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Posted to issues@iceberg.apache.org by GitBox <gi...@apache.org> on 2022/02/28 18:55:25 UTC
[GitHub] [iceberg] funcheetah opened a new pull request #4242: Support complex union types for Avro and ORC
funcheetah opened a new pull request #4242:
URL: https://github.com/apache/iceberg/pull/4242
This PR adds support to read complex union type as struct type for Apache Avro and Apache ORC format.
[TODO]
1. Add detailed PR description
2. Handle union type with only one option properly
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[GitHub] [iceberg] shardulm94 commented on a change in pull request #4242: Support non-optional union types for Avro and ORC
Posted by GitBox <gi...@apache.org>.
shardulm94 commented on a change in pull request #4242:
URL: https://github.com/apache/iceberg/pull/4242#discussion_r827529615
##########
File path: core/src/main/java/org/apache/iceberg/avro/AvroSchemaVisitor.java
##########
@@ -52,8 +52,21 @@
case UNION:
List<Schema> types = schema.getTypes();
List<T> options = Lists.newArrayListWithExpectedSize(types.size());
- for (Schema type : types) {
- options.add(visit(type, visitor));
+ if (AvroSchemaUtil.isOptionSchema(schema)) {
+ for (Schema type : types) {
+ options.add(visit(type, visitor));
+ }
+ } else {
+ // complex union case
Review comment:
Seems like we are implementing business logic in the visitor. Ideally the visitor should just handle traversing the Schema tree and leave business logic to the implementation. e.g. here converting union to struct and assigning field names like "field${i}" should be handled in the implementation class's `union` method.
On a side note, I removed this piece of code and `TestUnionSchemaConversion` ran just fine. Is this code really needed?
##########
File path: core/src/main/java/org/apache/iceberg/avro/AvroSchemaUtil.java
##########
@@ -154,6 +154,27 @@ public static boolean isOptionSchema(Schema schema) {
return false;
}
+ /**
+ * This method decides whether a schema is of type union and is complex union and is optional
+ *
+ * Complex union: the number of options in union not equals to 2
+ * Optional: null is present in union
+ *
+ * @param schema input schema
+ * @return true if schema is complex union and it is optional
+ */
+ public static boolean isOptionalComplexUnion(Schema schema) {
+ if (schema.getType() == UNION && schema.getTypes().size() != 2) {
Review comment:
What happens is it receives a schema like ["null"]. This is regarded as an optional complex union by this function. Is this expected? Should we instead check for `schema.getTypes().size() > 2`. What is the impact of this return true on the readers?
##########
File path: core/src/main/java/org/apache/iceberg/avro/AvroSchemaWithTypeVisitor.java
##########
@@ -79,11 +79,25 @@
private static <T> T visitUnion(Type type, Schema union, AvroSchemaWithTypeVisitor<T> visitor) {
List<Schema> types = union.getTypes();
List<T> options = Lists.newArrayListWithExpectedSize(types.size());
- for (Schema branch : types) {
- if (branch.getType() == Schema.Type.NULL) {
- options.add(visit((Type) null, branch, visitor));
- } else {
- options.add(visit(type, branch, visitor));
+
+ // simple union case
+ if (AvroSchemaUtil.isOptionSchema(union)) {
+ for (Schema branch : types) {
+ if (branch.getType() == Schema.Type.NULL) {
+ options.add(visit((Type) null, branch, visitor));
+ } else {
+ options.add(visit(type, branch, visitor));
+ }
+ }
+ } else { // complex union case
+ int index = 1;
+ for (Schema branch : types) {
+ if (branch.getType() == Schema.Type.NULL) {
+ options.add(visit((Type) null, branch, visitor));
+ } else {
+ options.add(visit(type.asStructType().fields().get(index).type(), branch, visitor));
Review comment:
Similar comment to `AvroSchemaVisitor` with business logic being introduced in the visitor.
