TimeUnit.MILLIS)).named(structField.name());
Review Comment:
Good catch! Is there a test coverage on this?
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/utils/SparkValueMetadata.java:
##########
@@ -0,0 +1,230 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.client.utils;
+
+import org.apache.hudi.SparkAdapterSupport$;
+import org.apache.hudi.avro.ValueMetadata;
+import org.apache.hudi.avro.ValueType;
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.ArrayComparable;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.spark.sql.types.ArrayType;
+import org.apache.spark.sql.types.BinaryType;
+import org.apache.spark.sql.types.BooleanType;
+import org.apache.spark.sql.types.ByteType;
+import org.apache.spark.sql.types.CharType;
+import org.apache.spark.sql.types.DataType;
+import org.apache.spark.sql.types.DateType;
+import org.apache.spark.sql.types.Decimal;
+import org.apache.spark.sql.types.DecimalType;
+import org.apache.spark.sql.types.DoubleType;
+import org.apache.spark.sql.types.FloatType;
+import org.apache.spark.sql.types.IntegerType;
+import org.apache.spark.sql.types.LongType;
+import org.apache.spark.sql.types.NullType;
+import org.apache.spark.sql.types.ShortType;
+import org.apache.spark.sql.types.StringType;
+import org.apache.spark.sql.types.TimestampType;
+import org.apache.spark.sql.types.VarcharType;
+
+import java.sql.Date;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.util.Arrays;
+
+public class SparkValueMetadata extends ValueMetadata {
+
+ private final DataType dataType;
+
+ protected SparkValueMetadata(ValueType valueType, DataType dataType) {
+ super(valueType);
+ this.dataType = dataType;
+ }
+
+ public Comparable convertSparkToJava(Object value) {
+ return convertSparkToJava(value, true);
+ }
+
+ public static SparkValueMetadata getValueMetadata(DataType dataType, HoodieIndexVersion indexVersion) {
+ if (indexVersion.lowerThan(HoodieIndexVersion.V2)) {
+ return SparkV1EmptyMetadata.get();
+ }
+ if (dataType == null) {
+ return new SparkValueMetadata(ValueType.NULL, null);
+ }
+ ValueType valueType = fromDataType(dataType);
+ if (valueType == ValueType.DECIMAL) {
+ return new SparkDecimalMetadata((DecimalType) dataType);
+ } else {
+ return new SparkValueMetadata(valueType, dataType);
+ }
+ }
+
+ private static ValueType fromDataType(DataType dataType) {
+ return fromDataType(dataType, true);
+ }
+
+ private static ValueType fromDataType(DataType dataType, boolean root) {
+ if (dataType instanceof NullType) {
+ return ValueType.NULL;
+ } else if (dataType instanceof BooleanType) {
+ return ValueType.BOOLEAN;
+ } else if (dataType instanceof IntegerType || dataType instanceof ShortType || dataType instanceof ByteType) {
+ return ValueType.INT;
+ } else if (dataType instanceof LongType) {
+ return ValueType.LONG;
+ } else if (dataType instanceof FloatType) {
+ return ValueType.FLOAT;
+ } else if (dataType instanceof DoubleType) {
+ return ValueType.DOUBLE;
+ } else if (dataType instanceof StringType || dataType instanceof CharType || dataType instanceof VarcharType) {
+ return ValueType.STRING;
+ } else if (dataType instanceof TimestampType) {
+ return ValueType.TIMESTAMP_MICROS;
+ } else if (dataType instanceof DecimalType) {
+ return ValueType.DECIMAL;
+ } else if (dataType instanceof DateType) {
+ return ValueType.DATE;
+ } else if (dataType instanceof BinaryType) {
+ return ValueType.BYTES;
+ } else if (dataType instanceof ArrayType) {
+ if (root) {
+ return fromDataType(((ArrayType) dataType).elementType(), false);
+ } else {
+ throw new IllegalArgumentException("Array of Array is not supported");
+ }
+ } else if (SparkAdapterSupport$.MODULE$.sparkAdapter().isTimestampNTZType(dataType)) {
+ return ValueType.LOCAL_TIMESTAMP_MICROS;
+ } else {
+ throw new IllegalArgumentException("Unsupported data type: " + dataType);
+ }
+ }
+
+ private static class SparkV1EmptyMetadata extends SparkValueMetadata {
+ private static final SparkV1EmptyMetadata V_1_EMPTY_METADATA = new SparkV1EmptyMetadata();
+ public static SparkV1EmptyMetadata get() {
+ return V_1_EMPTY_METADATA;
+ }
+
+ private SparkV1EmptyMetadata() {
+ super(ValueType.V1, null);
+ }
+
+ @Override
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ return null;
+ }
+ }
+
+ private static class SparkDecimalMetadata extends SparkValueMetadata implements ValueMetadata.DecimalValueMetadata {
+
+ private final int precision;
+ private final int scale;
+
+ protected SparkDecimalMetadata(DecimalType decimalType) {
+ super(ValueType.DECIMAL, decimalType);
+ this.precision = decimalType.precision();
+ this.scale = decimalType.scale();
+ }
+
+ @Override
+ public int getPrecision() {
+ return precision;
+ }
+
+ @Override
+ public int getScale() {
+ return scale;
+ }
+
+ @Override
+ public String getAdditionalInfo() {
+ return DecimalValueMetadata.encodeData(this);
+ }
+ }
+
+ private Comparable convertSparkToJava(Object value, boolean rootLevel) {
+ if (value == null) {
+ return null;
+ }
+
+ if (value instanceof org.apache.spark.sql.catalyst.util.ArrayData) {
+ if (rootLevel) {
+ return new ArrayComparable(Arrays.stream(((org.apache.spark.sql.catalyst.util.ArrayData) value)
+ .toObjectArray(((org.apache.spark.sql.types.ArrayType) dataType).elementType()))
+ .map(v -> convertSparkToJava(v, false)).toArray(Comparable[]::new));
+ } else {
+ throw new IllegalArgumentException("array of arrays not supported");
+ }
+ }
+
+ switch (getValueType()) {
+ case V1:
+ return (Comparable) value;
+ case NULL:
+ return null;
+ case BOOLEAN:
+ return (Boolean) value;
+ case INT:
+ return (Integer) value;
+ case LONG:
+ return (Long) value;
+ case FLOAT:
+ return (Float) value;
+ case DOUBLE:
+ return (Double) value;
+ case STRING:
+ return (String) value;
+ case BYTES:
+ return ValueType.castToBytes(value);
+ case DECIMAL:
+ return ((Decimal) value).toJavaBigDecimal();
+ case DATE:
+ return ValueType.castToDate(value, this);
+ case TIMESTAMP_MICROS:
+ return ValueType.castToTimestampMicros(value, this);
+ case LOCAL_TIMESTAMP_MICROS:
+ return ValueType.castToLocalTimestampMicros(value, this);
+ case FIXED:
+ case UUID:
+ case TIME_MILLIS:
+ case TIME_MICROS:
+ case TIMESTAMP_MILLIS:
+ case TIMESTAMP_NANOS:
+ case LOCAL_TIMESTAMP_MILLIS:
+ case LOCAL_TIMESTAMP_NANOS:
+ default:
+ throw new IllegalStateException("Spark value metadata for expression index should never be " + getValueType().name());
+ }
+ }
+
+ public static Object convertJavaTypeToSparkType(Comparable<?> javaVal, boolean useJava8api) {
Review Comment:
So for Spark the `java.sql.Timestamp` and `java.sql.Date` are used when not using Java 8 API. Could we document the nuance in a code comment based on what Spark expects and what Hudi provides when extracting the values so the expectation is clear?
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2354075418
##########
hudi-common/src/main/java/org/apache/hudi/stats/ValueType.java:
##########
@@ -0,0 +1,668 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.avro.AvroSchemaUtils;
+import org.apache.hudi.avro.HoodieAvroWrapperUtils;
+import org.apache.hudi.common.util.DateTimeUtils;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.avro.util.Utf8;
+import org.apache.parquet.io.api.Binary;
+import org.apache.parquet.schema.LogicalTypeTokenParser;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.math.BigDecimal;
+import java.math.BigInteger;
+import java.math.MathContext;
+import java.math.RoundingMode;
+import java.nio.ByteBuffer;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.time.LocalDateTime;
+import java.time.LocalTime;
+import java.time.ZoneOffset;
+import java.util.Objects;
+import java.util.UUID;
+import java.util.function.BiFunction;
+import java.util.function.Function;
+
+import static org.apache.hudi.avro.HoodieAvroUtils.convertBytesToBigDecimal;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToMicros;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToNanos;
+import static org.apache.hudi.common.util.DateTimeUtils.microsToInstant;
+import static org.apache.hudi.common.util.DateTimeUtils.nanosToInstant;
+import static org.apache.hudi.common.util.StringUtils.getUTF8Bytes;
+
+public enum ValueType {
+ V1(HoodieAvroWrapperUtils.PrimitiveWrapperType.V1.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.V1,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ NULL(HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ BOOLEAN(HoodieAvroWrapperUtils.PrimitiveWrapperType.BOOLEAN, ValueType::castToBoolean),
+ INT(HoodieAvroWrapperUtils.PrimitiveWrapperType.INT, ValueType::castToInteger),
+ LONG(HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG, ValueType::castToLong),
+ FLOAT(HoodieAvroWrapperUtils.PrimitiveWrapperType.FLOAT, ValueType::castToFloat),
+ DOUBLE(HoodieAvroWrapperUtils.PrimitiveWrapperType.DOUBLE, ValueType::castToDouble),
+ STRING(HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING, ValueType::castToString),
+ BYTES(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToBytes),
+ FIXED(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToFixed),
+ DECIMAL(BigDecimal.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES,
+ ValueType::castToDecimal, ValueType::toDecimal, ValueType::fromDecimal),
+ UUID(UUID.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING,
+ ValueType::castToUUID, ValueType::toUUID, ValueType::fromUUID),
+ DATE(LocalDate.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToDate, ValueType::toDate, ValueType::fromDate),
+ TIME_MILLIS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToTimeMillis, ValueType::toTimeMillis, ValueType::fromTimeMillis),
+ TIME_MICROS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimeMicros, ValueType::toTimeMicros, ValueType::fromTimeMicros),
+ TIMESTAMP_MILLIS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMillis, ValueType::toTimestampMillis, ValueType::fromTimestampMillis),
+ TIMESTAMP_MICROS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMicros, ValueType::toTimestampMicros, ValueType::fromTimestampMicros),
+ TIMESTAMP_NANOS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampNanos, ValueType::toTimestampNanos, ValueType::fromTimestampNanos),
+ LOCAL_TIMESTAMP_MILLIS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMillis, ValueType::toLocalTimestampMillis, ValueType::fromLocalTimestampMillis),
+ LOCAL_TIMESTAMP_MICROS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMicros, ValueType::toLocalTimestampMicros, ValueType::fromLocalTimestampMicros),
+ LOCAL_TIMESTAMP_NANOS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampNanos, ValueType::toLocalTimestampNanos, ValueType::fromLocalTimestampNanos);
+
+ private final Class<?> internalType;
+ private final HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType;
+ private final BiFunction<Object, ValueMetadata, Comparable<?>> standardize;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toPrimitive;
+
+ ValueType(HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType, Function<Object, Object> single) {
+ this(primitiveWrapperType.getClazz(),
+ primitiveWrapperType,
+ (val, meta) -> (Comparable<?>) single.apply(val),
+ ValueType::passThrough,
+ ValueType::passThrough);
+ }
+
+ ValueType(Class<?> internalType,
+ HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType,
+ BiFunction<Object, ValueMetadata, Comparable<?>> standardize,
+ BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex,
+ BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toPrimitive) {
+ this.internalType = internalType;
+ this.primitiveWrapperType = primitiveWrapperType;
+ this.standardize = standardize;
+ this.toComplex = toComplex;
+ this.toPrimitive = toPrimitive;
+ }
+
+ Comparable<?> standardizeJavaTypeAndPromote(Object val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return standardize.apply(val, meta);
+ }
+
+ private Comparable<?> convertIntoPrimitive(Comparable<?> val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return toPrimitive.apply(val, meta);
+ }
+
+ private Comparable<?> convertIntoComplex(Comparable<?> val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return toComplex.apply(val, meta);
+ }
+
+ void validate(Object val) {
+ if (val == null) {
+ return;
+ }
+
+ if (!internalType.isInstance(val)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ internalType.getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ }
+
+ public Object wrapValue(Comparable<?> val, ValueMetadata meta) {
+ if (meta.getValueType() == V1) {
+ return primitiveWrapperType.wrap(val);
+ }
+
+ if (val == null) {
+ return null;
+ }
+ if (!this.internalType.isInstance(val)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ this.internalType.getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ return primitiveWrapperType.wrap(convertIntoPrimitive(val, meta));
+ }
+
+ public Comparable<?> unwrapValue(Object val, ValueMetadata meta) {
+ if (meta.getValueType() == V1) {
+ return primitiveWrapperType.unwrap(val);
Review Comment:
The primitiveWrapperType is V1 which just invokes the original method that the code used to go through
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2352895680
##########
hudi-client/hudi-spark-client/src/test/java/org/apache/hudi/client/functional/TestHoodieBackedTableMetadata.java:
##########
@@ -350,7 +375,7 @@ public void testMetadataRecordKeyExcludeFromPayload(final HoodieTableType tableT
* plan has not been successfully executed before the new one is scheduled.
*/
@ParameterizedTest
- @CsvSource({"COPY_ON_WRITE,6", "COPY_ON_WRITE,8", "MERGE_ON_READ,6", "MERGE_ON_READ,8"})
+ @MethodSource("testMetadataTableKeyGeneratorArgs")
Review Comment:
I don't think it was too bad, but do we know why 6 and 8 were tested? Maybe we can drop 8 and just do 6 and current?
