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Posted to issues@iceberg.apache.org by GitBox <gi...@apache.org> on 2020/07/29 08:01:01 UTC
[GitHub] [iceberg] chenjunjiedada commented on a change in pull request #1254: Parquet: Add row position reader
chenjunjiedada commented on a change in pull request #1254:
URL: https://github.com/apache/iceberg/pull/1254#discussion_r461321137
##########
File path: spark/src/test/java/org/apache/iceberg/spark/data/TestSparkParquetReadMetadataColumns.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.iceberg.spark.data;
+
+import java.io.File;
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Iterator;
+import java.util.List;
+import org.apache.arrow.vector.NullCheckingForGet;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.fs.Path;
+import org.apache.iceberg.Files;
+import org.apache.iceberg.MetadataColumns;
+import org.apache.iceberg.Schema;
+import org.apache.iceberg.expressions.Expression;
+import org.apache.iceberg.expressions.Expressions;
+import org.apache.iceberg.io.CloseableIterable;
+import org.apache.iceberg.io.FileAppender;
+import org.apache.iceberg.parquet.Parquet;
+import org.apache.iceberg.parquet.ParquetSchemaUtil;
+import org.apache.iceberg.relocated.com.google.common.collect.Lists;
+import org.apache.iceberg.spark.SparkSchemaUtil;
+import org.apache.iceberg.spark.data.vectorized.VectorizedSparkParquetReaders;
+import org.apache.iceberg.types.TypeUtil;
+import org.apache.iceberg.types.Types;
+import org.apache.parquet.ParquetReadOptions;
+import org.apache.parquet.hadoop.ParquetFileReader;
+import org.apache.parquet.hadoop.ParquetFileWriter;
+import org.apache.parquet.hadoop.metadata.BlockMetaData;
+import org.apache.parquet.hadoop.util.HadoopInputFile;
+import org.apache.spark.sql.catalyst.InternalRow;
+import org.apache.spark.sql.catalyst.expressions.GenericInternalRow;
+import org.apache.spark.sql.types.StructType;
+import org.apache.spark.unsafe.types.UTF8String;
+import org.junit.Assert;
+import org.junit.Before;
+import org.junit.Rule;
+import org.junit.Test;
+import org.junit.rules.TemporaryFolder;
+import org.junit.runner.RunWith;
+import org.junit.runners.Parameterized;
+
+import static org.apache.iceberg.types.Types.NestedField.required;
+
+@RunWith(Parameterized.class)
+public class TestSparkParquetReadMetadataColumns {
+ private static final Schema DATA_SCHEMA = new Schema(
+ required(100, "id", Types.LongType.get()),
+ required(101, "data", Types.StringType.get())
+ );
+
+ private static final Schema PROJECTION_SCHEMA = new Schema(
+ required(100, "id", Types.LongType.get()),
+ required(101, "data", Types.StringType.get()),
+ MetadataColumns.ROW_POSITION
+ );
+
+ private static final int NUM_ROWS = 1000;
+ private static final List<InternalRow> DATA_ROWS;
+ private static final List<InternalRow> EXPECTED_ROWS;
+ private static final int NUM_ROW_GROUPS = 10;
+ private static final int ROWS_PER_SPLIT = NUM_ROWS / NUM_ROW_GROUPS;
+
+ static {
+ DATA_ROWS = Lists.newArrayListWithCapacity(NUM_ROWS);
+ for (long i = 0; i < NUM_ROWS; i++) {
+ InternalRow row = new GenericInternalRow(DATA_SCHEMA.columns().size());
+ row.update(0, i);
+ row.update(1, UTF8String.fromString("str" + i));
+ DATA_ROWS.add(row);
+ }
+
+ EXPECTED_ROWS = Lists.newArrayListWithCapacity(NUM_ROWS);