##########
File path: core/src/main/java/org/apache/iceberg/avro/PruneColumns.java
##########
@@ -323,4 +325,19 @@ private static Schema makeEmptyCopy(Schema field) {
private static boolean isOptionSchemaWithNonNullFirstOption(Schema schema) {
return AvroSchemaUtil.isOptionSchema(schema) && schema.getTypes().get(0).getType() != Schema.Type.NULL;
}
+
+ // for primitive types, the visitResult will be null, we want to reuse the primitive types from the original
+ // schema, while for nested types, we want to use the visitResult because they have content from the previous
+ // recursive calls.
+ private static Schema copyUnion(Schema record, List<Schema> visitResults) {
Review comment:
It does not look we prune any columns in the complex union case. I tried modifying `TestSparkAvroUnions` to test projecting a single field from the complex union and it fails (error below). There are a couple of ways we can go about column pruning:
1. We should implement column pruning for complex unions. It should be okay to implement this as a followup PR, but in that case I think we should throw a better error message letting the user known that projecting fields within a complex union is not supported for now.
2. We can choose not to prune columns inside complex unions and rather let the engine handle the pruning. E.g. you can see a comment in `map()` => `// right now, maps can't be selected without values`. The `ReadBuilder`s might need to be handled to account for this change.
```
index (1) must be less than size (1)
java.lang.IndexOutOfBoundsException: index (1) must be less than size (1)
at org.apache.iceberg.relocated.com.google.common.base.Preconditions.checkElementIndex(Preconditions.java:1355)
at org.apache.iceberg.relocated.com.google.common.base.Preconditions.checkElementIndex(Preconditions.java:1337)
at org.apache.iceberg.relocated.com.google.common.collect.SingletonImmutableList.get(SingletonImmutableList.java:44)
at org.apache.iceberg.avro.AvroSchemaWithTypeVisitor.visitUnion(AvroSchemaWithTypeVisitor.java:98)
at org.apache.iceberg.avro.AvroSchemaWithTypeVisitor.visit(AvroSchemaWithTypeVisitor.java:41)
at org.apache.iceberg.avro.AvroSchemaWithTypeVisitor.visitRecord(AvroSchemaWithTypeVisitor.java:71)
at org.apache.iceberg.avro.AvroSchemaWithTypeVisitor.visit(AvroSchemaWithTypeVisitor.java:38)
at org.apache.iceberg.avro.AvroSchemaWithTypeVisitor.visit(AvroSchemaWithTypeVisitor.java:32)
at org.apache.iceberg.spark.data.SparkAvroReader.<init>(SparkAvroReader.java:57)
at org.apache.iceberg.spark.data.SparkAvroReader.<init>(SparkAvroReader.java:50)
at org.apache.iceberg.avro.Avro$ReadBuilder.lambda$build$1(Avro.java:652)
at org.apache.iceberg.avro.ProjectionDatumReader.newDatumReader(ProjectionDatumReader.java:79)
at org.apache.iceberg.avro.ProjectionDatumReader.setSchema(ProjectionDatumReader.java:69)
at org.apache.avro.file.DataFileStream.initialize(DataFileStream.java:133)
at org.apache.avro.file.DataFileReader.<init>(DataFileReader.java:130)
at org.apache.avro.file.DataFileReader.<init>(DataFileReader.java:122)
at org.apache.avro.file.DataFileReader.openReader(DataFileReader.java:66)
at org.apache.iceberg.avro.AvroIterable.newFileReader(AvroIterable.java:100)
at org.apache.iceberg.avro.AvroIterable.iterator(AvroIterable.java:77)
at org.apache.iceberg.avro.AvroIterable.iterator(AvroIterable.java:37)
at org.apache.iceberg.relocated.com.google.common.collect.Lists.newArrayList(Lists.java:133)
at org.apache.iceberg.spark.data.TestSparkAvroUnions.writeAndValidateRequiredComplexUnion(TestSparkAvroUnions.java:75)
```
##########
File path: spark/v3.2/spark/src/test/java/org/apache/iceberg/spark/data/TestSparkAvroUnions.java
##########
@@ -0,0 +1,272 @@
+/*
+ * Licensed 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.iceberg.spark.data;
+
+import java.io.File;
+import java.io.IOException;
+import java.util.Arrays;
+import java.util.List;
+import org.apache.avro.SchemaBuilder;
+import org.apache.avro.file.DataFileWriter;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericDatumWriter;
+import org.apache.iceberg.Files;
+import org.apache.iceberg.Schema;
+import org.apache.iceberg.avro.Avro;
+import org.apache.iceberg.avro.AvroIterable;
+import org.apache.iceberg.avro.AvroSchemaUtil;
+import org.apache.iceberg.relocated.com.google.common.collect.Lists;
+import org.apache.spark.sql.catalyst.InternalRow;
+import org.junit.Assert;
+import org.junit.Rule;
+import org.junit.Test;
+import org.junit.rules.TemporaryFolder;
+
+public class TestSparkAvroUnions {
Review comment:
Can we add a test case here to check for the output when only some fields within the union are projected?
