huaxingao commented on code in PR #9841: URL: https://github.com/apache/iceberg/pull/9841#discussion_r1566753486
########## spark/v3.4/spark/src/main/java/org/apache/iceberg/spark/data/vectorized/comet/CometIcebergColumnarBatchReader.java: ########## @@ -0,0 +1,303 @@ +/* + * 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.vectorized.comet; + +import java.io.IOException; +import java.io.UncheckedIOException; +import java.util.Iterator; +import java.util.List; +import java.util.Map; +import org.apache.comet.parquet.AbstractColumnReader; +import org.apache.comet.parquet.BatchReader; +import org.apache.iceberg.Schema; +import org.apache.iceberg.data.DeleteFilter; +import org.apache.iceberg.deletes.PositionDeleteIndex; +import org.apache.iceberg.parquet.VectorizedReader; +import org.apache.iceberg.relocated.com.google.common.base.Preconditions; +import org.apache.iceberg.spark.SparkSchemaUtil; +import org.apache.iceberg.util.Pair; +import org.apache.parquet.column.page.PageReadStore; +import org.apache.parquet.hadoop.metadata.ColumnChunkMetaData; +import org.apache.parquet.hadoop.metadata.ColumnPath; +import org.apache.spark.sql.catalyst.InternalRow; +import org.apache.spark.sql.vectorized.ColumnVector; +import org.apache.spark.sql.vectorized.ColumnarBatch; + +/** + * {@link VectorizedReader} that returns Spark's {@link ColumnarBatch} to support Spark's vectorized + * read path. The {@link ColumnarBatch} returned is created by passing in the Arrow vectors + * populated via delegated read calls to {@linkplain CometIcebergColumnReader VectorReader(s)}. + */ +@SuppressWarnings("checkstyle:VisibilityModifier") +public class CometIcebergColumnarBatchReader implements VectorizedReader<ColumnarBatch> { + + private final CometIcebergColumnReader[] readers; + private final boolean hasIsDeletedColumn; + private DeleteFilter<InternalRow> deletes = null; + private long rowStartPosInBatch = 0; + private final BatchReader delegate; + + public CometIcebergColumnarBatchReader(List<VectorizedReader<?>> readers, Schema schema) { + this.readers = + readers.stream() + .map(CometIcebergColumnReader.class::cast) + .toArray(CometIcebergColumnReader[]::new); + this.hasIsDeletedColumn = + readers.stream().anyMatch(reader -> reader instanceof CometIcebergDeleteColumnReader); + + AbstractColumnReader[] abstractColumnReaders = new AbstractColumnReader[readers.size()]; + delegate = new BatchReader(abstractColumnReaders); + delegate.setSparkSchema(SparkSchemaUtil.convert(schema)); + } + + @Override + public void setRowGroupInfo( + PageReadStore pageStore, Map<ColumnPath, ColumnChunkMetaData> metaData, long rowPosition) { + for (int i = 0; i < readers.length; i++) { + try { + if (!(readers[i] instanceof CometIcebergConstantColumnReader) + && !(readers[i] instanceof CometIcebergPositionColumnReader) + && !(readers[i] instanceof CometIcebergDeleteColumnReader)) { + readers[i].reset(); + readers[i].setPageReader( + pageStore.getPageReader(((CometIcebergColumnReader) readers[i]).getDescriptor())); + } + } catch (IOException e) { + throw new UncheckedIOException("Failed to setRowGroupInfo for Comet vectorization", e); + } + } + + for (int i = 0; i < readers.length; i++) { + delegate.getColumnReaders()[i] = ((CometIcebergColumnReader) this.readers[i]).getDelegate(); + } + + this.rowStartPosInBatch = rowPosition; + } + + public void setDeleteFilter(DeleteFilter<InternalRow> deleteFilter) { + this.deletes = deleteFilter; + } + + @Override + public final ColumnarBatch read(ColumnarBatch reuse, int numRowsToRead) { + ColumnarBatch columnarBatch = new ColumnBatchLoader(numRowsToRead).loadDataToColumnBatch(); + rowStartPosInBatch += numRowsToRead; + return columnarBatch; + } + + @Override + public void setBatchSize(int batchSize) { + for (CometIcebergColumnReader reader : readers) { + if (reader != null) { + reader.setBatchSize(batchSize); + } + } + } + + @Override + public void close() { + for (CometIcebergColumnReader reader : readers) { + if (reader != null) { + reader.close(); + } + } + } + + private class ColumnBatchLoader { + private final int numRowsToRead; + // the rowId mapping to skip deleted rows for all column vectors inside a batch, it is null when + // there is no deletes + private int[] rowIdMapping; + // the array to indicate if a row is deleted or not, it is null when there is no "_deleted" + // metadata column + private boolean[] isDeleted; + + ColumnBatchLoader(int numRowsToRead) { + Preconditions.checkArgument( + numRowsToRead > 0, "Invalid number of rows to read: %s", numRowsToRead); + this.numRowsToRead = numRowsToRead; + if (hasIsDeletedColumn) { + isDeleted = new boolean[numRowsToRead]; + } + } + + ColumnarBatch loadDataToColumnBatch() { Review Comment: There are lots of overlap. I will put the common code in a base method and reuse. ########## spark/v3.4/spark/src/main/java/org/apache/iceberg/spark/data/vectorized/comet/CometIcebergColumnarBatchReader.java: ########## @@ -0,0 +1,303 @@ +/* + * 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.vectorized.comet; + +import java.io.IOException; +import java.io.UncheckedIOException; +import java.util.Iterator; +import java.util.List; +import java.util.Map; +import org.apache.comet.parquet.AbstractColumnReader; +import org.apache.comet.parquet.BatchReader; +import org.apache.iceberg.Schema; +import org.apache.iceberg.data.DeleteFilter; +import org.apache.iceberg.deletes.PositionDeleteIndex; +import org.apache.iceberg.parquet.VectorizedReader; +import org.apache.iceberg.relocated.com.google.common.base.Preconditions; +import org.apache.iceberg.spark.SparkSchemaUtil; +import org.apache.iceberg.util.Pair; +import org.apache.parquet.column.page.PageReadStore; +import org.apache.parquet.hadoop.metadata.ColumnChunkMetaData; +import org.apache.parquet.hadoop.metadata.ColumnPath; +import org.apache.spark.sql.catalyst.InternalRow; +import org.apache.spark.sql.vectorized.ColumnVector; +import org.apache.spark.sql.vectorized.ColumnarBatch; + +/** + * {@link VectorizedReader} that returns Spark's {@link ColumnarBatch} to support Spark's vectorized + * read path. The {@link ColumnarBatch} returned is created by passing in the Arrow vectors + * populated via delegated read calls to {@linkplain CometIcebergColumnReader VectorReader(s)}. + */ +@SuppressWarnings("checkstyle:VisibilityModifier") +public class CometIcebergColumnarBatchReader implements VectorizedReader<ColumnarBatch> { + + private final CometIcebergColumnReader[] readers; + private final boolean hasIsDeletedColumn; + private DeleteFilter<InternalRow> deletes = null; + private long rowStartPosInBatch = 0; + private final BatchReader delegate; + + public CometIcebergColumnarBatchReader(List<VectorizedReader<?>> readers, Schema schema) { + this.readers = + readers.stream() + .map(CometIcebergColumnReader.class::cast) + .toArray(CometIcebergColumnReader[]::new); + this.hasIsDeletedColumn = + readers.stream().anyMatch(reader -> reader instanceof CometIcebergDeleteColumnReader); + + AbstractColumnReader[] abstractColumnReaders = new AbstractColumnReader[readers.size()]; + delegate = new BatchReader(abstractColumnReaders); + delegate.setSparkSchema(SparkSchemaUtil.convert(schema)); + } + + @Override + public void setRowGroupInfo( + PageReadStore pageStore, Map<ColumnPath, ColumnChunkMetaData> metaData, long rowPosition) { + for (int i = 0; i < readers.length; i++) { + try { + if (!(readers[i] instanceof CometIcebergConstantColumnReader) + && !(readers[i] instanceof CometIcebergPositionColumnReader) + && !