+ for (long i = 0; i < NUM_ROWS; i++) {
+ InternalRow row = new GenericInternalRow(PROJECTION_SCHEMA.columns().size());
+ row.update(0, i);
+ row.update(1, UTF8String.fromString("str" + i));
+ row.update(2, i);
+ EXPECTED_ROWS.add(row);
+ }
+ }
+
+ @Parameterized.Parameters
+ public static Object[][] parameters() {
+ return new Object[][] {
+ new Object[] { false },
+ //new Object[] { true }
+ };
+ }
+
+ @Rule
+ public TemporaryFolder temp = new TemporaryFolder();
+
+ private boolean vectorized;
+ private File testFile;
+
+ public TestSparkParquetReadMetadataColumns(boolean vectorized) {
+ this.vectorized = vectorized;
+ }
+
+ @Before
+ public void writeFile() throws IOException {
+ List<Path> fileSplits = new ArrayList<>();
+ StructType struct = SparkSchemaUtil.convert(DATA_SCHEMA);
+ Configuration conf = new Configuration();
+
+ testFile = temp.newFile();
+ Assert.assertTrue("Delete should succeed", testFile.delete());
+ ParquetFileWriter parquetFileWriter = new ParquetFileWriter(
+ conf,
+ ParquetSchemaUtil.convert(DATA_SCHEMA, "testSchema"),
+ new Path(testFile.getAbsolutePath())
+ );
+
+ parquetFileWriter.start();
+ for (int i = 0; i < NUM_ROW_GROUPS; i += 1) {
+ File split = temp.newFile();
+ Assert.assertTrue("Delete should succeed", split.delete());
+ fileSplits.add(new Path(split.getAbsolutePath()));
+ try (FileAppender<InternalRow> writer = Parquet.write(Files.localOutput(split))
+ .createWriterFunc(msgType -> SparkParquetWriters.buildWriter(struct, msgType))
+ .schema(DATA_SCHEMA)
+ .overwrite()
+ .build()) {
+ writer.addAll(DATA_ROWS.subList(i * ROWS_PER_SPLIT, (i + 1) * ROWS_PER_SPLIT));
+ }
+ parquetFileWriter.appendFile(HadoopInputFile.fromPath(new Path(split.getAbsolutePath()), conf));
+ }
+ parquetFileWriter
+ .end(ParquetFileWriter.mergeMetadataFiles(fileSplits, conf).getFileMetaData().getKeyValueMetaData());
+ }
+
+ @Test
+ public void testReadRowNumbers() throws IOException {
+ readAndValidate(null, null, null, EXPECTED_ROWS);
+ }
+
+ @Test
+ public void testReadRowNumbersWithFilter() throws IOException {
+ // current iceberg support row group filter.
+ for (int i = 0; i < NUM_ROW_GROUPS; i += 1) {
+ readAndValidate(Expressions.greaterThanOrEqual("id", i * ROWS_PER_SPLIT), null, null,
+ EXPECTED_ROWS.subList(i * ROWS_PER_SPLIT, 1000));
+ }
+ }
+
+ @Test
+ public void testReadRowNumbersWithSplits() throws IOException {
+ ParquetFileReader fileReader = new ParquetFileReader(
+ HadoopInputFile.fromPath(new Path(testFile.getAbsolutePath()), new Configuration()),
+ ParquetReadOptions.builder().build());
+ List<BlockMetaData> rowGroups = fileReader.getRowGroups();
+ for (int i = 0; i < NUM_ROW_GROUPS; i += 1) {
+ readAndValidate(null,
+ rowGroups.get(i).getColumns().get(1).getStartingPos(),
+ rowGroups.get(i).getCompressedSize(),
+ EXPECTED_ROWS.subList(i * ROWS_PER_SPLIT, (i + 1) * ROWS_PER_SPLIT));
+ }
+ }
+
+ private void readAndValidate(Expression filter, Long splitStart, Long splitLength, List<InternalRow> expected)
+ throws IOException {
+ Schema projectionWithoutMetadataFields = TypeUtil.selectNot(PROJECTION_SCHEMA, MetadataColumns.metadataFieldIds());
Review comment:
Hmm, this is a copy-paste error. let me remove this at first. At least, I don't use any related logic right now.