##########
File path: core/src/main/java/org/apache/iceberg/avro/SchemaToType.java
##########
@@ -105,13 +106,27 @@ public Type record(Schema record, List<String> names, List<Type> fieldTypes) {
@Override
public Type union(Schema union, List<Type> options) {
- Preconditions.checkArgument(AvroSchemaUtil.isOptionSchema(union),
- "Unsupported type: non-option union: %s", union);
- // records, arrays, and maps will check nullability later
- if (options.get(0) == null) {
- return options.get(1);
+ if (AvroSchemaUtil.isOptionSchema(union)) {
+ // Optional simple union
+ // records, arrays, and maps will check nullability later
+ if (options.get(0) == null) {
+ return options.get(1);
+ } else {
+ return options.get(0);
+ }
} else {
- return options.get(0);
+ // Complex union
+ List<Types.NestedField> newFields = new ArrayList<>();
+ newFields.add(Types.NestedField.required(allocateId(), "tag", Types.IntegerType.get()));
+
+ int tagIndex = 0;
+ for (Type type : options) {
+ if (type != null) {
+ newFields.add(Types.NestedField.optional(allocateId(), "field" + tagIndex++, type));
+ }
Review comment:
Can you add the reasoning behind why the field names `tag` and `field${index}` were chosen when converting to struct? Spark's Avro datasources uses `member${index}` while Hive's `extract_union` UDF uses `tag_${index}`.
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[GitHub] [iceberg] shardulm94 commented on a change in pull request #4242: Support non-optional union types for Avro and ORC
Posted by GitBox <gi...@apache.org>.
shardulm94 commented on a change in pull request #4242:
URL: https://github.com/apache/iceberg/pull/4242#discussion_r827529615
##########
File path: core/src/main/java/org/apache/iceberg/avro/AvroSchemaVisitor.java
##########
@@ -52,8 +52,21 @@
case UNION:
List<Schema> types = schema.getTypes();
List<T> options = Lists.newArrayListWithExpectedSize(types.size());
- for (Schema type : types) {
- options.add(visit(type, visitor));
+ if (AvroSchemaUtil.isOptionSchema(schema)) {
+ for (Schema type : types) {
+ options.add(visit(type, visitor));
+ }
+ } else {
+ // complex union case
Review comment:
Seems like we are implementing business logic in the visitor. Ideally the visitor should just handle traversing the Schema tree and leave business logic to the implementation. e.g. here converting union to struct and assigning field names like "field${i}" should be handled in the implementation class's `union` method.
On a side note, I removed this piece of code and `TestUnionSchemaConversion` ran just fine. Is this code really needed?
##########
File path: core/src/main/java/org/apache/iceberg/avro/AvroSchemaUtil.java
##########
@@ -154,6 +154,27 @@ public static boolean isOptionSchema(Schema schema) {
return false;
}
+ /**
+ * This method decides whether a schema is of type union and is complex union and is optional
+ *
+ * Complex union: the number of options in union not equals to 2
+ * Optional: null is present in union
+ *
+ * @param schema input schema
+ * @return true if schema is complex union and it is optional
+ */
+ public static boolean isOptionalComplexUnion(Schema schema) {
+ if (schema.getType() == UNION && schema.getTypes().size() != 2) {
Review comment:
What happens is it receives a schema like ["null"]. This is regarded as an optional complex union by this function. Is this expected? Should we instead check for `schema.getTypes().size() > 2`. What is the impact of this return true on the readers?