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2350062251
##########
hudi-common/src/main/java/org/apache/hudi/avro/ValueMetadata.java:
##########
@@ -0,0 +1,241 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.avro;
+
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.Pair;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.parquet.schema.LogicalTypeTokenParser;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.io.Serializable;
+
+import static org.apache.hudi.avro.AvroSchemaUtils.resolveNullableSchema;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE_ADDITIONAL_INFO;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE_ORDINAL;
+
+public class ValueMetadata implements Serializable {
Review Comment:
Let's add javadocs
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2354071152
##########
hudi-common/src/main/java/org/apache/hudi/stats/ValueType.java:
##########
@@ -0,0 +1,668 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.avro.AvroSchemaUtils;
+import org.apache.hudi.avro.HoodieAvroWrapperUtils;
+import org.apache.hudi.common.util.DateTimeUtils;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.avro.util.Utf8;
+import org.apache.parquet.io.api.Binary;
+import org.apache.parquet.schema.LogicalTypeTokenParser;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.math.BigDecimal;
+import java.math.BigInteger;
+import java.math.MathContext;
+import java.math.RoundingMode;
+import java.nio.ByteBuffer;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.time.LocalDateTime;
+import java.time.LocalTime;
+import java.time.ZoneOffset;
+import java.util.Objects;
+import java.util.UUID;
+import java.util.function.BiFunction;
+import java.util.function.Function;
+
+import static org.apache.hudi.avro.HoodieAvroUtils.convertBytesToBigDecimal;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToMicros;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToNanos;
+import static org.apache.hudi.common.util.DateTimeUtils.microsToInstant;
+import static org.apache.hudi.common.util.DateTimeUtils.nanosToInstant;
+import static org.apache.hudi.common.util.StringUtils.getUTF8Bytes;
+
+public enum ValueType {
+ V1(HoodieAvroWrapperUtils.PrimitiveWrapperType.V1.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.V1,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ NULL(HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ BOOLEAN(HoodieAvroWrapperUtils.PrimitiveWrapperType.BOOLEAN, ValueType::castToBoolean),
+ INT(HoodieAvroWrapperUtils.PrimitiveWrapperType.INT, ValueType::castToInteger),
+ LONG(HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG, ValueType::castToLong),
+ FLOAT(HoodieAvroWrapperUtils.PrimitiveWrapperType.FLOAT, ValueType::castToFloat),
+ DOUBLE(HoodieAvroWrapperUtils.PrimitiveWrapperType.DOUBLE, ValueType::castToDouble),
+ STRING(HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING, ValueType::castToString),
+ BYTES(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToBytes),
+ FIXED(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToFixed),
+ DECIMAL(BigDecimal.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES,
+ ValueType::castToDecimal, ValueType::toDecimal, ValueType::fromDecimal),
+ UUID(UUID.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING,
+ ValueType::castToUUID, ValueType::toUUID, ValueType::fromUUID),
+ DATE(LocalDate.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToDate, ValueType::toDate, ValueType::fromDate),
+ TIME_MILLIS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToTimeMillis, ValueType::toTimeMillis, ValueType::fromTimeMillis),
+ TIME_MICROS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimeMicros, ValueType::toTimeMicros, ValueType::fromTimeMicros),
+ TIMESTAMP_MILLIS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMillis, ValueType::toTimestampMillis, ValueType::fromTimestampMillis),
+ TIMESTAMP_MICROS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMicros, ValueType::toTimestampMicros, ValueType::fromTimestampMicros),
+ TIMESTAMP_NANOS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampNanos, ValueType::toTimestampNanos, ValueType::fromTimestampNanos),
+ LOCAL_TIMESTAMP_MILLIS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMillis, ValueType::toLocalTimestampMillis, ValueType::fromLocalTimestampMillis),
+ LOCAL_TIMESTAMP_MICROS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMicros, ValueType::toLocalTimestampMicros, ValueType::fromLocalTimestampMicros),
+ LOCAL_TIMESTAMP_NANOS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampNanos, ValueType::toLocalTimestampNanos, ValueType::fromLocalTimestampNanos);
+
+ private final Class<?> internalType;
+ private final HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType;
+ private final BiFunction<Object, ValueMetadata, Comparable<?>> standardize;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toPrimitive;
+
+ ValueType(HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType, Function<Object, Object> single) {
Review Comment:
as opposed to BiFunction
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2354163047
##########
hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/spark/sql/adapter/BaseSpark3Adapter.scala:
##########
@@ -110,5 +110,8 @@ abstract class BaseSpark3Adapter extends SparkAdapter with Logging {
def stopSparkContext(jssc: JavaSparkContext, exitCode: Int): Unit
// Older Spark 3.x versions do not have TimestampNTZType
- override def isTimestampNTZType(dataType: DataType): Boolean = false
+ override def isTimestampNTZType(dataType: DataType): Boolean = {
+ // TimestampNTZType$ but don't want to rule out possibility of TimestampNTZType
+ dataType.getClass.getSimpleName.startsWith("TimestampNTZType")
+ }
Review Comment:
spark 3.3 it's not
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3304125317
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2355858831
##########
hudi-spark-datasource/hudi-spark/src/test/resources/schema_with_logical_types.avsc:
##########
@@ -30,12 +30,11 @@
},
{
"name": "ts",
- "type": ["long", "null"]
Review Comment:
I don't think this should be avoided, because it's not really a valid schema for hudi.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3304316090
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2349941534
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/index/bloom/HoodieBloomIndex.java:
##########
@@ -231,12 +231,13 @@ protected List<Pair<String, BloomIndexFileInfo>> loadColumnRangesFromMetaIndex(
List<Pair<String, BloomIndexFileInfo>> result = new ArrayList<>(fileToColumnStatsMap.size());
for (Map.Entry<Pair<String, String>, HoodieMetadataColumnStats> entry : fileToColumnStatsMap.entrySet()) {
+ ValueMetadata valueMetadata = ValueMetadata.getValueMetadata(entry.getValue().getValueType());
result.add(Pair.of(entry.getKey().getLeft(),
new BloomIndexFileInfo(
partitionAndFileNameToFileId.get(entry.getKey()),
// NOTE: Here we assume that the type of the primary key field is string
- unwrapAvroValueWrapper(entry.getValue().getMinValue()).toString(),
- unwrapAvroValueWrapper(entry.getValue().getMaxValue()).toString()
+ valueMetadata.unwrapValue(entry.getValue().getMinValue()).toString(),
+ valueMetadata.unwrapValue(entry.getValue().getMaxValue()).toString()
Review Comment:
@jonvex also, when doing the backward compatibility testing, let's enforce stricter validation by comparing the metadata records in column stats index in the Metadata Table written by 0.14 and 1.1 (this PR) using the same set of inserts/updates to make sure the storage bytes are the same.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3300119664
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2353702608
##########
hudi-common/src/main/java/org/apache/hudi/internal/schema/Type.java:
##########
@@ -64,7 +64,14 @@ enum TypeID {
TIME(Long.class),
TIMESTAMP(Long.class),
DECIMAL(BigDecimal.class),
- UUID(UUID.class);
+ UUID(UUID.class),
+ DECIMAL_BYTES(BigDecimal.class),
+ DECIMAL_FIXED(BigDecimal.class),
Review Comment:
Is this for Avro compatibility? I'm trying to recollect the reason of adding two more decimal representation types.
##########
hudi-common/src/main/java/org/apache/hudi/internal/schema/Types.java:
##########
@@ -353,6 +347,51 @@ public int precision() {
return precision;
}
+ @Override
+ public boolean equals(Object o) {
+ if (this == o) {
+ return true;
+ } else if (!(o instanceof DecimalBase)) {
+ return false;
+ }
+
+ DecimalBase that = (DecimalBase) o;
+ if (scale != that.scale) {
+ return false;
+ }
+ return precision == that.precision;
+ }
+
+ @Override
+ public int hashCode() {
+ return Objects.hash(this.getClass(), scale, precision);
+ }
+ }
+
+ /**
+ * Decimal primitive type.
+ */
+ public static class DecimalType extends DecimalTypeFixed {
+ public static DecimalType get(int precision, int scale) {
+ return new DecimalType(precision, scale);
+ }
+
+ /**
+ * Return the minimum number of bytes needed to store a decimal with a give 'precision'.
+ * reference from Spark release 3.1 .
+ */
+ private static int computeMinBytesForDecimalPrecision(int precision) {
Review Comment:
Now I see the min bytes calculation is moved here.
##########
hudi-common/src/main/java/org/apache/hudi/stats/ValueType.java:
##########
@@ -0,0 +1,668 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.avro.AvroSchemaUtils;
+import org.apache.hudi.avro.HoodieAvroWrapperUtils;
+import org.apache.hudi.common.util.DateTimeUtils;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.avro.util.Utf8;
+import org.apache.parquet.io.api.Binary;
+import org.apache.parquet.schema.LogicalTypeTokenParser;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.math.BigDecimal;
+import java.math.BigInteger;
+import java.math.MathContext;
+import java.math.RoundingMode;
+import java.nio.ByteBuffer;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.time.LocalDateTime;
+import java.time.LocalTime;
+import java.time.ZoneOffset;
+import java.util.Objects;
+import java.util.UUID;
+import java.util.function.BiFunction;
+import java.util.function.Function;
+
+import static org.apache.hudi.avro.HoodieAvroUtils.convertBytesToBigDecimal;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToMicros;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToNanos;
+import static org.apache.hudi.common.util.DateTimeUtils.microsToInstant;
+import static org.apache.hudi.common.util.DateTimeUtils.nanosToInstant;
+import static org.apache.hudi.common.util.StringUtils.getUTF8Bytes;
+
+public enum ValueType {
+ V1(HoodieAvroWrapperUtils.PrimitiveWrapperType.V1.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.V1,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ NULL(HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ BOOLEAN(HoodieAvroWrapperUtils.PrimitiveWrapperType.BOOLEAN, ValueType::castToBoolean),
+ INT(HoodieAvroWrapperUtils.PrimitiveWrapperType.INT, ValueType::castToInteger),
+ LONG(HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG, ValueType::castToLong),
+ FLOAT(HoodieAvroWrapperUtils.PrimitiveWrapperType.FLOAT, ValueType::castToFloat),
+ DOUBLE(HoodieAvroWrapperUtils.PrimitiveWrapperType.DOUBLE, ValueType::castToDouble),
+ STRING(HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING, ValueType::castToString),
+ BYTES(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToBytes),
+ FIXED(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToFixed),
+ DECIMAL(BigDecimal.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES,
+ ValueType::castToDecimal, ValueType::toDecimal, ValueType::fromDecimal),
+ UUID(UUID.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING,
+ ValueType::castToUUID, ValueType::toUUID, ValueType::fromUUID),
+ DATE(LocalDate.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToDate, ValueType::toDate, ValueType::fromDate),
+ TIME_MILLIS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToTimeMillis, ValueType::toTimeMillis, ValueType::fromTimeMillis),
+ TIME_MICROS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimeMicros, ValueType::toTimeMicros, ValueType::fromTimeMicros),
+ TIMESTAMP_MILLIS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMillis, ValueType::toTimestampMillis, ValueType::fromTimestampMillis),
+ TIMESTAMP_MICROS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMicros, ValueType::toTimestampMicros, ValueType::fromTimestampMicros),
+ TIMESTAMP_NANOS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampNanos, ValueType::toTimestampNanos, ValueType::fromTimestampNanos),
+ LOCAL_TIMESTAMP_MILLIS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMillis, ValueType::toLocalTimestampMillis, ValueType::fromLocalTimestampMillis),
+ LOCAL_TIMESTAMP_MICROS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMicros, ValueType::toLocalTimestampMicros, ValueType::fromLocalTimestampMicros),
+ LOCAL_TIMESTAMP_NANOS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampNanos, ValueType::toLocalTimestampNanos, ValueType::fromLocalTimestampNanos);
+
+ private final Class<?> internalType;
+ private final HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType;
+ private final BiFunction<Object, ValueMetadata, Comparable<?>> standardize;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toPrimitive;
+
+ ValueType(HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType, Function<Object, Object> single) {
+ this(primitiveWrapperType.getClazz(),
+ primitiveWrapperType,
+ (val, meta) -> (Comparable<?>) single.apply(val),
+ ValueType::passThrough,
+ ValueType::passThrough);
+ }
+
+ ValueType(Class<?> internalType,
+ HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType,
+ BiFunction<Object, ValueMetadata, Comparable<?>> standardize,
+ BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex,
+ BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toPrimitive) {
+ this.internalType = internalType;
+ this.primitiveWrapperType = primitiveWrapperType;
+ this.standardize = standardize;
+ this.toComplex = toComplex;
+ this.toPrimitive = toPrimitive;
+ }
+
+ Comparable<?> standardizeJavaTypeAndPromote(Object val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return standardize.apply(val, meta);
+ }
+
+ private Comparable<?> convertIntoPrimitive(Comparable<?> val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return toPrimitive.apply(val, meta);
+ }
+
+ private Comparable<?> convertIntoComplex(Comparable<?> val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return toComplex.apply(val, meta);
+ }
+
+ void validate(Object val) {
+ if (val == null) {
+ return;
+ }
+
+ if (!internalType.isInstance(val)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ internalType.getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ }
+
+ public Object wrapValue(Comparable<?> val, ValueMetadata meta) {
+ if (meta.getValueType() == V1) {
+ return primitiveWrapperType.wrap(val);
+ }
+
+ if (val == null) {
+ return null;
+ }
+ if (!this.internalType.isInstance(val)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ this.internalType.getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ return primitiveWrapperType.wrap(convertIntoPrimitive(val, meta));
+ }
+
+ public Comparable<?> unwrapValue(Object val, ValueMetadata meta) {
+ if (meta.getValueType() == V1) {
+ return primitiveWrapperType.unwrap(val);
Review Comment:
Are V1 logical value wrappers e.g., `DateWrapper`, `DecimalWrapper`, `TimeMicrosWrapper`, handled separately?