##########
File path: spark/src/test/java/org/apache/iceberg/spark/data/TestSparkParquetReadMetadataColumns.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.iceberg.spark.data;
+
+import java.io.File;
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Iterator;
+import java.util.List;
+import org.apache.arrow.vector.NullCheckingForGet;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.fs.Path;
+import org.apache.iceberg.Files;
+import org.apache.iceberg.MetadataColumns;
+import org.apache.iceberg.Schema;
+import org.apache.iceberg.expressions.Expression;
+import org.apache.iceberg.expressions.Expressions;
+import org.apache.iceberg.io.CloseableIterable;
+import org.apache.iceberg.io.FileAppender;
+import org.apache.iceberg.parquet.Parquet;
+import org.apache.iceberg.parquet.ParquetSchemaUtil;
+import org.apache.iceberg.relocated.com.google.common.collect.Lists;
+import org.apache.iceberg.spark.SparkSchemaUtil;
+import org.apache.iceberg.spark.data.vectorized.VectorizedSparkParquetReaders;
+import org.apache.iceberg.types.TypeUtil;
+import org.apache.iceberg.types.Types;
+import org.apache.parquet.ParquetReadOptions;
+import org.apache.parquet.hadoop.ParquetFileReader;
+import org.apache.parquet.hadoop.ParquetFileWriter;
+import org.apache.parquet.hadoop.metadata.BlockMetaData;
+import org.apache.parquet.hadoop.util.HadoopInputFile;
+import org.apache.spark.sql.catalyst.InternalRow;
+import org.apache.spark.sql.catalyst.expressions.GenericInternalRow;
+import org.apache.spark.sql.types.StructType;
+import org.apache.spark.unsafe.types.UTF8String;
+import org.junit.Assert;
+import org.junit.Before;
+import org.junit.Rule;
+import org.junit.Test;
+import org.junit.rules.TemporaryFolder;
+import org.junit.runner.RunWith;
+import org.junit.runners.Parameterized;
+
+import static org.apache.iceberg.types.Types.NestedField.required;
+
+@RunWith(Parameterized.class)
+public class TestSparkParquetReadMetadataColumns {
+ private static final Schema DATA_SCHEMA = new Schema(
+ required(100, "id", Types.LongType.get()),
+ required(101, "data", Types.StringType.get())
+ );
+
+ private static final Schema PROJECTION_SCHEMA = new Schema(
+ required(100, "id", Types.LongType.get()),
+ required(101, "data", Types.StringType.get()),
+ MetadataColumns.ROW_POSITION
+ );
+
+ private static final int NUM_ROWS = 1000;
+ private static final List<InternalRow> DATA_ROWS;
+ private static final List<InternalRow> EXPECTED_ROWS;
+ private static final int NUM_ROW_GROUPS = 10;
+ private static final int ROWS_PER_SPLIT = NUM_ROWS / NUM_ROW_GROUPS;
+
+ static {
+ DATA_ROWS = Lists.newArrayListWithCapacity(NUM_ROWS);
+ for (long i = 0; i < NUM_ROWS; i++) {
+ InternalRow row = new GenericInternalRow(DATA_SCHEMA.columns().size());
+ row.update(0, i);
Review comment:
Nice catch! The split start should use the first column's starting pos other than the second one. I updated the UT to cover both `row.update(0, i)` and `row.update(0, 2*i)`.
##########
File path: parquet/src/main/java/org/apache/iceberg/parquet/ReadConf.java
##########
@@ -157,6 +164,23 @@ ParquetFileReader reader() {
return shouldSkip;
}
+ private Map<Long, Long> generateRowGroupsStartRowPos() {
Review comment:
The existing loop of row groups is based on the row group set that had been filtered with `options`. So we need to read the Parquet file without any filter to get each starting row position of row group.