##########
File path: core/src/main/java/org/apache/iceberg/avro/AvroSchemaWithTypeVisitor.java
##########
@@ -79,11 +79,25 @@
private static <T> T visitUnion(Type type, Schema union, AvroSchemaWithTypeVisitor<T> visitor) {
List<Schema> types = union.getTypes();
List<T> options = Lists.newArrayListWithExpectedSize(types.size());
- for (Schema branch : types) {
- if (branch.getType() == Schema.Type.NULL) {
- options.add(visit((Type) null, branch, visitor));
- } else {
- options.add(visit(type, branch, visitor));
+
+ // simple union case
+ if (AvroSchemaUtil.isOptionSchema(union)) {
+ for (Schema branch : types) {
+ if (branch.getType() == Schema.Type.NULL) {
+ options.add(visit((Type) null, branch, visitor));
+ } else {
+ options.add(visit(type, branch, visitor));
+ }
+ }
+ } else { // complex union case
+ int index = 1;
+ for (Schema branch : types) {
+ if (branch.getType() == Schema.Type.NULL) {
+ options.add(visit((Type) null, branch, visitor));
+ } else {
+ options.add(visit(type.asStructType().fields().get(index).type(), branch, visitor));
Review comment:
Similar comment to `AvroSchemaVisitor` with business logic being introduced in the visitor.
##########
File path: core/src/main/java/org/apache/iceberg/avro/PruneColumns.java
##########
@@ -323,4 +325,19 @@ private static Schema makeEmptyCopy(Schema field) {
private static boolean isOptionSchemaWithNonNullFirstOption(Schema schema) {
return AvroSchemaUtil.isOptionSchema(schema) && schema.getTypes().get(0).getType() != Schema.Type.NULL;
}
+
+ // for primitive types, the visitResult will be null, we want to reuse the primitive types from the original
+ // schema, while for nested types, we want to use the visitResult because they have content from the previous
+ // recursive calls.
+ private static Schema copyUnion(Schema record, List<Schema> visitResults) {
Review comment:
It does not look we prune any columns in the complex union case. I tried modifying `TestSparkAvroUnions` to test projecting a single field from the complex union and it fails (error below). There are a couple of ways we can go about column pruning:
1. We should implement column pruning for complex unions. It should be okay to implement this as a followup PR, but in that case I think we should throw a better error message letting the user known that projecting fields within a complex union is not supported for now.
2. We can choose not to prune columns inside complex unions and rather let the engine handle the pruning. E.g. you can see a comment in `map()` => `// right now, maps can't be selected without values`. The `ReadBuilder`s might need to be handled to account for this change.
```
index (1) must be less than size (1)
java.lang.IndexOutOfBoundsException: index (1) must be less than size (1)
at org.apache.iceberg.relocated.com.google.common.base.Preconditions.checkElementIndex(Preconditions.java:1355)
at org.apache.iceberg.relocated.com.google.common.base.Preconditions.checkElementIndex(Preconditions.java:1337)
at org.apache.iceberg.relocated.com.google.common.collect.SingletonImmutableList.get(SingletonImmutableList.java:44)
at org.apache.iceberg.avro.AvroSchemaWithTypeVisitor.visitUnion(AvroSchemaWithTypeVisitor.java:98)
at org.apache.iceberg.avro.AvroSchemaWithTypeVisitor.visit(AvroSchemaWithTypeVisitor.java:41)
at org.apache.iceberg.avro.AvroSchemaWithTypeVisitor.visitRecord(AvroSchemaWithTypeVisitor.java:71)
at org.apache.iceberg.avro.AvroSchemaWithTypeVisitor.visit(AvroSchemaWithTypeVisitor.java:38)
at org.apache.iceberg.avro.AvroSchemaWithTypeVisitor.visit(AvroSchemaWithTypeVisitor.java:32)