##########
hudi-common/src/main/java/org/apache/hudi/stats/ValueType.java:
##########
@@ -0,0 +1,668 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.avro.AvroSchemaUtils;
+import org.apache.hudi.avro.HoodieAvroWrapperUtils;
+import org.apache.hudi.common.util.DateTimeUtils;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.avro.util.Utf8;
+import org.apache.parquet.io.api.Binary;
+import org.apache.parquet.schema.LogicalTypeTokenParser;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.math.BigDecimal;
+import java.math.BigInteger;
+import java.math.MathContext;
+import java.math.RoundingMode;
+import java.nio.ByteBuffer;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.time.LocalDateTime;
+import java.time.LocalTime;
+import java.time.ZoneOffset;
+import java.util.Objects;
+import java.util.UUID;
+import java.util.function.BiFunction;
+import java.util.function.Function;
+
+import static org.apache.hudi.avro.HoodieAvroUtils.convertBytesToBigDecimal;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToMicros;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToNanos;
+import static org.apache.hudi.common.util.DateTimeUtils.microsToInstant;
+import static org.apache.hudi.common.util.DateTimeUtils.nanosToInstant;
+import static org.apache.hudi.common.util.StringUtils.getUTF8Bytes;
+
+public enum ValueType {
+ V1(HoodieAvroWrapperUtils.PrimitiveWrapperType.V1.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.V1,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ NULL(HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ BOOLEAN(HoodieAvroWrapperUtils.PrimitiveWrapperType.BOOLEAN, ValueType::castToBoolean),
+ INT(HoodieAvroWrapperUtils.PrimitiveWrapperType.INT, ValueType::castToInteger),
+ LONG(HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG, ValueType::castToLong),
+ FLOAT(HoodieAvroWrapperUtils.PrimitiveWrapperType.FLOAT, ValueType::castToFloat),
+ DOUBLE(HoodieAvroWrapperUtils.PrimitiveWrapperType.DOUBLE, ValueType::castToDouble),
+ STRING(HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING, ValueType::castToString),
+ BYTES(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToBytes),
+ FIXED(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToFixed),
+ DECIMAL(BigDecimal.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES,
+ ValueType::castToDecimal, ValueType::toDecimal, ValueType::fromDecimal),
+ UUID(UUID.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING,
+ ValueType::castToUUID, ValueType::toUUID, ValueType::fromUUID),
+ DATE(LocalDate.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToDate, ValueType::toDate, ValueType::fromDate),
+ TIME_MILLIS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToTimeMillis, ValueType::toTimeMillis, ValueType::fromTimeMillis),
+ TIME_MICROS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimeMicros, ValueType::toTimeMicros, ValueType::fromTimeMicros),
+ TIMESTAMP_MILLIS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMillis, ValueType::toTimestampMillis, ValueType::fromTimestampMillis),
+ TIMESTAMP_MICROS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMicros, ValueType::toTimestampMicros, ValueType::fromTimestampMicros),
+ TIMESTAMP_NANOS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampNanos, ValueType::toTimestampNanos, ValueType::fromTimestampNanos),
+ LOCAL_TIMESTAMP_MILLIS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMillis, ValueType::toLocalTimestampMillis, ValueType::fromLocalTimestampMillis),
+ LOCAL_TIMESTAMP_MICROS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMicros, ValueType::toLocalTimestampMicros, ValueType::fromLocalTimestampMicros),
+ LOCAL_TIMESTAMP_NANOS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampNanos, ValueType::toLocalTimestampNanos, ValueType::fromLocalTimestampNanos);
+
+ private final Class<?> internalType;
+ private final HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType;
+ private final BiFunction<Object, ValueMetadata, Comparable<?>> standardize;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toPrimitive;
+
+ ValueType(HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType, Function<Object, Object> single) {
+ this(primitiveWrapperType.getClazz(),
+ primitiveWrapperType,
+ (val, meta) -> (Comparable<?>) single.apply(val),
+ ValueType::passThrough,
+ ValueType::passThrough);
+ }
+
+ ValueType(Class<?> internalType,
+ HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType,
+ BiFunction<Object, ValueMetadata, Comparable<?>> standardize,
+ BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex,
+ BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toPrimitive) {
+ this.internalType = internalType;
+ this.primitiveWrapperType = primitiveWrapperType;
+ this.standardize = standardize;
+ this.toComplex = toComplex;
+ this.toPrimitive = toPrimitive;
+ }
+
+ Comparable<?> standardizeJavaTypeAndPromote(Object val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return standardize.apply(val, meta);
+ }
+
+ private Comparable<?> convertIntoPrimitive(Comparable<?> val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return toPrimitive.apply(val, meta);
+ }
+
+ private Comparable<?> convertIntoComplex(Comparable<?> val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return toComplex.apply(val, meta);
+ }
+
+ void validate(Object val) {
+ if (val == null) {
+ return;
+ }
+
+ if (!internalType.isInstance(val)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ internalType.getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ }
+
+ public Object wrapValue(Comparable<?> val, ValueMetadata meta) {
+ if (meta.getValueType() == V1) {
+ return primitiveWrapperType.wrap(val);
+ }
+
+ if (val == null) {
+ return null;
+ }
+ if (!this.internalType.isInstance(val)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ this.internalType.getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ return primitiveWrapperType.wrap(convertIntoPrimitive(val, meta));
+ }
+
+ public Comparable<?> unwrapValue(Object val, ValueMetadata meta) {
+ if (meta.getValueType() == V1) {
+ return primitiveWrapperType.unwrap(val);
+ }
+
+ if (val == null) {
+ return null;
+ }
+
+ if (!primitiveWrapperType.getWrapperClass().isInstance(val)) {
+ if (!(val instanceof GenericRecord)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ primitiveWrapperType.getWrapperClass().getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ } else if (((GenericRecord) val).getSchema().getField("value") != null) {
+ return standardizeJavaTypeAndPromote(HoodieAvroWrapperUtils.unwrapGenericRecord(val), meta);
+ } else {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ primitiveWrapperType.getWrapperClass().getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ }
+ return convertIntoComplex(primitiveWrapperType.unwrap(val), meta);
+ }
+
+ private static ValueType[] myEnumValues;
+
+ public static ValueType fromInt(int i) {
+ if (ValueType.myEnumValues == null) {
+ ValueType.myEnumValues = ValueType.values();
+ }
+ return ValueType.myEnumValues[i];
+ }
+
+ public static ValueType fromPrimitiveType(PrimitiveType primitiveType) {
Review Comment:
This is parquet specific so rename it to be specific?
```suggestion
public static ValueType fromParquetPrimitiveType(PrimitiveType primitiveType) {
```
##########
hudi-common/src/main/java/org/apache/hudi/stats/ValueType.java:
##########
@@ -0,0 +1,668 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.avro.AvroSchemaUtils;
+import org.apache.hudi.avro.HoodieAvroWrapperUtils;
+import org.apache.hudi.common.util.DateTimeUtils;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.avro.util.Utf8;
+import org.apache.parquet.io.api.Binary;
+import org.apache.parquet.schema.LogicalTypeTokenParser;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.math.BigDecimal;
+import java.math.BigInteger;
+import java.math.MathContext;
+import java.math.RoundingMode;
+import java.nio.ByteBuffer;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.time.LocalDateTime;
+import java.time.LocalTime;
+import java.time.ZoneOffset;
+import java.util.Objects;
+import java.util.UUID;
+import java.util.function.BiFunction;
+import java.util.function.Function;
+
+import static org.apache.hudi.avro.HoodieAvroUtils.convertBytesToBigDecimal;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToMicros;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToNanos;
+import static org.apache.hudi.common.util.DateTimeUtils.microsToInstant;
+import static org.apache.hudi.common.util.DateTimeUtils.nanosToInstant;
+import static org.apache.hudi.common.util.StringUtils.getUTF8Bytes;
+
+public enum ValueType {
+ V1(HoodieAvroWrapperUtils.PrimitiveWrapperType.V1.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.V1,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ NULL(HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ BOOLEAN(HoodieAvroWrapperUtils.PrimitiveWrapperType.BOOLEAN, ValueType::castToBoolean),
+ INT(HoodieAvroWrapperUtils.PrimitiveWrapperType.INT, ValueType::castToInteger),
+ LONG(HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG, ValueType::castToLong),
+ FLOAT(HoodieAvroWrapperUtils.PrimitiveWrapperType.FLOAT, ValueType::castToFloat),
+ DOUBLE(HoodieAvroWrapperUtils.PrimitiveWrapperType.DOUBLE, ValueType::castToDouble),
+ STRING(HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING, ValueType::castToString),
+ BYTES(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToBytes),
+ FIXED(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToFixed),
+ DECIMAL(BigDecimal.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES,
+ ValueType::castToDecimal, ValueType::toDecimal, ValueType::fromDecimal),
+ UUID(UUID.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING,
+ ValueType::castToUUID, ValueType::toUUID, ValueType::fromUUID),
+ DATE(LocalDate.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToDate, ValueType::toDate, ValueType::fromDate),
+ TIME_MILLIS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToTimeMillis, ValueType::toTimeMillis, ValueType::fromTimeMillis),
+ TIME_MICROS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimeMicros, ValueType::toTimeMicros, ValueType::fromTimeMicros),
+ TIMESTAMP_MILLIS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMillis, ValueType::toTimestampMillis, ValueType::fromTimestampMillis),
+ TIMESTAMP_MICROS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMicros, ValueType::toTimestampMicros, ValueType::fromTimestampMicros),
+ TIMESTAMP_NANOS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampNanos, ValueType::toTimestampNanos, ValueType::fromTimestampNanos),
+ LOCAL_TIMESTAMP_MILLIS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMillis, ValueType::toLocalTimestampMillis, ValueType::fromLocalTimestampMillis),
+ LOCAL_TIMESTAMP_MICROS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMicros, ValueType::toLocalTimestampMicros, ValueType::fromLocalTimestampMicros),
+ LOCAL_TIMESTAMP_NANOS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampNanos, ValueType::toLocalTimestampNanos, ValueType::fromLocalTimestampNanos);
+
+ private final Class<?> internalType;
+ private final HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType;
+ private final BiFunction<Object, ValueMetadata, Comparable<?>> standardize;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toPrimitive;
+
+ ValueType(HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType, Function<Object, Object> single) {
+ this(primitiveWrapperType.getClazz(),
+ primitiveWrapperType,
+ (val, meta) -> (Comparable<?>) single.apply(val),
+ ValueType::passThrough,
+ ValueType::passThrough);
+ }
+
+ ValueType(Class<?> internalType,
+ HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType,
+ BiFunction<Object, ValueMetadata, Comparable<?>> standardize,
+ BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex,
+ BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toPrimitive) {
+ this.internalType = internalType;
+ this.primitiveWrapperType = primitiveWrapperType;
+ this.standardize = standardize;
+ this.toComplex = toComplex;
+ this.toPrimitive = toPrimitive;
+ }
+
+ Comparable<?> standardizeJavaTypeAndPromote(Object val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return standardize.apply(val, meta);
+ }
+
+ private Comparable<?> convertIntoPrimitive(Comparable<?> val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return toPrimitive.apply(val, meta);
+ }
+
+ private Comparable<?> convertIntoComplex(Comparable<?> val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return toComplex.apply(val, meta);
+ }
+
+ void validate(Object val) {
+ if (val == null) {
+ return;
+ }
+
+ if (!internalType.isInstance(val)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ internalType.getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ }
+
+ public Object wrapValue(Comparable<?> val, ValueMetadata meta) {
+ if (meta.getValueType() == V1) {
+ return primitiveWrapperType.wrap(val);
+ }
+
+ if (val == null) {
+ return null;
+ }
+ if (!this.internalType.isInstance(val)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ this.internalType.getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ return primitiveWrapperType.wrap(convertIntoPrimitive(val, meta));
+ }
+
+ public Comparable<?> unwrapValue(Object val, ValueMetadata meta) {
+ if (meta.getValueType() == V1) {
+ return primitiveWrapperType.unwrap(val);
+ }
+
+ if (val == null) {
+ return null;
+ }
+
+ if (!primitiveWrapperType.getWrapperClass().isInstance(val)) {
+ if (!(val instanceof GenericRecord)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ primitiveWrapperType.getWrapperClass().getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ } else if (((GenericRecord) val).getSchema().getField("value") != null) {
+ return standardizeJavaTypeAndPromote(HoodieAvroWrapperUtils.unwrapGenericRecord(val), meta);
+ } else {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ primitiveWrapperType.getWrapperClass().getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ }
+ return convertIntoComplex(primitiveWrapperType.unwrap(val), meta);
+ }
+
+ private static ValueType[] myEnumValues;
+
+ public static ValueType fromInt(int i) {
Review Comment:
```suggestion
public static ValueType fromOrdinal(int i) {
```
##########
hudi-common/src/main/java/org/apache/hudi/stats/ValueType.java:
##########
@@ -0,0 +1,668 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.avro.AvroSchemaUtils;
+import org.apache.hudi.avro.HoodieAvroWrapperUtils;
+import org.apache.hudi.common.util.DateTimeUtils;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.avro.util.Utf8;
+import org.apache.parquet.io.api.Binary;
+import org.apache.parquet.schema.LogicalTypeTokenParser;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.math.BigDecimal;
+import java.math.BigInteger;
+import java.math.MathContext;
+import java.math.RoundingMode;
+import java.nio.ByteBuffer;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.time.LocalDateTime;
+import java.time.LocalTime;
+import java.time.ZoneOffset;
+import java.util.Objects;
+import java.util.UUID;
+import java.util.function.BiFunction;
+import java.util.function.Function;
+
+import static org.apache.hudi.avro.HoodieAvroUtils.convertBytesToBigDecimal;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToMicros;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToNanos;
+import static org.apache.hudi.common.util.DateTimeUtils.microsToInstant;
+import static org.apache.hudi.common.util.DateTimeUtils.nanosToInstant;
+import static org.apache.hudi.common.util.StringUtils.getUTF8Bytes;
+
+public enum ValueType {
+ V1(HoodieAvroWrapperUtils.PrimitiveWrapperType.V1.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.V1,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ NULL(HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ BOOLEAN(HoodieAvroWrapperUtils.PrimitiveWrapperType.BOOLEAN, ValueType::castToBoolean),
+ INT(HoodieAvroWrapperUtils.PrimitiveWrapperType.INT, ValueType::castToInteger),
+ LONG(HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG, ValueType::castToLong),
+ FLOAT(HoodieAvroWrapperUtils.PrimitiveWrapperType.FLOAT, ValueType::castToFloat),
+ DOUBLE(HoodieAvroWrapperUtils.PrimitiveWrapperType.DOUBLE, ValueType::castToDouble),
+ STRING(HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING, ValueType::castToString),
+ BYTES(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToBytes),
+ FIXED(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToFixed),
+ DECIMAL(BigDecimal.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES,
+ ValueType::castToDecimal, ValueType::toDecimal, ValueType::fromDecimal),
+ UUID(UUID.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING,
+ ValueType::castToUUID, ValueType::toUUID, ValueType::fromUUID),
+ DATE(LocalDate.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToDate, ValueType::toDate, ValueType::fromDate),
+ TIME_MILLIS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToTimeMillis, ValueType::toTimeMillis, ValueType::fromTimeMillis),
+ TIME_MICROS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimeMicros, ValueType::toTimeMicros, ValueType::fromTimeMicros),
+ TIMESTAMP_MILLIS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMillis, ValueType::toTimestampMillis, ValueType::fromTimestampMillis),
+ TIMESTAMP_MICROS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMicros, ValueType::toTimestampMicros, ValueType::fromTimestampMicros),
+ TIMESTAMP_NANOS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampNanos, ValueType::toTimestampNanos, ValueType::fromTimestampNanos),
+ LOCAL_TIMESTAMP_MILLIS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMillis, ValueType::toLocalTimestampMillis, ValueType::fromLocalTimestampMillis),
+ LOCAL_TIMESTAMP_MICROS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMicros, ValueType::toLocalTimestampMicros, ValueType::fromLocalTimestampMicros),
+ LOCAL_TIMESTAMP_NANOS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampNanos, ValueType::toLocalTimestampNanos, ValueType::fromLocalTimestampNanos);
+
+ private final Class<?> internalType;
+ private final HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType;
+ private final BiFunction<Object, ValueMetadata, Comparable<?>> standardize;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toPrimitive;
+
+ ValueType(HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType, Function<Object, Object> single) {
Review Comment:
nit: what does `single` mean here?