##########
File path: parquet/src/main/java/org/apache/iceberg/parquet/ReadConf.java
##########
@@ -157,6 +164,23 @@ ParquetFileReader reader() {
return shouldSkip;
}
+ private Map<Long, Long> generateRowGroupsStartRowPos() {
+ ParquetFileReader fileReader = newReader(this.file, ParquetReadOptions.builder().build());
+ Map<Long, Long> offsetToStartRowPosMap = new HashMap<>();
+ long curRowCount = 0;
+ for (int i = 0; i < fileReader.getRowGroups().size(); i += 1) {
+ BlockMetaData meta = fileReader.getRowGroups().get(i);
+ offsetToStartRowPosMap.put(meta.getStartingPos(), curRowCount);
+ curRowCount += meta.getRowCount();
+ }
+
+ return offsetToStartRowPosMap;
+ }
+
+ long[] getRowGroupsStartRowPos() {
Review comment:
`startPositions` may confuse with `rowGroup.startingPosition`, how about `startRowPosititions`?
##########
File path: parquet/src/main/java/org/apache/iceberg/parquet/ParquetValueReader.java
##########
@@ -30,4 +30,6 @@
List<TripleIterator<?>> columns();
void setPageSource(PageReadStore pageStore);
+
+ default void setRowOffsetForRowGroup(long position) {}
Review comment:
I can change to that. Just one thing that do we mind to change the function signature in the public API?
##########
File path: spark/src/test/java/org/apache/iceberg/spark/data/TestSparkParquetReadMetadataColumns.java
##########
@@ -0,0 +1,227 @@
+/*
+ * 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.iceberg.spark.data;
+
+import java.io.File;
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Iterator;
+import java.util.List;
+import org.apache.arrow.vector.NullCheckingForGet;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.fs.Path;
+import org.apache.iceberg.Files;
+import org.apache.iceberg.MetadataColumns;
+import org.apache.iceberg.Schema;
+import org.apache.iceberg.expressions.Expression;
+import org.apache.iceberg.expressions.Expressions;
+import org.apache.iceberg.io.CloseableIterable;
+import org.apache.iceberg.io.FileAppender;
+import org.apache.iceberg.parquet.Parquet;
+import org.apache.iceberg.parquet.ParquetSchemaUtil;
+import org.apache.iceberg.relocated.com.google.common.collect.Lists;
+import org.apache.iceberg.spark.SparkSchemaUtil;
+import org.apache.iceberg.spark.data.vectorized.VectorizedSparkParquetReaders;
+import org.apache.iceberg.types.Types;
+import org.apache.parquet.ParquetReadOptions;
+import org.apache.parquet.hadoop.ParquetFileReader;
+import org.apache.parquet.hadoop.ParquetFileWriter;
+import org.apache.parquet.hadoop.metadata.BlockMetaData;
+import org.apache.parquet.hadoop.util.HadoopInputFile;
+import org.apache.spark.sql.catalyst.InternalRow;
+import org.apache.spark.sql.catalyst.expressions.GenericInternalRow;
+import org.apache.spark.sql.types.StructType;
+import org.apache.spark.unsafe.types.UTF8String;
+import org.junit.Assert;
+import org.junit.Before;
+import org.junit.Rule;
+import org.junit.Test;
+import org.junit.rules.TemporaryFolder;
+import org.junit.runner.RunWith;
+import org.junit.runners.Parameterized;
+
+import static org.apache.iceberg.types.Types.NestedField.required;
+
+@RunWith(Parameterized.class)
+public class TestSparkParquetReadMetadataColumns {