at org.apache.iceberg.spark.data.SparkAvroReader.<init>(SparkAvroReader.java:57)
at org.apache.iceberg.spark.data.SparkAvroReader.<init>(SparkAvroReader.java:50)
at org.apache.iceberg.avro.Avro$ReadBuilder.lambda$build$1(Avro.java:652)
at org.apache.iceberg.avro.ProjectionDatumReader.newDatumReader(ProjectionDatumReader.java:79)
at org.apache.iceberg.avro.ProjectionDatumReader.setSchema(ProjectionDatumReader.java:69)
at org.apache.avro.file.DataFileStream.initialize(DataFileStream.java:133)
at org.apache.avro.file.DataFileReader.<init>(DataFileReader.java:130)
at org.apache.avro.file.DataFileReader.<init>(DataFileReader.java:122)
at org.apache.avro.file.DataFileReader.openReader(DataFileReader.java:66)
at org.apache.iceberg.avro.AvroIterable.newFileReader(AvroIterable.java:100)
at org.apache.iceberg.avro.AvroIterable.iterator(AvroIterable.java:77)
at org.apache.iceberg.avro.AvroIterable.iterator(AvroIterable.java:37)
at org.apache.iceberg.relocated.com.google.common.collect.Lists.newArrayList(Lists.java:133)
at org.apache.iceberg.spark.data.TestSparkAvroUnions.writeAndValidateRequiredComplexUnion(TestSparkAvroUnions.java:75)
```
##########
File path: spark/v3.2/spark/src/test/java/org/apache/iceberg/spark/data/TestSparkAvroUnions.java
##########
@@ -0,0 +1,272 @@
+/*
+ * Licensed 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.iceberg.spark.data;
+
+import java.io.File;
+import java.io.IOException;
+import java.util.Arrays;
+import java.util.List;
+import org.apache.avro.SchemaBuilder;
+import org.apache.avro.file.DataFileWriter;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericDatumWriter;
+import org.apache.iceberg.Files;
+import org.apache.iceberg.Schema;
+import org.apache.iceberg.avro.Avro;
+import org.apache.iceberg.avro.AvroIterable;
+import org.apache.iceberg.avro.AvroSchemaUtil;
+import org.apache.iceberg.relocated.com.google.common.collect.Lists;
+import org.apache.spark.sql.catalyst.InternalRow;
+import org.junit.Assert;
+import org.junit.Rule;
+import org.junit.Test;
+import org.junit.rules.TemporaryFolder;
+
+public class TestSparkAvroUnions {
Review comment:
Can we add a test case here to check for the output when only some fields within the union are projected?
##########
File path: core/src/main/java/org/apache/iceberg/avro/SchemaToType.java
##########
@@ -105,13 +106,27 @@ public Type record(Schema record, List<String> names, List<Type> fieldTypes) {
@Override
public Type union(Schema union, List<Type> options) {
- Preconditions.checkArgument(AvroSchemaUtil.isOptionSchema(union),
- "Unsupported type: non-option union: %s", union);
- // records, arrays, and maps will check nullability later
- if (options.get(0) == null) {
- return options.get(1);
+ if (AvroSchemaUtil.isOptionSchema(union)) {
+ // Optional simple union
+ // records, arrays, and maps will check nullability later
+ if (options.get(0) == null) {
+ return options.get(1);
+ } else {
+ return options.get(0);
+ }
} else {
- return options.get(0);
+ // Complex union
+ List<Types.NestedField> newFields = new ArrayList<>();
+ newFields.add(Types.NestedField.required(allocateId(), "tag", Types.IntegerType.get()));
+
+ int tagIndex = 0;
+ for (Type type : options) {
+ if (type != null) {
+ newFields.add(Types.NestedField.optional(allocateId(), "field" + tagIndex++, type));
+ }
Review comment:
Can you add the reasoning behind why the field names `tag` and `field${index}` were chosen when converting to struct? Spark's Avro datasources uses `member${index}` while Hive's `extract_union` UDF uses `tag_${index}`.