##########
hudi-common/src/main/java/org/apache/hudi/stats/ValueType.java:
##########
@@ -0,0 +1,668 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.avro.AvroSchemaUtils;
+import org.apache.hudi.avro.HoodieAvroWrapperUtils;
+import org.apache.hudi.common.util.DateTimeUtils;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.avro.util.Utf8;
+import org.apache.parquet.io.api.Binary;
+import org.apache.parquet.schema.LogicalTypeTokenParser;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.math.BigDecimal;
+import java.math.BigInteger;
+import java.math.MathContext;
+import java.math.RoundingMode;
+import java.nio.ByteBuffer;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.time.LocalDateTime;
+import java.time.LocalTime;
+import java.time.ZoneOffset;
+import java.util.Objects;
+import java.util.UUID;
+import java.util.function.BiFunction;
+import java.util.function.Function;
+
+import static org.apache.hudi.avro.HoodieAvroUtils.convertBytesToBigDecimal;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToMicros;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToNanos;
+import static org.apache.hudi.common.util.DateTimeUtils.microsToInstant;
+import static org.apache.hudi.common.util.DateTimeUtils.nanosToInstant;
+import static org.apache.hudi.common.util.StringUtils.getUTF8Bytes;
+
+public enum ValueType {
+ V1(HoodieAvroWrapperUtils.PrimitiveWrapperType.V1.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.V1,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ NULL(HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ BOOLEAN(HoodieAvroWrapperUtils.PrimitiveWrapperType.BOOLEAN, ValueType::castToBoolean),
+ INT(HoodieAvroWrapperUtils.PrimitiveWrapperType.INT, ValueType::castToInteger),
+ LONG(HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG, ValueType::castToLong),
+ FLOAT(HoodieAvroWrapperUtils.PrimitiveWrapperType.FLOAT, ValueType::castToFloat),
+ DOUBLE(HoodieAvroWrapperUtils.PrimitiveWrapperType.DOUBLE, ValueType::castToDouble),
+ STRING(HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING, ValueType::castToString),
+ BYTES(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToBytes),
+ FIXED(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToFixed),
+ DECIMAL(BigDecimal.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES,
+ ValueType::castToDecimal, ValueType::toDecimal, ValueType::fromDecimal),
+ UUID(UUID.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING,
+ ValueType::castToUUID, ValueType::toUUID, ValueType::fromUUID),
+ DATE(LocalDate.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToDate, ValueType::toDate, ValueType::fromDate),
+ TIME_MILLIS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToTimeMillis, ValueType::toTimeMillis, ValueType::fromTimeMillis),
+ TIME_MICROS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimeMicros, ValueType::toTimeMicros, ValueType::fromTimeMicros),
+ TIMESTAMP_MILLIS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMillis, ValueType::toTimestampMillis, ValueType::fromTimestampMillis),
+ TIMESTAMP_MICROS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMicros, ValueType::toTimestampMicros, ValueType::fromTimestampMicros),
+ TIMESTAMP_NANOS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampNanos, ValueType::toTimestampNanos, ValueType::fromTimestampNanos),
+ LOCAL_TIMESTAMP_MILLIS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMillis, ValueType::toLocalTimestampMillis, ValueType::fromLocalTimestampMillis),
+ LOCAL_TIMESTAMP_MICROS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMicros, ValueType::toLocalTimestampMicros, ValueType::fromLocalTimestampMicros),
+ LOCAL_TIMESTAMP_NANOS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampNanos, ValueType::toLocalTimestampNanos, ValueType::fromLocalTimestampNanos);
+
+ private final Class<?> internalType;
+ private final HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType;
+ private final BiFunction<Object, ValueMetadata, Comparable<?>> standardize;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex;
Review Comment:
"complex" usually refers to records, arrays, maps, etc.
```suggestion
private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toLogical;
```
##########
hudi-common/src/main/java/org/apache/hudi/stats/ValueType.java:
##########
@@ -0,0 +1,668 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.avro.AvroSchemaUtils;
+import org.apache.hudi.avro.HoodieAvroWrapperUtils;
+import org.apache.hudi.common.util.DateTimeUtils;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.avro.util.Utf8;
+import org.apache.parquet.io.api.Binary;
+import org.apache.parquet.schema.LogicalTypeTokenParser;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.math.BigDecimal;
+import java.math.BigInteger;
+import java.math.MathContext;
+import java.math.RoundingMode;
+import java.nio.ByteBuffer;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.time.LocalDateTime;
+import java.time.LocalTime;
+import java.time.ZoneOffset;
+import java.util.Objects;
+import java.util.UUID;
+import java.util.function.BiFunction;
+import java.util.function.Function;
+
+import static org.apache.hudi.avro.HoodieAvroUtils.convertBytesToBigDecimal;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToMicros;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToNanos;
+import static org.apache.hudi.common.util.DateTimeUtils.microsToInstant;
+import static org.apache.hudi.common.util.DateTimeUtils.nanosToInstant;
+import static org.apache.hudi.common.util.StringUtils.getUTF8Bytes;
+
+public enum ValueType {
+ V1(HoodieAvroWrapperUtils.PrimitiveWrapperType.V1.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.V1,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ NULL(HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ BOOLEAN(HoodieAvroWrapperUtils.PrimitiveWrapperType.BOOLEAN, ValueType::castToBoolean),
+ INT(HoodieAvroWrapperUtils.PrimitiveWrapperType.INT, ValueType::castToInteger),
+ LONG(HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG, ValueType::castToLong),
+ FLOAT(HoodieAvroWrapperUtils.PrimitiveWrapperType.FLOAT, ValueType::castToFloat),
+ DOUBLE(HoodieAvroWrapperUtils.PrimitiveWrapperType.DOUBLE, ValueType::castToDouble),
+ STRING(HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING, ValueType::castToString),
+ BYTES(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToBytes),
+ FIXED(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToFixed),
+ DECIMAL(BigDecimal.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES,
+ ValueType::castToDecimal, ValueType::toDecimal, ValueType::fromDecimal),
+ UUID(UUID.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING,
+ ValueType::castToUUID, ValueType::toUUID, ValueType::fromUUID),
+ DATE(LocalDate.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToDate, ValueType::toDate, ValueType::fromDate),
+ TIME_MILLIS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToTimeMillis, ValueType::toTimeMillis, ValueType::fromTimeMillis),
+ TIME_MICROS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimeMicros, ValueType::toTimeMicros, ValueType::fromTimeMicros),
+ TIMESTAMP_MILLIS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMillis, ValueType::toTimestampMillis, ValueType::fromTimestampMillis),
+ TIMESTAMP_MICROS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMicros, ValueType::toTimestampMicros, ValueType::fromTimestampMicros),
+ TIMESTAMP_NANOS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampNanos, ValueType::toTimestampNanos, ValueType::fromTimestampNanos),
+ LOCAL_TIMESTAMP_MILLIS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMillis, ValueType::toLocalTimestampMillis, ValueType::fromLocalTimestampMillis),
+ LOCAL_TIMESTAMP_MICROS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMicros, ValueType::toLocalTimestampMicros, ValueType::fromLocalTimestampMicros),
+ LOCAL_TIMESTAMP_NANOS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampNanos, ValueType::toLocalTimestampNanos, ValueType::fromLocalTimestampNanos);
+
+ private final Class<?> internalType;
+ private final HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType;
+ private final BiFunction<Object, ValueMetadata, Comparable<?>> standardize;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toPrimitive;
+
+ ValueType(HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType, Function<Object, Object> single) {
+ this(primitiveWrapperType.getClazz(),
+ primitiveWrapperType,
+ (val, meta) -> (Comparable<?>) single.apply(val),
+ ValueType::passThrough,
+ ValueType::passThrough);
+ }
+
+ ValueType(Class<?> internalType,
+ HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType,
+ BiFunction<Object, ValueMetadata, Comparable<?>> standardize,
+ BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex,
+ BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toPrimitive) {
+ this.internalType = internalType;
+ this.primitiveWrapperType = primitiveWrapperType;
+ this.standardize = standardize;
+ this.toComplex = toComplex;
+ this.toPrimitive = toPrimitive;
+ }
+
+ Comparable<?> standardizeJavaTypeAndPromote(Object val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return standardize.apply(val, meta);
+ }
+
+ private Comparable<?> convertIntoPrimitive(Comparable<?> val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return toPrimitive.apply(val, meta);
+ }
+
+ private Comparable<?> convertIntoComplex(Comparable<?> val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return toComplex.apply(val, meta);
+ }
+
+ void validate(Object val) {
+ if (val == null) {
+ return;
+ }
+
+ if (!internalType.isInstance(val)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ internalType.getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ }
+
+ public Object wrapValue(Comparable<?> val, ValueMetadata meta) {
+ if (meta.getValueType() == V1) {
+ return primitiveWrapperType.wrap(val);
+ }
+
+ if (val == null) {
+ return null;
+ }
+ if (!this.internalType.isInstance(val)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ this.internalType.getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ return primitiveWrapperType.wrap(convertIntoPrimitive(val, meta));
+ }
+
+ public Comparable<?> unwrapValue(Object val, ValueMetadata meta) {
+ if (meta.getValueType() == V1) {
+ return primitiveWrapperType.unwrap(val);
+ }
+
+ if (val == null) {
+ return null;
+ }
+
+ if (!primitiveWrapperType.getWrapperClass().isInstance(val)) {
+ if (!(val instanceof GenericRecord)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ primitiveWrapperType.getWrapperClass().getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ } else if (((GenericRecord) val).getSchema().getField("value") != null) {
+ return standardizeJavaTypeAndPromote(HoodieAvroWrapperUtils.unwrapGenericRecord(val), meta);
+ } else {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ primitiveWrapperType.getWrapperClass().getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ }
+ return convertIntoComplex(primitiveWrapperType.unwrap(val), meta);
+ }
+
+ private static ValueType[] myEnumValues;
+
+ public static ValueType fromInt(int i) {
+ if (ValueType.myEnumValues == null) {
+ ValueType.myEnumValues = ValueType.values();
+ }
+ return ValueType.myEnumValues[i];
+ }
+
+ public static ValueType fromPrimitiveType(PrimitiveType primitiveType) {
+ if (primitiveType.getLogicalTypeAnnotation() != null) {
+ return LogicalTypeTokenParser.fromLogicalTypeAnnotation(primitiveType);
+ }
+ switch (primitiveType.getPrimitiveTypeName()) {
+ case INT64:
+ return ValueType.LONG;
+ case INT32:
+ return ValueType.INT;
+ case BOOLEAN:
+ return ValueType.BOOLEAN;
+ case BINARY:
+ return ValueType.BYTES;
+ case FLOAT:
+ return ValueType.FLOAT;
+ case DOUBLE:
+ return ValueType.DOUBLE;
+ case INT96:
+ // TODO: probably wrong
+ return ValueType.DECIMAL;
Review Comment:
I'm not sure if INT96 is supported; I think Spark has deprecated writing INT96 in Parquet.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3293487750
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3309036438
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
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URL: https://github.com/apache/hudi/pull/13711#issuecomment-3310435107
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2359677720
##########
hudi-common/src/main/java/org/apache/hudi/stats/ValueType.java:
##########
@@ -0,0 +1,668 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.avro.AvroSchemaUtils;
+import org.apache.hudi.avro.HoodieAvroWrapperUtils;
+import org.apache.hudi.common.util.DateTimeUtils;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.avro.util.Utf8;
+import org.apache.parquet.io.api.Binary;
+import org.apache.parquet.schema.LogicalTypeTokenParser;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.math.BigDecimal;
+import java.math.BigInteger;
+import java.math.MathContext;
+import java.math.RoundingMode;
+import java.nio.ByteBuffer;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.time.LocalDateTime;
+import java.time.LocalTime;
+import java.time.ZoneOffset;
+import java.util.Objects;
+import java.util.UUID;
+import java.util.function.BiFunction;
+import java.util.function.Function;
+
+import static org.apache.hudi.avro.HoodieAvroUtils.convertBytesToBigDecimal;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToMicros;
+import static org.apache.hudi.common.util.DateTimeUtils.instantToNanos;
+import static org.apache.hudi.common.util.DateTimeUtils.microsToInstant;