+ private static final Schema DATA_SCHEMA = new Schema(
+ required(100, "id", Types.LongType.get()),
+ required(101, "data", Types.StringType.get())
+ );
+
+ private static final Schema PROJECTION_SCHEMA = new Schema(
+ required(100, "id", Types.LongType.get()),
+ required(101, "data", Types.StringType.get()),
+ MetadataColumns.ROW_POSITION
+ );
+
+ private static final int NUM_ROWS = 1000;
+ private static final List<InternalRow> DATA_ROWS;
+ private static final List<InternalRow> EXPECTED_ROWS;
+ private static final int NUM_ROW_GROUPS = 10;
+ private static final int ROWS_PER_SPLIT = NUM_ROWS / NUM_ROW_GROUPS;
+
+ static {
+ DATA_ROWS = Lists.newArrayListWithCapacity(NUM_ROWS);
+ for (long i = 0; i < NUM_ROWS; i += 1) {
+ InternalRow row = new GenericInternalRow(DATA_SCHEMA.columns().size());
+ if (i >= 500) {
+ row.update(0, 2 * i);
+ } else {
+ row.update(0, i);
+ }
+ row.update(1, UTF8String.fromString("str" + i));
+ DATA_ROWS.add(row);
+ }
+
+ EXPECTED_ROWS = Lists.newArrayListWithCapacity(NUM_ROWS);
+ for (long i = 0; i < NUM_ROWS; i += 1) {
+ InternalRow row = new GenericInternalRow(PROJECTION_SCHEMA.columns().size());
+ if (i >= 500) {
+ row.update(0, 2 * i);
+ } else {
+ row.update(0, i);
+ }
+ row.update(1, UTF8String.fromString("str" + i));
+ row.update(2, i);
+ EXPECTED_ROWS.add(row);
+ }
+ }
+
+ @Parameterized.Parameters
+ public static Object[][] parameters() {
+ return new Object[][] {
+ new Object[] { false },
+ //new Object[] { true }
+ };
+ }
+
+ @Rule
+ public TemporaryFolder temp = new TemporaryFolder();
+
+ private boolean vectorized;
+ private File testFile;
+
+ public TestSparkParquetReadMetadataColumns(boolean vectorized) {
+ this.vectorized = vectorized;
+ }
+
+ @Before
+ public void writeFile() throws IOException {
+ List<Path> fileSplits = new ArrayList<>();
+ StructType struct = SparkSchemaUtil.convert(DATA_SCHEMA);
+ Configuration conf = new Configuration();
+
+ testFile = temp.newFile();
+ Assert.assertTrue("Delete should succeed", testFile.delete());
+ ParquetFileWriter parquetFileWriter = new ParquetFileWriter(
+ conf,
+ ParquetSchemaUtil.convert(DATA_SCHEMA, "testSchema"),
+ new Path(testFile.getAbsolutePath())
+ );
+
+ parquetFileWriter.start();
+ for (int i = 0; i < NUM_ROW_GROUPS; i += 1) {
+ File split = temp.newFile();
+ Assert.assertTrue("Delete should succeed", split.delete());
+ fileSplits.add(new Path(split.getAbsolutePath()));
+ try (FileAppender<InternalRow> writer = Parquet.write(Files.localOutput(split))
+ .createWriterFunc(msgType -> SparkParquetWriters.buildWriter(struct, msgType))
+ .schema(DATA_SCHEMA)
+ .overwrite()
+ .build()) {
+ writer.addAll(DATA_ROWS.subList(i * ROWS_PER_SPLIT, (i + 1) * ROWS_PER_SPLIT));
+ }
+ parquetFileWriter.appendFile(HadoopInputFile.fromPath(new Path(split.getAbsolutePath()), conf));
+ }
+ parquetFileWriter
+ .end(ParquetFileWriter.mergeMetadataFiles(fileSplits, conf).getFileMetaData().getKeyValueMetaData());
+ }
+
+ @Test
+ public void testReadRowNumbers() throws IOException {
+ readAndValidate(null, null, null, EXPECTED_ROWS);
+ }
+
+ @Test
+ public void testReadRowNumbersWithFilter() throws IOException {
+ // current iceberg supports row group filter.