##########
File path: core/src/main/java/org/apache/iceberg/avro/AvroSchemaUtil.java
##########
@@ -154,6 +154,27 @@ public static boolean isOptionSchema(Schema schema) {
return false;
}
+ /**
+ * This method decides whether a schema is of type union and is complex union and is optional
+ *
+ * Complex union: the number of options in union not equals to 2
+ * Optional: null is present in union
+ *
+ * @param schema input schema
+ * @return true if schema is complex union and it is optional
+ */
+ public static boolean isOptionalComplexUnion(Schema schema) {
+ if (schema.getType() == UNION && schema.getTypes().size() != 2) {
Review comment:
What happens if it receives a schema like `["null"]`. This is regarded as an optional complex union by this function. Is this expected? Should we instead check for `schema.getTypes().size() > 2`. What is the impact of this return true on the readers?
##########
File path: core/src/main/java/org/apache/iceberg/avro/PruneColumns.java
##########
@@ -323,4 +325,19 @@ private static Schema makeEmptyCopy(Schema field) {
private static boolean isOptionSchemaWithNonNullFirstOption(Schema schema) {
return AvroSchemaUtil.isOptionSchema(schema) && schema.getTypes().get(0).getType() != Schema.Type.NULL;
}
+
+ // for primitive types, the visitResult will be null, we want to reuse the primitive types from the original
+ // schema, while for nested types, we want to use the visitResult because they have content from the previous
+ // recursive calls.
+ private static Schema copyUnion(Schema record, List<Schema> visitResults) {
Review comment:
It does not look we prune any columns in the complex union case. I tried modifying `TestSparkAvroUnions` to test projecting a single field from the complex union and it fails (error below). There are a couple of ways we can go about column pruning:
1. We should implement column pruning for complex unions. It should be okay to implement this as a followup PR, but in that case I think we should throw a better error message letting the user known that projecting fields within a complex union is not supported for now.
2. We can choose not to prune columns inside complex unions and rather let the engine handle the pruning. E.g. you can see a comment in `map()` => `// right now, maps can't be selected without values`. The `ReadBuilder`s might need to be handled to account for this change. We also need to make sure that the schema advertised by Iceberg to the engine does not prune these fields either. In Spark land, this would be the schema returned through `Scan.readSchema()`.
```
index (1) must be less than size (1)
java.lang.IndexOutOfBoundsException: index (1) must be less than size (1)
at org.apache.iceberg.relocated.com.google.common.base.Preconditions.checkElementIndex(Preconditions.java:1355)
at org.apache.iceberg.relocated.com.google.common.base.Preconditions.checkElementIndex(Preconditions.java:1337)
at org.apache.iceberg.relocated.com.google.common.collect.SingletonImmutableList.get(SingletonImmutableList.java:44)
at org.apache.iceberg.avro.AvroSchemaWithTypeVisitor.visitUnion(AvroSchemaWithTypeVisitor.java:98)
at org.apache.iceberg.avro.AvroSchemaWithTypeVisitor.visit(AvroSchemaWithTypeVisitor.java:41)
at org.apache.iceberg.avro.AvroSchemaWithTypeVisitor.visitRecord(AvroSchemaWithTypeVisitor.java:71)
at org.apache.iceberg.avro.AvroSchemaWithTypeVisitor.visit(AvroSchemaWithTypeVisitor.java:38)
at org.apache.iceberg.avro.AvroSchemaWithTypeVisitor.visit(AvroSchemaWithTypeVisitor.java:32)
at org.apache.iceberg.spark.data.SparkAvroReader.<init>(SparkAvroReader.java:57)
at org.apache.iceberg.spark.data.SparkAvroReader.<init>(SparkAvroReader.java:50)
at org.apache.iceberg.avro.Avro$ReadBuilder.lambda$build$1(Avro.java:652)
at org.apache.iceberg.avro.ProjectionDatumReader.newDatumReader(ProjectionDatumReader.java:79)
at org.apache.iceberg.avro.ProjectionDatumReader.setSchema(ProjectionDatumReader.java:69)
at org.apache.avro.file.DataFileStream.initialize(DataFileStream.java:133)
at org.apache.avro.file.DataFileReader.<init>(DataFileReader.java:130)
at org.apache.avro.file.DataFileReader.<init>(DataFileReader.java:122)
at org.apache.avro.file.DataFileReader.openReader(DataFileReader.java:66)
at org.apache.iceberg.avro.AvroIterable.newFileReader(AvroIterable.java:100)
at org.apache.iceberg.avro.AvroIterable.iterator(AvroIterable.java:77)
at org.apache.iceberg.avro.AvroIterable.iterator(AvroIterable.java:37)
at org.apache.iceberg.relocated.com.google.common.collect.Lists.newArrayList(Lists.java:133)
at org.apache.iceberg.spark.data.TestSparkAvroUnions.writeAndValidateRequiredComplexUnion(TestSparkAvroUnions.java:75)
```
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[GitHub] [iceberg] shardulm94 commented on a change in pull request #4242: Support non-optional union types for Avro and ORC
Posted by GitBox <gi...@apache.org>.