+import static org.apache.hudi.common.util.DateTimeUtils.nanosToInstant;
+import static org.apache.hudi.common.util.StringUtils.getUTF8Bytes;
+
+public enum ValueType {
+ V1(HoodieAvroWrapperUtils.PrimitiveWrapperType.V1.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.V1,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ NULL(HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL.getClazz(), HoodieAvroWrapperUtils.PrimitiveWrapperType.NULL,
+ ValueType::passThrough, ValueType::passThrough, ValueType::passThrough),
+ BOOLEAN(HoodieAvroWrapperUtils.PrimitiveWrapperType.BOOLEAN, ValueType::castToBoolean),
+ INT(HoodieAvroWrapperUtils.PrimitiveWrapperType.INT, ValueType::castToInteger),
+ LONG(HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG, ValueType::castToLong),
+ FLOAT(HoodieAvroWrapperUtils.PrimitiveWrapperType.FLOAT, ValueType::castToFloat),
+ DOUBLE(HoodieAvroWrapperUtils.PrimitiveWrapperType.DOUBLE, ValueType::castToDouble),
+ STRING(HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING, ValueType::castToString),
+ BYTES(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToBytes),
+ FIXED(HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES, ValueType::castToFixed),
+ DECIMAL(BigDecimal.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.BYTES,
+ ValueType::castToDecimal, ValueType::toDecimal, ValueType::fromDecimal),
+ UUID(UUID.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.STRING,
+ ValueType::castToUUID, ValueType::toUUID, ValueType::fromUUID),
+ DATE(LocalDate.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToDate, ValueType::toDate, ValueType::fromDate),
+ TIME_MILLIS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.INT,
+ ValueType::castToTimeMillis, ValueType::toTimeMillis, ValueType::fromTimeMillis),
+ TIME_MICROS(LocalTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimeMicros, ValueType::toTimeMicros, ValueType::fromTimeMicros),
+ TIMESTAMP_MILLIS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMillis, ValueType::toTimestampMillis, ValueType::fromTimestampMillis),
+ TIMESTAMP_MICROS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampMicros, ValueType::toTimestampMicros, ValueType::fromTimestampMicros),
+ TIMESTAMP_NANOS(Instant.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToTimestampNanos, ValueType::toTimestampNanos, ValueType::fromTimestampNanos),
+ LOCAL_TIMESTAMP_MILLIS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMillis, ValueType::toLocalTimestampMillis, ValueType::fromLocalTimestampMillis),
+ LOCAL_TIMESTAMP_MICROS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampMicros, ValueType::toLocalTimestampMicros, ValueType::fromLocalTimestampMicros),
+ LOCAL_TIMESTAMP_NANOS(LocalDateTime.class, HoodieAvroWrapperUtils.PrimitiveWrapperType.LONG,
+ ValueType::castToLocalTimestampNanos, ValueType::toLocalTimestampNanos, ValueType::fromLocalTimestampNanos);
+
+ private final Class<?> internalType;
+ private final HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType;
+ private final BiFunction<Object, ValueMetadata, Comparable<?>> standardize;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex;
+ private final BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toPrimitive;
+
+ ValueType(HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType, Function<Object, Object> single) {
+ this(primitiveWrapperType.getClazz(),
+ primitiveWrapperType,
+ (val, meta) -> (Comparable<?>) single.apply(val),
+ ValueType::passThrough,
+ ValueType::passThrough);
+ }
+
+ ValueType(Class<?> internalType,
+ HoodieAvroWrapperUtils.PrimitiveWrapperType primitiveWrapperType,
+ BiFunction<Object, ValueMetadata, Comparable<?>> standardize,
+ BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toComplex,
+ BiFunction<Comparable<?>, ValueMetadata, Comparable<?>> toPrimitive) {
+ this.internalType = internalType;
+ this.primitiveWrapperType = primitiveWrapperType;
+ this.standardize = standardize;
+ this.toComplex = toComplex;
+ this.toPrimitive = toPrimitive;
+ }
+
+ Comparable<?> standardizeJavaTypeAndPromote(Object val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return standardize.apply(val, meta);
+ }
+
+ private Comparable<?> convertIntoPrimitive(Comparable<?> val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return toPrimitive.apply(val, meta);
+ }
+
+ private Comparable<?> convertIntoComplex(Comparable<?> val, ValueMetadata meta) {
+ if (val == null) {
+ return null;
+ }
+ return toComplex.apply(val, meta);
+ }
+
+ void validate(Object val) {
+ if (val == null) {
+ return;
+ }
+
+ if (!internalType.isInstance(val)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ internalType.getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ }
+
+ public Object wrapValue(Comparable<?> val, ValueMetadata meta) {
+ if (meta.getValueType() == V1) {
+ return primitiveWrapperType.wrap(val);
+ }
+
+ if (val == null) {
+ return null;
+ }
+ if (!this.internalType.isInstance(val)) {
+ throw new IllegalArgumentException(String.format(
+ "should be %s, but got %s",
+ this.internalType.getSimpleName(),
+ val.getClass().getSimpleName()
+ ));
+ }
+ return primitiveWrapperType.wrap(convertIntoPrimitive(val, meta));
+ }
+
+ public Comparable<?> unwrapValue(Object val, ValueMetadata meta) {
+ if (meta.getValueType() == V1) {
+ return primitiveWrapperType.unwrap(val);
Review Comment:
I see, so `PrimitiveWrapperType.V1` handles logical types. I got confused because of the naming.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2359684736
##########
hudi-utilities/src/test/resources/streamer-config/source-timestamp-millis.avsc:
##########
@@ -0,0 +1,162 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+{
+ "type" : "record",
+ "name" : "triprec",
+ "fields" : [
+ {
+ "name": "timestamp",
+ "type": "long"
+ },
+ {
+ "name": "_row_key",
+ "type": "string"
+ },
+ {
+ "name": "partition_path",
+ "type": "string"
+ },
+ {
+ "name": "trip_type",
+ "type": {
+ "type": "enum",
+ "name": "TripType",
+ "symbols": [
+ "UNKNOWN",
+ "UBERX",
+ "BLACK"
+ ],
+ "default": "UNKNOWN"
+ }
+ },
+ {
+ "name": "rider",
+ "type": "string"
+ },
+ {
+ "name": "driver",
+ "type": "string"
+ },
+ {
+ "name": "begin_lat",
+ "type": "double"
+ },
+ {
+ "name": "begin_lon",
+ "type": "double"
+ },
+ {
+ "name": "end_lat",
+ "type": "double"
+ },
+ {
+ "name": "end_lon",
+ "type": "double"
+ },
+ {
+ "name": "distance_in_meters",
+ "type": "int"
+ },
+ {
+ "name": "seconds_since_epoch",
+ "type": "long"
+ },
+ {
+ "name": "weight",
+ "type": "float"
+ },
+ {
+ "name": "nation",
+ "type": "bytes"
+ },
+ {
+ "name": "current_date",
+ "type": {
+ "type": "int",
+ "logicalType": "date"
+ }
+ },
+ {
+ "name": "current_ts",
+ "type": {
+ "type": "long",
+ "logicalType": "timestamp-millis"
Review Comment:
Sg
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3305426326
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2370835662
##########
hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/HoodieFileGroupReaderBasedFileFormat.scala:
##########
@@ -192,9 +195,12 @@ class HoodieFileGroupReaderBasedFileFormat(tablePath: String,
val fixedPartitionIndexes = fixedPartitionIndexesArr.toSet
// schema that we want fg reader to output to us
+ val exclusionFields = new java.util.HashSet[String]()
+ exclusionFields.add("op")
+ partitionSchema.fields.foreach(f => exclusionFields.add(f.name))
val requestedSchema = StructType(requiredSchema.fields ++ partitionSchema.fields.filter(f => mandatoryFields.contains(f.name)))
- val requestedAvroSchema = AvroConversionUtils.convertStructTypeToAvroSchema(requestedSchema, sanitizedTableName)
- val dataAvroSchema = AvroConversionUtils.convertStructTypeToAvroSchema(dataSchema, sanitizedTableName)
+ val requestedAvroSchema = AvroSchemaUtils.pruneDataSchema(avroTableSchema, AvroConversionUtils.convertStructTypeToAvroSchema(requestedSchema, sanitizedTableName), exclusionFields)
+ val dataAvroSchema = AvroSchemaUtils.pruneDataSchema(avroTableSchema, AvroConversionUtils.convertStructTypeToAvroSchema(dataSchema, sanitizedTableName), exclusionFields)
Review Comment:
Yeah I think this should probably be passed through by the hadoopfsrelationfactory
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3321441701
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2370696705
##########
hudi-common/src/main/java/org/apache/hudi/stats/ValueMetadata.java:
##########
@@ -0,0 +1,254 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.ParquetAdapter;
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.Pair;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.io.Serializable;
+
+import static org.apache.hudi.avro.AvroSchemaUtils.resolveNullableSchema;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE_ADDITIONAL_INFO;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE_ORDINAL;
+
+/**
+ * Holder for VaueType and additional info
+ * Used for wrapping and unwrapping col stat values
+ * as well as for type promotion
+ */
+public class ValueMetadata implements Serializable {
+
+ private static final ParquetAdapter PARQUET_ADAPTER = ParquetAdapter.getAdapter();
+
+ private final ValueType valueType;
+
+ protected ValueMetadata(ValueType valueType) {
+ this.valueType = valueType;
+ }
+
+ public ValueType getValueType() {
+ return valueType;
+ }
+
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ return HoodieValueTypeInfo.newBuilder()
+ .setTypeOrdinal(valueType.ordinal())
+ .setAdditionalInfo(getAdditionalInfo())
+ .build();
+ }
+
+ String getAdditionalInfo() {
+ return null;
+ }
+
+ public Comparable<?> standardizeJavaTypeAndPromote(Object val) {
+ return this.getValueType().standardizeJavaTypeAndPromote(val, this);
+ }
+
+ public Object wrapValue(Comparable<?> value) {
+ return this.getValueType().wrapValue(value, this);
+ }
+
+ public Comparable<?> unwrapValue(Object value) {
+ return this.getValueType().unwrapValue(value, this);
+ }
+
+ public void validate(Object minVal, Object maxVal) {
+ if (getValueType() == ValueType.V1) {
+ return;
+ }
+ this.getValueType().validate(minVal);
+ this.getValueType().validate(maxVal);
+ }
+
+ public boolean isV1() {
+ return this.getValueType() == ValueType.V1;
+ }
+
+ public static class V1EmptyMetadata extends ValueMetadata {
+ private static final V1EmptyMetadata V1_EMPTY_METADATA = new V1EmptyMetadata();
+ public static V1EmptyMetadata get() {
+ return V1_EMPTY_METADATA;
+ }
+
+ private V1EmptyMetadata() {
+ super(ValueType.V1);
+ }
+
+ @Override
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ // V1 should never be persisted to the MDT. It is only for in memory
+ return null;
+ }
+ }
+
+ public static final ValueMetadata NULL_METADATA = new ValueMetadata(ValueType.NULL);
+
+ interface DecimalValueMetadata {
+
+ int getPrecision();
+
+ int getScale();
+
+ static String encodeData(DecimalValueMetadata decimalValueMetadata) {
+ return String.format("%d,%d", decimalValueMetadata.getPrecision(), decimalValueMetadata.getScale());
+ }
+
+ static Pair<Integer, Integer> decodeData(String data) {
+ //TODO: decide if we want to store things in a better way
+ String[] splits = data.split(",");
+ return Pair.of(Integer.parseInt(splits[0]), Integer.parseInt(splits[1]));
+ }
+ }
+
+ static class DecimalMetadata extends ValueMetadata implements DecimalValueMetadata {
+
+ static DecimalMetadata create(String additionalInfo) {
+ if (additionalInfo == null) {
+ throw new IllegalArgumentException("additionalInfo cannot be null");
+ }
+ Pair<Integer, Integer> data = DecimalValueMetadata.decodeData(additionalInfo);
+ return new DecimalMetadata(data.getLeft(), data.getRight());
+ }
+
+ static DecimalMetadata create(LogicalTypes.Decimal decimal) {
+ return new DecimalMetadata(decimal.getPrecision(), decimal.getScale());
+ }
+
+ static DecimalMetadata create(PrimitiveType primitiveType) {
+ return new DecimalMetadata(PARQUET_ADAPTER.getPrecision(primitiveType), PARQUET_ADAPTER.getScale(primitiveType));
+ }
+
+ static DecimalMetadata create(int precision, int scale) {
+ return new DecimalMetadata(precision, scale);
+ }
+
+ private final int precision;
+ private final int scale;
+
+ private DecimalMetadata(int precision, int scale) {
+ super(ValueType.DECIMAL);
+ this.precision = precision;
+ this.scale = scale;
+ }
+
+ @Override
+ public int getPrecision() {
+ return precision;
+ }
+
+ @Override
+ public int getScale() {
+ return scale;
+ }
+
+ @Override
+ String getAdditionalInfo() {
+ return DecimalValueMetadata.encodeData(this);
+ }
+ }
+
+ public static ValueMetadata getEmptyValueMetadata(HoodieIndexVersion indexVersion) {
+ if (indexVersion.lowerThan(HoodieIndexVersion.V2)) {
+ return V1EmptyMetadata.get();
+ }
+ return NULL_METADATA;
+ }
+
+ public static ValueMetadata getValueMetadata(HoodieValueTypeInfo valueTypeInfo) {
+ // valueTypeInfo will always be null when version is v1
+ if (valueTypeInfo == null) {
+ return V1EmptyMetadata.get();
+ }
+
+ ValueType valueType = ValueType.fromOrdinal(valueTypeInfo.getTypeOrdinal());
+ if (valueType == ValueType.V1) {
+ return V1EmptyMetadata.get();
+ } else if (valueType == ValueType.DECIMAL) {
+ return DecimalMetadata.create(valueTypeInfo.getAdditionalInfo());
+ } else {
+ return new ValueMetadata(valueType);
+ }
+ }
+
+ public static ValueMetadata getValueMetadata(GenericRecord columnStatsRecord) {
+ if (columnStatsRecord == null) {
+ // TODO: Should we return V1EmptyMetadata here?
+ return NULL_METADATA;
Review Comment:
Is this only used for computation only, i.e., reading from storage bits for processing?