+ for (int i = 1; i < 5; i += 1) {
+ readAndValidate(
+ Expressions.and(Expressions.lessThan("id", 500),
+ Expressions.greaterThanOrEqual("id", i * ROWS_PER_SPLIT)),
+ null,
+ null,
+ EXPECTED_ROWS.subList(i * ROWS_PER_SPLIT, 500));
+ }
+ }
+
+ @Test
+ public void testReadRowNumbersWithSplits() throws IOException {
+ ParquetFileReader fileReader = new ParquetFileReader(
+ HadoopInputFile.fromPath(new Path(testFile.getAbsolutePath()), new Configuration()),
+ ParquetReadOptions.builder().build());
+ List<BlockMetaData> rowGroups = fileReader.getRowGroups();
+ for (int i = 0; i < NUM_ROW_GROUPS; i += 1) {
+ readAndValidate(null,
+ rowGroups.get(i).getColumns().get(0).getStartingPos(),
+ rowGroups.get(i).getCompressedSize(),
+ EXPECTED_ROWS.subList(i * ROWS_PER_SPLIT, (i + 1) * ROWS_PER_SPLIT));
+ }
+ }
+
+ private void readAndValidate(Expression filter, Long splitStart, Long splitLength, List<InternalRow> expected)
+ throws IOException {
+ CloseableIterable<InternalRow> reader = null;
+ try {
+ Parquet.ReadBuilder builder = Parquet.read(Files.localInput(testFile))
+ .project(PROJECTION_SCHEMA);
+
+ if (vectorized) {
+ builder.createBatchedReaderFunc(fileSchema -> VectorizedSparkParquetReaders.buildReader(PROJECTION_SCHEMA,
+ fileSchema, NullCheckingForGet.NULL_CHECKING_ENABLED));
+ } else {
+ builder = builder.createReaderFunc(msgType -> SparkParquetReaders.buildReader(PROJECTION_SCHEMA, msgType));
+ }
+
+ if (filter != null) {
+ builder = builder.filter(filter);
+ }
+
+ if (splitStart != null && splitLength != null) {
+ builder = builder.split(splitStart, splitLength);
+ }
+
+ reader = builder.build();
+
+ final Iterator<InternalRow> actualRows = reader.iterator();
+
+ for (InternalRow internalRow : expected) {
+ Assert.assertTrue("Should have expected number of rows", actualRows.hasNext());
+ TestHelpers.assertEquals(PROJECTION_SCHEMA, internalRow, actualRows.next());
+ }
+ Assert.assertFalse("Should not have extra rows", actualRows.hasNext());
+ } finally {
+ if (reader != null) {
+ reader.close();
Review comment:
Done.
##########
File path: parquet/src/main/java/org/apache/iceberg/parquet/ParquetValueReaders.java
##########
@@ -137,6 +137,41 @@ public void setPageSource(PageReadStore pageStore) {
}
}
+ static class PositionReader implements ParquetValueReader<Long> {
+ private long rowOffsetInCurrentRowGroup = -1;
+ private long rowGroupRowOffsetInFile;
Review comment:
Done.
##########
File path: parquet/src/main/java/org/apache/iceberg/parquet/ParquetValueReaders.java
##########
@@ -137,6 +137,41 @@ public void setPageSource(PageReadStore pageStore) {
}
}
+ static class PositionReader implements ParquetValueReader<Long> {
+ private long rowOffsetInCurrentRowGroup = -1;
+ private long rowGroupRowOffsetInFile;
+
+ @Override
+ public Long read(Long reuse) {
+ rowOffsetInCurrentRowGroup = rowOffsetInCurrentRowGroup + 1;
+ return rowGroupRowOffsetInFile + rowOffsetInCurrentRowGroup;
+ }
+
+ @Override
+ public TripleIterator<?> column() {
+ return NullReader.NULL_COLUMN;
+ }
+
+ @Override
+ public List<TripleIterator<?>> columns() {
+ return NullReader.COLUMNS;
+ }
+
+ @Override
+ public void setPageSource(PageReadStore pageStore) {
+ }
+
+ @Override
+ public void setRowOffsetForRowGroup(long rowGroupStartPos) {
+ this.rowGroupRowOffsetInFile = rowGroupStartPos;
+ this.rowOffsetInCurrentRowGroup = -1;
+ }
+ }
+
+ public static ParquetValueReader<Long> position() {
+ return new PositionReader();
+ }
Review comment:
Done.
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