shardulm94 commented on a change in pull request #4242:
URL: https://github.com/apache/iceberg/pull/4242#discussion_r829345463
##########
File path: core/src/main/java/org/apache/iceberg/avro/PruneColumns.java
##########
@@ -323,4 +325,19 @@ private static Schema makeEmptyCopy(Schema field) {
private static boolean isOptionSchemaWithNonNullFirstOption(Schema schema) {
return AvroSchemaUtil.isOptionSchema(schema) && schema.getTypes().get(0).getType() != Schema.Type.NULL;
}
+
+ // for primitive types, the visitResult will be null, we want to reuse the primitive types from the original
+ // schema, while for nested types, we want to use the visitResult because they have content from the previous
+ // recursive calls.
+ private static Schema copyUnion(Schema record, List<Schema> visitResults) {
Review comment:
It does not look we prune any columns in the complex union case. I tried modifying `TestSparkAvroUnions` to test projecting a single field from the complex union and it fails (error below). There are a couple of ways we can go about column pruning:
1. We should implement column pruning for complex unions. It should be okay to implement this as a followup PR, but in that case I think we should throw a better error message letting the user known that projecting fields within a complex union is not supported for now.
2. We can choose not to prune columns inside complex unions and rather let the engine handle the pruning. E.g. you can see a comment in `map()` => `// right now, maps can't be selected without values`. The `ReadBuilder`s might need to be handled to account for this change. We also need to make sure that the schema advertised by Iceberg to the engine does not prune these fields either. In Spark land, this would be the schema returned through `Scan.readSchema()`.
```
index (1) must be less than size (1)
java.lang.IndexOutOfBoundsException: index (1) must be less than size (1)
at org.apache.iceberg.relocated.com.google.common.base.Preconditions.checkElementIndex(Preconditions.java:1355)
at org.apache.iceberg.relocated.com.google.common.base.Preconditions.checkElementIndex(Preconditions.java:1337)
at org.apache.iceberg.relocated.com.google.common.collect.SingletonImmutableList.get(SingletonImmutableList.java:44)
at org.apache.iceberg.avro.AvroSchemaWithTypeVisitor.visitUnion(AvroSchemaWithTypeVisitor.java:98)
at org.apache.iceberg.avro.AvroSchemaWithTypeVisitor.visit(AvroSchemaWithTypeVisitor.java:41)
at org.apache.iceberg.avro.AvroSchemaWithTypeVisitor.visitRecord(AvroSchemaWithTypeVisitor.java:71)
at org.apache.iceberg.avro.AvroSchemaWithTypeVisitor.visit(AvroSchemaWithTypeVisitor.java:38)
at org.apache.iceberg.avro.AvroSchemaWithTypeVisitor.visit(AvroSchemaWithTypeVisitor.java:32)
at org.apache.iceberg.spark.data.SparkAvroReader.<init>(SparkAvroReader.java:57)
at org.apache.iceberg.spark.data.SparkAvroReader.<init>(SparkAvroReader.java:50)
at org.apache.iceberg.avro.Avro$ReadBuilder.lambda$build$1(Avro.java:652)
at org.apache.iceberg.avro.ProjectionDatumReader.newDatumReader(ProjectionDatumReader.java:79)
at org.apache.iceberg.avro.ProjectionDatumReader.setSchema(ProjectionDatumReader.java:69)
at org.apache.avro.file.DataFileStream.initialize(DataFileStream.java:133)
at org.apache.avro.file.DataFileReader.<init>(DataFileReader.java:130)
at org.apache.avro.file.DataFileReader.<init>(DataFileReader.java:122)
at org.apache.avro.file.DataFileReader.openReader(DataFileReader.java:66)
at org.apache.iceberg.avro.AvroIterable.newFileReader(AvroIterable.java:100)