##########
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/hudi/functional/TestPartitionStatsPruning.scala:
##########
@@ -57,6 +56,7 @@ class TestPartitionStatsPruning extends ColumnStatIndexTestBase {
"hoodie.upsert.shuffle.parallelism" -> "4",
HoodieWriteConfig.TBL_NAME.key -> "hoodie_test",
DataSourceWriteOptions.TABLE_TYPE.key -> testCase.tableType.toString,
+ HoodieWriteConfig.WRITE_TABLE_VERSION.key() -> testCase.tableVersion.toString,
Review Comment:
Reminder on this
##########
hudi-common/src/test/java/org/apache/hudi/common/testutils/HoodieTestDataGenerator.java:
##########
@@ -151,6 +154,30 @@ public class HoodieTestDataGenerator implements AutoCloseable {
+ "{\"name\":\"current_ts\",\"type\": {\"type\": \"long\"}},"
+ "{\"name\":\"height\",\"type\":{\"type\":\"fixed\",\"name\":\"abc\",\"size\":5,\"logicalType\":\"decimal\",\"precision\":10,\"scale\":6}},";
+ public static final String EXTENDED_LOGICAL_TYPES_SCHEMA_V6 = "{\"name\":\"ts_millis\",\"type\":{\"type\":\"long\",\"logicalType\":\"timestamp-millis\"}},"
+ + "{\"name\":\"ts_micros\",\"type\":{\"type\":\"long\",\"logicalType\":\"timestamp-micros\"}},"
+ + "{\"name\":\"local_ts_millis\",\"type\":{\"type\":\"long\",\"logicalType\":\"local-timestamp-millis\"}},"
+ + "{\"name\":\"local_ts_micros\",\"type\":{\"type\":\"long\",\"logicalType\":\"local-timestamp-micros\"}},"
+ + "{\"name\":\"event_date\",\"type\":{\"type\":\"int\",\"logicalType\":\"date\"}},"
+ + "{\"name\":\"dec_fixed_small\",\"type\":{\"type\":\"fixed\",\"name\":\"decFixedSmall\",\"size\":3,\"logicalType\":\"decimal\",\"precision\":5,\"scale\":2}},"
+ + "{\"name\":\"dec_fixed_large\",\"type\":{\"type\":\"fixed\",\"name\":\"decFixedLarge\",\"size\":8,\"logicalType\":\"decimal\",\"precision\":18,\"scale\":9}},";
+
+ public static final String EXTENDED_LOGICAL_TYPES_SCHEMA = "{\"name\":\"ts_millis\",\"type\":{\"type\":\"long\",\"logicalType\":\"timestamp-millis\"}},"
+ + "{\"name\":\"ts_micros\",\"type\":{\"type\":\"long\",\"logicalType\":\"timestamp-micros\"}},"
+ + "{\"name\":\"local_ts_millis\",\"type\":{\"type\":\"long\",\"logicalType\":\"local-timestamp-millis\"}},"
+ + "{\"name\":\"local_ts_micros\",\"type\":{\"type\":\"long\",\"logicalType\":\"local-timestamp-micros\"}},"
+ + "{\"name\":\"event_date\",\"type\":{\"type\":\"int\",\"logicalType\":\"date\"}},"
+ + "{\"name\":\"dec_plain_large\",\"type\":{\"type\":\"bytes\",\"logicalType\":\"decimal\",\"precision\":20,\"scale\":10}},"
+ + "{\"name\":\"dec_fixed_small\",\"type\":{\"type\":\"fixed\",\"name\":\"decFixedSmall\",\"size\":3,\"logicalType\":\"decimal\",\"precision\":5,\"scale\":2}},"
+ + "{\"name\":\"dec_fixed_large\",\"type\":{\"type\":\"fixed\",\"name\":\"decFixedLarge\",\"size\":8,\"logicalType\":\"decimal\",\"precision\":18,\"scale\":9}},";
+
+ public static final String EXTENDED_LOGICAL_TYPES_SCHEMA_NO_LTS = "{\"name\":\"ts_millis\",\"type\":{\"type\":\"long\",\"logicalType\":\"timestamp-millis\"}},"
Review Comment:
nit: add comment on what `LTS` is
##########
hudi-common/src/main/java/org/apache/hudi/stats/ValueMetadata.java:
##########
@@ -0,0 +1,254 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.ParquetAdapter;
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.Pair;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.io.Serializable;
+
+import static org.apache.hudi.avro.AvroSchemaUtils.resolveNullableSchema;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE_ADDITIONAL_INFO;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE_ORDINAL;
+
+/**
+ * Holder for VaueType and additional info
+ * Used for wrapping and unwrapping col stat values
+ * as well as for type promotion
+ */
+public class ValueMetadata implements Serializable {
+
+ private static final ParquetAdapter PARQUET_ADAPTER = ParquetAdapter.getAdapter();
+
+ private final ValueType valueType;
+
+ protected ValueMetadata(ValueType valueType) {
+ this.valueType = valueType;
+ }
+
+ public ValueType getValueType() {
+ return valueType;
+ }
+
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ return HoodieValueTypeInfo.newBuilder()
+ .setTypeOrdinal(valueType.ordinal())
+ .setAdditionalInfo(getAdditionalInfo())
+ .build();
+ }
+
+ String getAdditionalInfo() {
+ return null;
+ }
+
+ public Comparable<?> standardizeJavaTypeAndPromote(Object val) {
+ return this.getValueType().standardizeJavaTypeAndPromote(val, this);
+ }
+
+ public Object wrapValue(Comparable<?> value) {
+ return this.getValueType().wrapValue(value, this);
+ }
+
+ public Comparable<?> unwrapValue(Object value) {
+ return this.getValueType().unwrapValue(value, this);
+ }
+
+ public void validate(Object minVal, Object maxVal) {
+ if (getValueType() == ValueType.V1) {
+ return;
+ }
+ this.getValueType().validate(minVal);
+ this.getValueType().validate(maxVal);
+ }
+
+ public boolean isV1() {
+ return this.getValueType() == ValueType.V1;
+ }
+
+ public static class V1EmptyMetadata extends ValueMetadata {
+ private static final V1EmptyMetadata V1_EMPTY_METADATA = new V1EmptyMetadata();
+ public static V1EmptyMetadata get() {
+ return V1_EMPTY_METADATA;
+ }
+
+ private V1EmptyMetadata() {
+ super(ValueType.V1);
+ }
+
+ @Override
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ // V1 should never be persisted to the MDT. It is only for in memory
+ return null;
+ }
+ }
+
+ public static final ValueMetadata NULL_METADATA = new ValueMetadata(ValueType.NULL);
+
+ interface DecimalValueMetadata {
+
+ int getPrecision();
+
+ int getScale();
+
+ static String encodeData(DecimalValueMetadata decimalValueMetadata) {
+ return String.format("%d,%d", decimalValueMetadata.getPrecision(), decimalValueMetadata.getScale());
+ }
+
+ static Pair<Integer, Integer> decodeData(String data) {
+ //TODO: decide if we want to store things in a better way
+ String[] splits = data.split(",");
+ return Pair.of(Integer.parseInt(splits[0]), Integer.parseInt(splits[1]));
+ }
+ }
+
+ static class DecimalMetadata extends ValueMetadata implements DecimalValueMetadata {
+
+ static DecimalMetadata create(String additionalInfo) {
+ if (additionalInfo == null) {
+ throw new IllegalArgumentException("additionalInfo cannot be null");
+ }
+ Pair<Integer, Integer> data = DecimalValueMetadata.decodeData(additionalInfo);
+ return new DecimalMetadata(data.getLeft(), data.getRight());
+ }
+
+ static DecimalMetadata create(LogicalTypes.Decimal decimal) {
+ return new DecimalMetadata(decimal.getPrecision(), decimal.getScale());
+ }
+
+ static DecimalMetadata create(PrimitiveType primitiveType) {
+ return new DecimalMetadata(PARQUET_ADAPTER.getPrecision(primitiveType), PARQUET_ADAPTER.getScale(primitiveType));
+ }
+
+ static DecimalMetadata create(int precision, int scale) {
+ return new DecimalMetadata(precision, scale);
+ }
+
+ private final int precision;
+ private final int scale;
+
+ private DecimalMetadata(int precision, int scale) {
+ super(ValueType.DECIMAL);
+ this.precision = precision;
+ this.scale = scale;
+ }
+
+ @Override
+ public int getPrecision() {
+ return precision;
+ }
+
+ @Override
+ public int getScale() {
+ return scale;
+ }
+
+ @Override
+ String getAdditionalInfo() {
+ return DecimalValueMetadata.encodeData(this);
+ }
+ }
+
+ public static ValueMetadata getEmptyValueMetadata(HoodieIndexVersion indexVersion) {
+ if (indexVersion.lowerThan(HoodieIndexVersion.V2)) {
+ return V1EmptyMetadata.get();
+ }
+ return NULL_METADATA;
+ }
+
+ public static ValueMetadata getValueMetadata(HoodieValueTypeInfo valueTypeInfo) {
+ // valueTypeInfo will always be null when version is v1
+ if (valueTypeInfo == null) {
+ return V1EmptyMetadata.get();
+ }
+
+ ValueType valueType = ValueType.fromOrdinal(valueTypeInfo.getTypeOrdinal());
+ if (valueType == ValueType.V1) {
+ return V1EmptyMetadata.get();
+ } else if (valueType == ValueType.DECIMAL) {
+ return DecimalMetadata.create(valueTypeInfo.getAdditionalInfo());
+ } else {
+ return new ValueMetadata(valueType);
+ }
+ }
+
+ public static ValueMetadata getValueMetadata(GenericRecord columnStatsRecord) {
+ if (columnStatsRecord == null) {
+ // TODO: Should we return V1EmptyMetadata here?
+ return NULL_METADATA;
Review Comment:
Remove TODO once decided
##########
hudi-common/src/main/java/org/apache/hudi/stats/ValueMetadata.java:
##########
@@ -0,0 +1,242 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.Pair;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.parquet.schema.LogicalTypeTokenParser;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.io.Serializable;
+
+import static org.apache.hudi.avro.AvroSchemaUtils.resolveNullableSchema;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE_ADDITIONAL_INFO;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE_ORDINAL;
+
+public class ValueMetadata implements Serializable {
+ private final ValueType valueType;
+
+ protected ValueMetadata(ValueType valueType) {
+ this.valueType = valueType;
+ }
+
+ public ValueType getValueType() {
+ return valueType;
+ }
+
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ return HoodieValueTypeInfo.newBuilder()
+ .setTypeOrdinal(valueType.ordinal())
+ .setAdditionalInfo(getAdditionalInfo())
+ .build();
+ }
+
+ public String getAdditionalInfo() {
+ return null;
+ }
+
+ public Comparable<?> standardizeJavaTypeAndPromote(Object val) {
+ return this.getValueType().standardizeJavaTypeAndPromote(val, this);
+ }
+
+ public Object wrapValue(Comparable<?> value) {
+ return this.getValueType().wrapValue(value, this);
+ }
+
+ public Comparable<?> unwrapValue(Object value) {
+ return this.getValueType().unwrapValue(value, this);
+ }
+
+ public void validate(Object minVal, Object maxVal) {
+ if (getValueType() == ValueType.V1) {
+ return;
+ }
+ this.getValueType().validate(minVal);
+ this.getValueType().validate(maxVal);
+ }
+
+ public static class V1EmptyMetadata extends ValueMetadata {
+ private static final V1EmptyMetadata V_1_EMPTY_METADATA = new V1EmptyMetadata();
+ public static V1EmptyMetadata get() {
+ return V_1_EMPTY_METADATA;
+ }
+
+ private V1EmptyMetadata() {
+ super(ValueType.V1);
+ }
+
+ @Override
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ // V1 should never be persisted to the MDT. It is only for in memory
+ return null;
+ }
+ }
+
+ public static final ValueMetadata NULL_METADATA = new ValueMetadata(ValueType.NULL);
+
+ public interface DecimalValueMetadata {
+
+ int getPrecision();
+
+ int getScale();
+
+ static String encodeData(DecimalValueMetadata decimalValueMetadata) {
+ return String.format("%d,%d", decimalValueMetadata.getPrecision(), decimalValueMetadata.getScale());
+ }
+
+ static Pair<Integer, Integer> decodeData(String data) {
+ //TODO: decide if we want to store things in a better way
+ String[] splits = data.split(",");
+ return Pair.of(Integer.parseInt(splits[0]), Integer.parseInt(splits[1]));
Review Comment:
Reminder on this
##########
hudi-common/src/main/java/org/apache/hudi/stats/ValueMetadata.java:
##########
@@ -0,0 +1,254 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.stats;
+
+import org.apache.hudi.ParquetAdapter;
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.Pair;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.avro.LogicalTypes;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.parquet.schema.PrimitiveType;
+
+import java.io.Serializable;
+
+import static org.apache.hudi.avro.AvroSchemaUtils.resolveNullableSchema;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE_ADDITIONAL_INFO;
+import static org.apache.hudi.metadata.HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_TYPE_ORDINAL;
+
+/**
+ * Holder for VaueType and additional info
+ * Used for wrapping and unwrapping col stat values
+ * as well as for type promotion
+ */
+public class ValueMetadata implements Serializable {
+
+ private static final ParquetAdapter PARQUET_ADAPTER = ParquetAdapter.getAdapter();
+
+ private final ValueType valueType;
+
+ protected ValueMetadata(ValueType valueType) {
+ this.valueType = valueType;
+ }
+
+ public ValueType getValueType() {
+ return valueType;
+ }
+
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ return HoodieValueTypeInfo.newBuilder()
+ .setTypeOrdinal(valueType.ordinal())
+ .setAdditionalInfo(getAdditionalInfo())
+ .build();
+ }
+
+ String getAdditionalInfo() {
+ return null;
+ }
+
+ public Comparable<?> standardizeJavaTypeAndPromote(Object val) {
+ return this.getValueType().standardizeJavaTypeAndPromote(val, this);
+ }
+
+ public Object wrapValue(Comparable<?> value) {
+ return this.getValueType().wrapValue(value, this);
+ }
+
+ public Comparable<?> unwrapValue(Object value) {
+ return this.getValueType().unwrapValue(value, this);
+ }
+
+ public void validate(Object minVal, Object maxVal) {
+ if (getValueType() == ValueType.V1) {
+ return;
+ }
+ this.getValueType().validate(minVal);
+ this.getValueType().validate(maxVal);
+ }
+
+ public boolean isV1() {
+ return this.getValueType() == ValueType.V1;
+ }
+
+ public static class V1EmptyMetadata extends ValueMetadata {
+ private static final V1EmptyMetadata V1_EMPTY_METADATA = new V1EmptyMetadata();
+ public static V1EmptyMetadata get() {
+ return V1_EMPTY_METADATA;
+ }
+
+ private V1EmptyMetadata() {
+ super(ValueType.V1);
+ }
+
+ @Override
+ public HoodieValueTypeInfo getValueTypeInfo() {
+ // V1 should never be persisted to the MDT. It is only for in memory
+ return null;
+ }
+ }
+
+ public static final ValueMetadata NULL_METADATA = new ValueMetadata(ValueType.NULL);
+
+ interface DecimalValueMetadata {
+
+ int getPrecision();
+
+ int getScale();
+
+ static String encodeData(DecimalValueMetadata decimalValueMetadata) {
+ return String.format("%d,%d", decimalValueMetadata.getPrecision(), decimalValueMetadata.getScale());
+ }
+
+ static Pair<Integer, Integer> decodeData(String data) {
+ //TODO: decide if we want to store things in a better way
Review Comment:
Remove TODO
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3320047310
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3259462576
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## CI report:
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3259458759
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3267641881
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3185533810
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* 7089c121f35cf1e233e6c9028efd1e36900b83df Azure: [FAILURE](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=7786)
* 7d221fb01d3382117f1be7139b1d4d02ff8c155c UNKNOWN
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* 5c34d1a43ba08f81212c25ec0a26e3900285c359 Azure: [PENDING](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=7788)
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3189829547
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## CI report:
* 7d221fb01d3382117f1be7139b1d4d02ff8c155c UNKNOWN
* a852c2ac4a43bf15dc0678fd822bc0a31e403d2c UNKNOWN
* 714e47eb6dcc8aee75a2e4de69a751b2014c7ceb UNKNOWN
* b0c0c7fb945210c0929302620383dbb2e4b59223 Azure: [FAILURE](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=7791)
* 71d846c08f030f7dbe03445c61d1cfacf2122c3d UNKNOWN
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3194699710
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## CI report:
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* a852c2ac4a43bf15dc0678fd822bc0a31e403d2c UNKNOWN
* 714e47eb6dcc8aee75a2e4de69a751b2014c7ceb UNKNOWN
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* b9f3fc394f24da6d5a0f35ce9b6e2e5318adc0ad Azure: [FAILURE](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=7896)
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2281045946
##########
hudi-common/src/main/java/org/apache/hudi/avro/HoodieAvroWrapperUtils.java:
##########
@@ -238,4 +231,121 @@ private static Pair<Boolean, String> getIsValueWrapperObfuscated(Object statsVal
}
return Pair.of(false, null);
}
+
+ public enum PrimitiveWrapperType {
+ V1(Object.class, HoodieAvroWrapperUtils::wrapValueIntoAvro, HoodieAvroWrapperUtils::unwrapAvroValueWrapper),
+ NULL(Void.class, HoodieAvroWrapperUtils::wrapNull, HoodieAvroWrapperUtils::unwrapNull),
+ BOOLEAN(Boolean.class, HoodieAvroWrapperUtils::wrapBoolean, HoodieAvroWrapperUtils::unwrapBoolean),
+ INT(Integer.class, HoodieAvroWrapperUtils::wrapInt, HoodieAvroWrapperUtils::unwrapInt),
+ LONG(Long.class, HoodieAvroWrapperUtils::wrapLong, HoodieAvroWrapperUtils::unwrapLong),
+ FLOAT(Float.class, HoodieAvroWrapperUtils::wrapFloat, HoodieAvroWrapperUtils::unwrapFloat),
+ DOUBLE(Double.class, HoodieAvroWrapperUtils::wrapDouble, HoodieAvroWrapperUtils::unwrapDouble),
+ STRING(String.class, HoodieAvroWrapperUtils::wrapString, HoodieAvroWrapperUtils::unwrapString),
+ BYTES(ByteBuffer.class, HoodieAvroWrapperUtils::wrapBytes, HoodieAvroWrapperUtils::unwrapBytes);
+
+ private final Class<?> clazz;
+ private final Function<Comparable<?>, Object> wrapper;
+ private final Function<Object, Comparable<?>> unwrapper;
+
+ PrimitiveWrapperType(Class<?> clazz, Function<Comparable<?>, Object> wrapper, Function<Object, Comparable<?>> unwrapper) {
+ this.clazz = clazz;
+ this.wrapper = wrapper;
+ this.unwrapper = unwrapper;
+ }
+
+ Class<?> getClazz() {
+ return clazz;
+ }
+
+ Object wrap(Comparable<?> value) {
+ return wrapper.apply(value);
+ }
+
+ Comparable<?> unwrap(Object value) {
+ return unwrapper.apply(value);
+ }
+ }
+
+ private static Object wrapNull(Comparable<?> value) {
+ return value;
+ }
+
+ private static Object wrapBoolean(Comparable<?> value) {
+ return BooleanWrapper.newBuilder(BOOLEAN_WRAPPER_BUILDER_STUB.get()).setValue((Boolean) value).build();
+ }
+
+ private static Object wrapInt(Comparable<?> value) {
+ return IntWrapper.newBuilder(INT_WRAPPER_BUILDER_STUB.get()).setValue((Integer) value).build();
+ }
+
+ private static Object wrapLong(Comparable<?> value) {
+ return LongWrapper.newBuilder(LONG_WRAPPER_BUILDER_STUB.get()).setValue((Long) value).build();
+ }
+
+ private static Object wrapFloat(Comparable<?> value) {
+ return FloatWrapper.newBuilder(FLOAT_WRAPPER_BUILDER_STUB.get()).setValue((Float) value).build();
+ }
+
+ private static Object wrapDouble(Comparable<?> value) {
+ return DoubleWrapper.newBuilder(DOUBLE_WRAPPER_BUILDER_STUB.get()).setValue((Double) value).build();
+ }
+
+ private static Object wrapString(Comparable<?> value) {
+ return StringWrapper.newBuilder(STRING_WRAPPER_BUILDER_STUB.get()).setValue((String) value).build();
+ }
+
+ private static Object wrapBytes(Comparable<?> value) {
+ return BytesWrapper.newBuilder(BYTES_WRAPPER_BUILDER_STUB.get()).setValue((ByteBuffer) value).build();
+ }
+
+ public static Object wrapArray(Comparable<?> value, Function<Comparable<?>, Object> wrapper) {
+ List<Object> avroValues = OrderingValues.getValues((ArrayComparable) value).stream().map(wrapper::apply).collect(Collectors.toList());
+ return ArrayWrapper.newBuilder(ARRAY_WRAPPER_BUILDER_STUB.get()).setWrappedValues(avroValues).build();
+ }
+
+ private static Comparable<?> unwrapNull(Object val) {
+ return (Comparable<?>) val;
+ }
+
+ private static Comparable<?> unwrapBoolean(Object val) {
+ return ((BooleanWrapper) val).getValue();
+ }
+
+ private static Comparable<?> unwrapInt(Object val) {
+ return ((IntWrapper) val).getValue();
+ }
+
+ private static Comparable<?> unwrapLong(Object val) {
+ return ((LongWrapper) val).getValue();
+ }
+
+ private static Comparable<?> unwrapFloat(Object val) {
+ return ((FloatWrapper) val).getValue();
+ }
+
+ private static Comparable<?> unwrapDouble(Object val) {
+ return ((DoubleWrapper) val).getValue();
+ }
+
+ private static Comparable<?> unwrapString(Object val) {
+ return ((StringWrapper) val).getValue();
+ }
+
+ private static Comparable<?> unwrapBytes(Object val) {
+ return ((BytesWrapper) val).getValue();
+ }
+
+ public static Comparable<?> unwrapArray(Object val, Function<Object, Comparable<?>> unwrapper) {
+ ArrayWrapper arrayWrapper = (ArrayWrapper) val;
+ return OrderingValues.create(arrayWrapper.getWrappedValues().stream()
+ .map(unwrapper::apply)
+ .toArray(Comparable[]::new));
+ }
+
+ // NOTE: This branch could be hit b/c Avro records could be reconstructed
+ // as {@code GenericRecord)
+ public static Comparable<?> unwrapGenericRecord(Object val) {
Review Comment:
This seems wrong. But this definitely still gets hit.