(readers[i] instanceof CometIcebergDeleteColumnReader)) { + readers[i].reset(); + readers[i].setPageReader( + pageStore.getPageReader(((CometIcebergColumnReader) readers[i]).getDescriptor())); + } + } catch (IOException e) { + throw new UncheckedIOException("Failed to setRowGroupInfo for Comet vectorization", e); + } + } + + for (int i = 0; i < readers.length; i++) { + delegate.getColumnReaders()[i] = ((CometIcebergColumnReader) this.readers[i]).getDelegate(); + } + + this.rowStartPosInBatch = rowPosition; + } + + public void setDeleteFilter(DeleteFilter<InternalRow> deleteFilter) { + this.deletes = deleteFilter; + } + + @Override + public final ColumnarBatch read(ColumnarBatch reuse, int numRowsToRead) { + ColumnarBatch columnarBatch = new ColumnBatchLoader(numRowsToRead).loadDataToColumnBatch(); + rowStartPosInBatch += numRowsToRead; + return columnarBatch; + } + + @Override + public void setBatchSize(int batchSize) { + for (CometIcebergColumnReader reader : readers) { + if (reader != null) { + reader.setBatchSize(batchSize); + } + } + } + + @Override + public void close() { + for (CometIcebergColumnReader reader : readers) { + if (reader != null) { + reader.close(); + } + } + } + + private class ColumnBatchLoader { + private final int numRowsToRead; + // the rowId mapping to skip deleted rows for all column vectors inside a batch, it is null when + // there is no deletes + private int[] rowIdMapping; + // the array to indicate if a row is deleted or not, it is null when there is no "_deleted" + // metadata column + private boolean[] isDeleted; + + ColumnBatchLoader(int numRowsToRead) { + Preconditions.checkArgument( + numRowsToRead > 0, "Invalid number of rows to read: %s", numRowsToRead); + this.numRowsToRead = numRowsToRead; + if (hasIsDeletedColumn) { + isDeleted = new boolean[numRowsToRead]; + } + } + + ColumnarBatch loadDataToColumnBatch() { + int numRowsUndeleted = initRowIdMapping(); + + ColumnVector[] arrowColumnVectors = readDataToColumnVectors(); + + ColumnarBatch newColumnarBatch = new ColumnarBatch(arrowColumnVectors); + newColumnarBatch.setNumRows(numRowsUndeleted); + + if (hasEqDeletes()) { + applyEqDelete(newColumnarBatch); + } + + if (hasIsDeletedColumn && rowIdMapping != null) { + // reset the row id mapping array, so that it doesn't filter out the deleted rows + for (int i = 0; i < numRowsToRead; i++) { + rowIdMapping[i] = i; + } + newColumnarBatch.setNumRows(numRowsToRead); + } + + if (hasIsDeletedColumn) { + readDeletedColumnIfNecessary(arrowColumnVectors); + } + + return newColumnarBatch; + } + + ColumnVector[] readDataToColumnVectors() { + ColumnVector[] columnVectors = new ColumnVector[readers.length]; + // Fetch rows for all readers in the delegate + delegate.nextBatch(numRowsToRead); + for (int i = 0; i < readers.length; i++) { + CometIcebergVector bv = ((CometIcebergColumnReader) readers[i]).getVector(); + bv.setDelegate(((CometIcebergColumnReader) readers[i]).getDelegate().currentBatch()); + bv.setRowIdMapping(rowIdMapping); + columnVectors[i] = bv; + } + + return columnVectors; + } + + boolean hasEqDeletes() { + return deletes != null && deletes.hasEqDeletes(); + } + + int initRowIdMapping() { + Pair<int[], Integer> posDeleteRowIdMapping = posDelRowIdMapping(); + if (posDeleteRowIdMapping != null) { + rowIdMapping = posDeleteRowIdMapping.first(); + return posDeleteRowIdMapping.second(); + } else { + rowIdMapping = initEqDeleteRowIdMapping(); + return numRowsToRead; + } + } + + Pair<int[], Integer> posDelRowIdMapping() { + if (deletes != null && deletes.hasPosDeletes()) { + return buildPosDelRowIdMapping(deletes.deletedRowPositions()); + } else { + return null; + } + } + + /** + * Build a row id mapping inside a batch, which skips deleted rows. Here is an example of how we + * delete 2 rows in a batch with 8 rows in total. [0,1,2,3,4,5,6,7] -- Original status of the + * row id mapping array [F,F,F,F,F,F,F,F] -- Original status of the isDeleted array Position + * delete 2, 6 [0,1,3,4,5,7,-,-] -- After applying position deletes [Set Num records to 6] + * [F,F,T,F,F,F,T,F] -- After applying position deletes + * + * @param deletedRowPositions a set of deleted row positions + * @return the mapping array and the new num of rows in a batch, null if no row is deleted + */ + Pair<int[], Integer> buildPosDelRowIdMapping(PositionDeleteIndex deletedRowPositions) { Review Comment: Will reuse the common code. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. 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