at org.apache.iceberg.avro.AvroIterable.iterator(AvroIterable.java:77)
at org.apache.iceberg.avro.AvroIterable.iterator(AvroIterable.java:37)
at org.apache.iceberg.relocated.com.google.common.collect.Lists.newArrayList(Lists.java:133)
at org.apache.iceberg.spark.data.TestSparkAvroUnions.writeAndValidateRequiredComplexUnion(TestSparkAvroUnions.java:75)
```
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[GitHub] [iceberg] funcheetah commented on pull request #4242: Support non-optional union types for Avro and ORC
Posted by GitBox <gi...@apache.org>.
funcheetah commented on pull request #4242:
URL: https://github.com/apache/iceberg/pull/4242#issuecomment-1062146680
@wmoustafa @shardulm94
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[GitHub] [iceberg] wmoustafa commented on a change in pull request #4242: Support non-optional union types for Avro and ORC
Posted by GitBox <gi...@apache.org>.
wmoustafa commented on a change in pull request #4242:
URL: https://github.com/apache/iceberg/pull/4242#discussion_r831514672
##########
File path: core/src/main/java/org/apache/iceberg/avro/PruneColumns.java
##########
@@ -323,4 +325,19 @@ private static Schema makeEmptyCopy(Schema field) {
private static boolean isOptionSchemaWithNonNullFirstOption(Schema schema) {
return AvroSchemaUtil.isOptionSchema(schema) && schema.getTypes().get(0).getType() != Schema.Type.NULL;
}
+
+ // for primitive types, the visitResult will be null, we want to reuse the primitive types from the original
+ // schema, while for nested types, we want to use the visitResult because they have content from the previous
+ // recursive calls.
+ private static Schema copyUnion(Schema record, List<Schema> visitResults) {
Review comment:
I think for now we should treat this as not supported, and continue to handle it in the next PR. That said, we should at least have a clear path and I agree on the error reporting change.
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[GitHub] [iceberg] shardulm94 commented on a change in pull request #4242: Support non-optional union types for Avro and ORC
Posted by GitBox <gi...@apache.org>.
shardulm94 commented on a change in pull request #4242:
URL: https://github.com/apache/iceberg/pull/4242#discussion_r829344056
##########
File path: core/src/main/java/org/apache/iceberg/avro/AvroSchemaUtil.java
##########
@@ -154,6 +154,27 @@ public static boolean isOptionSchema(Schema schema) {
return false;
}
+ /**
+ * This method decides whether a schema is of type union and is complex union and is optional
+ *
+ * Complex union: the number of options in union not equals to 2
+ * Optional: null is present in union
+ *
+ * @param schema input schema
+ * @return true if schema is complex union and it is optional
+ */
+ public static boolean isOptionalComplexUnion(Schema schema) {
+ if (schema.getType() == UNION && schema.getTypes().size() != 2) {
Review comment:
What happens if it receives a schema like `["null"]`. This is regarded as an optional complex union by this function. Is this expected? Should we instead check for `schema.getTypes().size() > 2`. What is the impact of this return true on the readers?
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[GitHub] [iceberg] wmoustafa commented on pull request #4242: Support non-optional union types for Avro and ORC
Posted by GitBox <gi...@apache.org>.
wmoustafa commented on pull request #4242:
URL: https://github.com/apache/iceberg/pull/4242#issuecomment-1063293895
FYI @rdblue @RussellSpitzer
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