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3193088555
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* b41b39fc5025b32b2acfa3aa667261c03e0e2aed Azure: [FAILURE](https://dev.azure.com/apachehudi/a1a51da7-8592-47d4-88dc-fd67bed336bb/_build/results?buildId=7859)
<details>
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3194571070
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Re: [PR] Col stats new schema [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2280969692
##########
hudi-common/src/main/java/org/apache/hudi/metadata/HoodieTableMetadataUtil.java:
##########
@@ -1721,8 +1760,9 @@ private static List<HoodieColumnRangeMetadata<Comparable>> readColumnRangeMetada
} catch (Exception e) {
// NOTE: In case reading column range metadata from individual file failed,
// we simply fall back, in lieu of failing the whole task
- LOG.error("Failed to fetch column range metadata for: {}", partitionPathFileName);
- return Collections.emptyList();
+ throw new HoodieException("Failed to fetch column range metadata for: " + partitionPathFileName, e);
Review Comment:
https://issues.apache.org/jira/browse/HUDI-9722 ticket. Need to fail task in some cases
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Re: [PR] Col stats new schema [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2280971055
##########
hudi-hadoop-common/src/main/java/org/apache/parquet/avro/HoodieAvroSchemaConverter.java:
##########
Review Comment:
This is copied from parquet-java and then I changed 2 methods to a later version of parquet java because they didn't account for local timestamps. Did this to unblock myself but maybe there is a better option than copying all this code
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3276535111
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3272173729
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2350304898
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/utils/SparkValueMetadata.java:
##########
@@ -0,0 +1,230 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.hudi.client.utils;
+
+import org.apache.hudi.SparkAdapterSupport$;
+import org.apache.hudi.avro.ValueMetadata;
+import org.apache.hudi.avro.ValueType;
+import org.apache.hudi.avro.model.HoodieValueTypeInfo;
+import org.apache.hudi.common.util.collection.ArrayComparable;
+import org.apache.hudi.metadata.HoodieIndexVersion;
+
+import org.apache.spark.sql.types.ArrayType;
+import org.apache.spark.sql.types.BinaryType;
+import org.apache.spark.sql.types.BooleanType;
+import org.apache.spark.sql.types.ByteType;
+import org.apache.spark.sql.types.CharType;
+import org.apache.spark.sql.types.DataType;
+import org.apache.spark.sql.types.DateType;
+import org.apache.spark.sql.types.Decimal;
+import org.apache.spark.sql.types.DecimalType;
+import org.apache.spark.sql.types.DoubleType;
+import org.apache.spark.sql.types.FloatType;
+import org.apache.spark.sql.types.IntegerType;
+import org.apache.spark.sql.types.LongType;
+import org.apache.spark.sql.types.NullType;
+import org.apache.spark.sql.types.ShortType;
+import org.apache.spark.sql.types.StringType;
+import org.apache.spark.sql.types.TimestampType;
+import org.apache.spark.sql.types.VarcharType;
+
+import java.sql.Date;
+import java.sql.Timestamp;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.util.Arrays;
+
+public class SparkValueMetadata extends ValueMetadata {
+
+ private final DataType dataType;
+
+ protected SparkValueMetadata(ValueType valueType, DataType dataType) {
+ super(valueType);
+ this.dataType = dataType;
+ }
+
+ public Comparable convertSparkToJava(Object value) {
+ return convertSparkToJava(value, true);
+ }
+
+ public static SparkValueMetadata getValueMetadata(DataType dataType, HoodieIndexVersion indexVersion) {
+ if (indexVersion.lowerThan(HoodieIndexVersion.V2)) {
+ return SparkV1EmptyMetadata.get();
+ }
+ if (dataType == null) {
+ return new SparkValueMetadata(ValueType.NULL, null);
+ }
+ ValueType valueType = fromDataType(dataType);
+ if (valueType == ValueType.DECIMAL) {
+ return new SparkDecimalMetadata((DecimalType) dataType);
+ } else {
+ return new SparkValueMetadata(valueType, dataType);
+ }
+ }
+
+ private static ValueType fromDataType(DataType dataType) {
+ return fromDataType(dataType, true);
+ }
+
+ private static ValueType fromDataType(DataType dataType, boolean root) {
+ if (dataType instanceof NullType) {
+ return ValueType.NULL;
+ } else if (dataType instanceof BooleanType) {
+ return ValueType.BOOLEAN;
+ } else if (dataType instanceof IntegerType || dataType instanceof ShortType || dataType instanceof ByteType) {
+ return ValueType.INT;
+ } else if (dataType instanceof LongType) {
+ return ValueType.LONG;
+ } else if (dataType instanceof FloatType) {
+ return ValueType.FLOAT;
+ } else if (dataType instanceof DoubleType) {
+ return ValueType.DOUBLE;
+ } else if (dataType instanceof StringType || dataType instanceof CharType || dataType instanceof VarcharType) {
+ return ValueType.STRING;
+ } else if (dataType instanceof TimestampType) {
Review Comment:
This is only used for expression index. Since we are dealing directly with spark we don't have a corresponding avro schema. I think maybe I should use `spark.sql.parquet.outputTimestampType` to decide if it's millis or micros to write. In spark in memory it is always micros I think.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3299709285
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3288796264
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2371635055
##########
hudi-common/src/main/java/org/apache/hudi/metadata/HoodieTableMetadataUtil.java:
##########
@@ -2540,33 +2615,36 @@ public HoodieRecord next() {
private static Stream<HoodieRecord> collectAndProcessColumnMetadata(
List<List<HoodieColumnRangeMetadata<Comparable>>> fileColumnMetadata,
String partitionPath, boolean isTightBound,
- Map<String, Schema> colsToIndexSchemaMap
+ Map<String, Schema> colsToIndexSchemaMap,
+ HoodieIndexVersion partitionStatsIndexVersion
) {
- return collectAndProcessColumnMetadata(partitionPath, isTightBound, Option.empty(), fileColumnMetadata.stream().flatMap(List::stream), colsToIndexSchemaMap);
+ return collectAndProcessColumnMetadata(partitionPath, isTightBound, Option.empty(), fileColumnMetadata.stream().flatMap(List::stream), colsToIndexSchemaMap, partitionStatsIndexVersion);
}
private static Stream<HoodieRecord> collectAndProcessColumnMetadata(Iterable<HoodieColumnRangeMetadata<Comparable>> fileColumnMetadataIterable, String partitionPath,
boolean isTightBound, Option<String> indexPartitionOpt,
- Map<String, Schema> colsToIndexSchemaMap
+ Map<String, Schema> colsToIndexSchemaMap,
+ HoodieIndexVersion partitionStatsIndexVersion
) {
List<HoodieColumnRangeMetadata<Comparable>> fileColumnMetadata = new ArrayList<>();
fileColumnMetadataIterable.forEach(fileColumnMetadata::add);
// Group by Column Name
- return collectAndProcessColumnMetadata(partitionPath, isTightBound, indexPartitionOpt, fileColumnMetadata.stream(), colsToIndexSchemaMap);
+ return collectAndProcessColumnMetadata(partitionPath, isTightBound, indexPartitionOpt, fileColumnMetadata.stream(), colsToIndexSchemaMap, partitionStatsIndexVersion);
}
private static Stream<HoodieRecord> collectAndProcessColumnMetadata(String partitionPath, boolean isTightBound, Option<String> indexPartitionOpt,
Stream<HoodieColumnRangeMetadata<Comparable>> fileColumnMetadata,
- Map<String, Schema> colsToIndexSchemaMap
+ Map<String, Schema> colsToIndexSchemaMap,
+ HoodieIndexVersion partitionStatsIndexVersion
) {
// Group by Column Name
Map<String, List<HoodieColumnRangeMetadata<Comparable>>> columnMetadataMap =
fileColumnMetadata.collect(Collectors.groupingBy(HoodieColumnRangeMetadata::getColumnName, Collectors.toList()));
// Aggregate Column Ranges
Stream<HoodieColumnRangeMetadata<Comparable>> partitionStatsRangeMetadata = columnMetadataMap.entrySet().stream()
- .map(entry -> FileFormatUtils.getColumnRangeInPartition(partitionPath, entry.getValue(), colsToIndexSchemaMap));
+ .map(entry -> FileFormatUtils.getColumnRangeInPartition(partitionPath, entry.getKey(), entry.getValue(), colsToIndexSchemaMap,partitionStatsIndexVersion));
Review Comment:
```suggestion
.map(entry -> FileFormatUtils.getColumnRangeInPartition(partitionPath, entry.getKey(), entry.getValue(), colsToIndexSchemaMap, partitionStatsIndexVersion));
```
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3320816342
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2294222855
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/table/upgrade/EightToNineUpgradeHandler.java:
##########
@@ -209,4 +229,24 @@ static void populateIndexVersionIfMissing(Option<HoodieIndexMetadata> indexDefOp
}
}));
}
+
+ /**
+ * Drop logical type indexes since we support them correctly now.
+ */
+ static List<String> mdtPartitionsToDrop(Option<HoodieIndexMetadata> indexDefOption, Schema tableSchema) {
+ Set<String> partitionsToDrop = new HashSet<>();
+ indexDefOption.ifPresent(idxDefs ->
+ idxDefs.getIndexDefinitions().forEach((indexName, idxDef) -> {
+ if (idxDef.getVersion() == null || idxDef.getVersion().lowerThan(HoodieIndexVersion.V2)) {
+ idxDef.getSourceFields().stream().filter(field -> {
+ Option<Schema> schema = AvroSchemaUtils.findNestedFieldSchema(tableSchema, field);
+ if (schema.isEmpty()) {
Review Comment:
Thanks yeah that's a mistake.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2304237966
##########
hudi-common/src/test/resources/nullWrong.avsc:
##########
@@ -197,7 +197,48 @@
},
"null"
]
- }
+ },
+ {
+ "name": "timeMicroField",
Review Comment:
Maybe it needs to be a separate test? The reason I added this is because fixNullOrdering was dropping the logical types. I should also check decimal fixed and binary as well
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3301320977
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2353712476
##########
hudi-common/src/main/java/org/apache/hudi/common/util/DateTimeUtils.java:
##########
@@ -71,6 +77,41 @@ public static long instantToMicros(Instant instant) {
}
}
+ public static long instantToNanos(Instant instant) {
+ long seconds = instant.getEpochSecond();
+ int nanos = instant.getNano();
+
+ if (seconds < 0 && nanos > 0) {
+ // Shift seconds by +1, then subtract a full second in nanos
+ long totalNanos = Math.multiplyExact(seconds + 1, 1_000_000_000L);
+ long adjustment = nanos - 1_000_000_000L;
+ return Math.addExact(totalNanos, adjustment);
+ } else {
+ long totalNanos = Math.multiplyExact(seconds, 1_000_000_000L);
+ return Math.addExact(totalNanos, nanos);
+ }
+ }
Review Comment:
I think I copied these from spark and I think the class name was the same in spark as well
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2354162393
##########
hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/HoodieFileGroupReaderBasedFileFormat.scala:
##########
@@ -192,9 +195,12 @@ class HoodieFileGroupReaderBasedFileFormat(tablePath: String,
val fixedPartitionIndexes = fixedPartitionIndexesArr.toSet
// schema that we want fg reader to output to us
+ val exclusionFields = new java.util.HashSet[String]()
+ exclusionFields.add("op")
+ partitionSchema.fields.foreach(f => exclusionFields.add(f.name))
val requestedSchema = StructType(requiredSchema.fields ++ partitionSchema.fields.filter(f => mandatoryFields.contains(f.name)))
- val requestedAvroSchema = AvroConversionUtils.convertStructTypeToAvroSchema(requestedSchema, sanitizedTableName)
- val dataAvroSchema = AvroConversionUtils.convertStructTypeToAvroSchema(dataSchema, sanitizedTableName)
+ val requestedAvroSchema = AvroSchemaUtils.pruneDataSchema(avroTableSchema, AvroConversionUtils.convertStructTypeToAvroSchema(requestedSchema, sanitizedTableName), exclusionFields)
+ val dataAvroSchema = AvroSchemaUtils.pruneDataSchema(avroTableSchema, AvroConversionUtils.convertStructTypeToAvroSchema(dataSchema, sanitizedTableName), exclusionFields)
Review Comment:
It's needed for reading timestamp millis properly
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2357307064
##########
hudi-common/src/test/java/org/apache/hudi/common/testutils/HoodieTestDataGenerator.java:
##########
@@ -598,6 +669,106 @@ public GenericRecord generateRecordForTripEncodedDecimalSchema(String rowKey, St
return rec;
}
+ public GenericRecord generateRecordForTripLogicalTypesSchema(HoodieKey key, String riderName, String driverName,
+ long timestamp, boolean isDeleteRecord, boolean v6, boolean hasLTS) {
+ GenericRecord rec;
+ if (!hasLTS) {
+ rec = new GenericData.Record(AVRO_TRIP_LOGICAL_TYPES_SCHEMA_NO_LTS);
+ } else if (v6) {
+ rec = new GenericData.Record(AVRO_TRIP_LOGICAL_TYPES_SCHEMA_V6);
+ } else {
+ rec = new GenericData.Record(AVRO_TRIP_LOGICAL_TYPES_SCHEMA);
+ }
+ generateTripPrefixValues(rec, key.getRecordKey(), key.getPartitionPath(), riderName, driverName, timestamp);
+
+ int hash = key.getRecordKey().hashCode();
+ boolean above = (hash & 1) == 0; // half above, half below threshold
+
+ // -------------------
+ // Threshold definitions
+ // -------------------
+ Instant tsMillisThreshold = Instant.parse("2020-01-01T00:00:00Z");
+ Instant tsMicrosThreshold = Instant.parse("2020-06-01T12:00:00Z");
+
+ //LocalTime timeMillisThreshold = LocalTime.of(12, 0, 0); // noon
+ //LocalTime timeMicrosThreshold = LocalTime.of(6, 0, 0); // 6 AM
+
+ Instant localTsMillisThreshold = ZonedDateTime.of(
+ 2015, 5, 20, 12, 34, 56, 0, ZoneOffset.UTC).toInstant();
+ Instant localTsMicrosThreshold = ZonedDateTime.of(
+ 2017, 7, 7, 7, 7, 7, 0, ZoneOffset.UTC).toInstant();
+
+ LocalDate dateThreshold = LocalDate.of(2000, 1, 1);
+
+ // -------------------
+ // Assign edge values
+ // -------------------
+
+ // ts_millis
+ long tsMillisBase = tsMillisThreshold.toEpochMilli();
+ rec.put("ts_millis", above ? tsMillisBase + 1 : tsMillisBase - 1);
+
+ // ts_micros
+ long tsMicrosBase = TimeUnit.SECONDS.toMicros(tsMicrosThreshold.getEpochSecond()) + tsMicrosThreshold.getNano() / 1_000L;
+ rec.put("ts_micros", above ? tsMicrosBase + 1 : tsMicrosBase - 1);
+
+ // time_millis
+ //int timeMillisBase = (int) TimeUnit.SECONDS.toMillis(timeMillisThreshold.toSecondOfDay());
+ //rec.put("time_millis", above ? timeMillisBase + 1 : timeMillisBase - 1);
+
+ // time_micros
+ //long timeMicrosBase = TimeUnit.SECONDS.toMicros(timeMicrosThreshold.toSecondOfDay());
+ //rec.put("time_micros", above ? timeMicrosBase + 1 : timeMicrosBase - 1);
Review Comment:
remove these because spark doesn't currently have support
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3288892763
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3289021752
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3312529358
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3312639082
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<details>
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2359321397
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/utils/SparkMetadataWriterUtils.java:
##########
@@ -178,12 +185,13 @@ public static ExpressionIndexComputationMetadata getExpressionIndexRecordsUsingC
HoodieColumnRangeMetadata<Comparable> rangeMetadata = HoodieColumnRangeMetadata.create(
relativeFilePath,
columnToIndex,
- minValue,
- maxValue,
+ (Comparable) valueMetadata.standardizeJavaTypeAndPromote(minValue),
+ (Comparable) valueMetadata.standardizeJavaTypeAndPromote(maxValue),
nullCount,
valueCount,
totalFileSize,
- totalUncompressedSize
+ totalUncompressedSize,
+ valueMetadata
Review Comment:
We decided to punt this.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3309690512
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2359581074
##########
hudi-common/src/main/java/org/apache/hudi/avro/AvroSchemaUtils.java:
##########
@@ -423,22 +428,24 @@ private static Schema pruneDataSchemaInternal(Schema dataSchema, Schema required
}
List<Schema.Field> newFields = new ArrayList<>();
for (Schema.Field requiredSchemaField : requiredSchema.getFields()) {
- Schema.Field dataSchemaField = dataSchema.getField(requiredSchemaField.name());
- if (dataSchemaField != null) {
- Schema.Field newField = new Schema.Field(
- dataSchemaField.name(),
- pruneDataSchema(dataSchemaField.schema(), requiredSchemaField.schema(), Collections.emptySet()),
- dataSchemaField.doc(),
- dataSchemaField.defaultVal()
- );
- newFields.add(newField);
- } else if (mandatoryFields.contains(requiredSchemaField.name())) {
+ if (mandatoryFields.contains(requiredSchemaField.name())) {
Review Comment:
Got it. This might be a bug around timestamp partition column, which is fixed by this PR.
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "yihua (via GitHub)" <gi...@apache.org>.
yihua commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2359692768
##########
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/spark/sql/hudi/feature/index/TestExpressionIndex.scala:
##########
@@ -1548,28 +1550,28 @@ class TestExpressionIndex extends HoodieSparkSqlTestBase {
spark.sql(s"create index idx_to_timestamp_default on $tableName using column_stats(date) options(expr='to_timestamp')")
metaClient = HoodieTableMetaClient.reload(metaClient)
val toTimestampDefault = resolveExpr(spark, unapply(functions.to_timestamp(functions.col("date"))).get, tableSchema)
- dataFilter = EqualTo(toTimestampDefault, lit(1732924800000000L).expr)
+ dataFilter = EqualTo(toTimestampDefault, lit(SparkValueMetadata.convertJavaTypeToSparkType(ValueType.toTimestampMicros(1732924800000000L, null), false)).expr)
verifyFilePruning(opts, dataFilter, metaClient, isDataSkippingExpected = true)
spark.sql(s"drop index idx_to_timestamp_default on $tableName")
spark.sql(s"create index idx_to_timestamp on $tableName using column_stats(date) options(expr='to_timestamp', format='yyyy-MM-dd')")
metaClient = HoodieTableMetaClient.reload(metaClient)
val toTimestamp = resolveExpr(spark, unapply(functions.to_timestamp(functions.col("date"), "yyyy-MM-dd")).get, tableSchema)
- dataFilter = EqualTo(toTimestamp, lit(1732924800000000L).expr)
+ dataFilter = EqualTo(toTimestamp, lit(SparkValueMetadata.convertJavaTypeToSparkType(ValueType.toTimestampMicros(1732924800000000L, null), false)).expr)
verifyFilePruning(opts, dataFilter, metaClient, isDataSkippingExpected = true)
spark.sql(s"drop index idx_to_timestamp on $tableName")
spark.sql(s"create index idx_date_add on $tableName using column_stats(date) options(expr='date_add', days='10')")
metaClient = HoodieTableMetaClient.reload(metaClient)
val dateAdd = resolveExpr(spark, unapply(functions.date_add(functions.col("date"), 10)).get, tableSchema)
- dataFilter = EqualTo(dateAdd, lit(18606).expr)
+ dataFilter = EqualTo(dateAdd, lit(HoodieAvroUtils.toJavaDate(18606)).expr)
verifyFilePruning(opts, dataFilter, metaClient, isDataSkippingExpected = true)
spark.sql(s"drop index idx_date_add on $tableName")
spark.sql(s"create index idx_date_sub on $tableName using column_stats(date) options(expr='date_sub', days='10')")
metaClient = HoodieTableMetaClient.reload(metaClient)
val dateSub = resolveExpr(spark, unapply(functions.date_sub(functions.col("date"), 10)).get, tableSchema)
- dataFilter = EqualTo(dateSub, lit(18586).expr)
+ dataFilter = EqualTo(dateSub, lit(HoodieAvroUtils.toJavaDate(18586)).expr)
Review Comment:
Got it
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3309121930
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "jonvex (via GitHub)" <gi...@apache.org>.
jonvex commented on code in PR #13711:
URL: https://github.com/apache/hudi/pull/13711#discussion_r2364650082
##########
hudi-utilities/src/test/java/org/apache/hudi/utilities/deltastreamer/TestHoodieDeltaStreamer.java:
##########
@@ -670,6 +672,286 @@ public void testSchemaEvolution(String tableType, boolean useUserProvidedSchema,
defaultSchemaProviderClassName = FilebasedSchemaProvider.class.getName();
}
+ @Test
+ public void testTimestampMillis() throws Exception {
+ // if (zookeeperTestService != null) {
+ // zookeeperTestService.stop();
+ // zookeeperTestService = null;
+ // }
+ String tableBasePath = basePath + "/testTimestampMillis";
+ defaultSchemaProviderClassName = FilebasedSchemaProvider.class.getName();
+ // Insert data produced with Schema A, pass Schema A
+ HoodieDeltaStreamer.Config cfg = TestHelpers.makeConfig(tableBasePath, WriteOperationType.INSERT, Collections.singletonList(TestIdentityTransformer.class.getName()),
+ PROPS_FILENAME_TEST_SOURCE, false, true, false, null, HoodieTableType.MERGE_ON_READ.name());
+ cfg.payloadClassName = DefaultHoodieRecordPayload.class.getName();
+ cfg.recordMergeStrategyId = HoodieRecordMerger.EVENT_TIME_BASED_MERGE_STRATEGY_UUID;
+ cfg.recordMergeMode = RecordMergeMode.EVENT_TIME_ORDERING;
+ cfg.configs.add("hoodie.streamer.schemaprovider.source.schema.file=" + basePath + "/source-timestamp-millis.avsc");
+ cfg.configs.add("hoodie.streamer.schemaprovider.target.schema.file=" + basePath + "/source-timestamp-millis.avsc");
+ cfg.configs.add(String.format("%s=%s", HoodieCompactionConfig.PARQUET_SMALL_FILE_LIMIT.key(), "0"));
+
+
+ new HoodieDeltaStreamer(cfg, jsc).sync();
+ assertUseV2Checkpoint(HoodieTestUtils.createMetaClient(storage, tableBasePath));
+ assertRecordCount(1000, tableBasePath, sqlContext);
+ TestHelpers.assertCommitMetadata("00000", tableBasePath, 1);
+ TableSchemaResolver tableSchemaResolver = new TableSchemaResolver(
+ HoodieTestUtils.createMetaClient(storage, tableBasePath));
+ Schema tableSchema = tableSchemaResolver.getTableAvroSchema(false);
+ assertEquals("timestamp-millis", tableSchema.getField("current_ts").schema().getLogicalType().getName());
+ assertEquals(1000, sqlContext.read().options(hudiOpts).format("org.apache.hudi").load(tableBasePath).filter("current_ts > '1980-01-01'").count());
+
+ cfg = TestHelpers.makeConfig(tableBasePath, WriteOperationType.UPSERT, Collections.singletonList(TestIdentityTransformer.class.getName()),
+ PROPS_FILENAME_TEST_SOURCE, false, true, false, null, HoodieTableType.MERGE_ON_READ.name());
+ cfg.payloadClassName = DefaultHoodieRecordPayload.class.getName();
+ cfg.recordMergeStrategyId = HoodieRecordMerger.EVENT_TIME_BASED_MERGE_STRATEGY_UUID;
+ cfg.recordMergeMode = RecordMergeMode.EVENT_TIME_ORDERING;
+ cfg.configs.add("hoodie.streamer.schemaprovider.source.schema.file=" + basePath + "/source-timestamp-millis.avsc");
+ cfg.configs.add("hoodie.streamer.schemaprovider.target.schema.file=" + basePath + "/source-timestamp-millis.avsc");
+ cfg.configs.add(String.format("%s=%s", HoodieCompactionConfig.PARQUET_SMALL_FILE_LIMIT.key(), "0"));
+
+ new HoodieDeltaStreamer(cfg, jsc).sync();
+ assertUseV2Checkpoint(HoodieTestUtils.createMetaClient(storage, tableBasePath));
+ assertRecordCount(1450, tableBasePath, sqlContext);
+ TestHelpers.assertCommitMetadata("00001", tableBasePath, 2);
+ tableSchemaResolver = new TableSchemaResolver(
+ HoodieTestUtils.createMetaClient(storage, tableBasePath));
+ tableSchema = tableSchemaResolver.getTableAvroSchema(false);
+ assertEquals("timestamp-millis", tableSchema.getField("current_ts").schema().getLogicalType().getName());
+ sqlContext.clearCache();
+ assertEquals(1450, sqlContext.read().options(hudiOpts).format("org.apache.hudi").load(tableBasePath).filter("current_ts > '1980-01-01'").count());
+ assertEquals(1450, sqlContext.read().options(hudiOpts).format("org.apache.hudi").load(tableBasePath).filter("current_ts < '2080-01-01'").count());
+ assertEquals(0, sqlContext.read().options(hudiOpts).format("org.apache.hudi").load(tableBasePath).filter("current_ts < '1980-01-01'").count());
+ }
+
+ @Test
+ public void testLogicalTypes() throws Exception {
Review Comment:
skipping for now since test datasource doesn't have v1 checkpoints
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Re: [PR] Improve Logical Type Handling on Col Stats [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3197741363
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Re: [PR] Col stats new schema [hudi]
Posted by "hudi-bot (via GitHub)" <gi...@apache.org>.
hudi-bot commented on PR #13711:
URL: https://github.com/apache/hudi/pull/13711#issuecomment-3194549597
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