RussellSpitzer commented on code in PR #14948: URL: https://github.com/apache/iceberg/pull/14948#discussion_r3320782031
########## spark/v4.1/spark/src/main/java/org/apache/iceberg/spark/source/MergingSortedRowDataReader.java: ########## @@ -0,0 +1,298 @@ +/* + * 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.source; + +import java.io.IOException; +import java.io.UncheckedIOException; +import java.util.Arrays; +import java.util.Collections; +import java.util.Comparator; +import java.util.List; +import org.apache.iceberg.BaseScanTaskGroup; +import org.apache.iceberg.FileScanTask; +import org.apache.iceberg.ScanTaskGroup; +import org.apache.iceberg.Schema; +import org.apache.iceberg.SortField; +import org.apache.iceberg.SortOrder; +import org.apache.iceberg.SortOrderComparators; +import org.apache.iceberg.StructLike; +import org.apache.iceberg.Table; +import org.apache.iceberg.io.CloseableGroup; +import org.apache.iceberg.io.CloseableIterable; +import org.apache.iceberg.io.CloseableIterator; +import org.apache.iceberg.relocated.com.google.common.base.Preconditions; +import org.apache.iceberg.relocated.com.google.common.collect.Lists; +import org.apache.iceberg.spark.SparkSchemaUtil; +import org.apache.iceberg.spark.source.metrics.TaskNumDeletes; +import org.apache.iceberg.spark.source.metrics.TaskNumSplits; +import org.apache.iceberg.types.TypeUtil; +import org.apache.iceberg.types.Types; +import org.apache.iceberg.util.SortedMerge; +import org.apache.spark.sql.catalyst.InternalRow; +import org.apache.spark.sql.catalyst.expressions.GenericInternalRow; +import org.apache.spark.sql.connector.metric.CustomTaskMetric; +import org.apache.spark.sql.connector.read.PartitionReader; +import org.apache.spark.sql.types.DataType; +import org.apache.spark.sql.types.StructType; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +/** + * A {@link PartitionReader} that reads multiple sorted files and merges them into a single sorted + * stream using a k-way heap merge ({@link SortedMerge}). + * + * <p>This reader is used when {@code preserve-data-ordering} is enabled and the task group contains + * multiple files that all have the same sort order. + * + * <p>Sort key columns absent from the requested projection are temporarily added to the read schema + * so that {@link SortOrderComparators} can access them during the merge. The extra columns are + * stripped from each row before it is returned to Spark. + */ +class MergingSortedRowDataReader implements PartitionReader<InternalRow> { + private static final Logger LOG = LoggerFactory.getLogger(MergingSortedRowDataReader.class); + + private final CloseableGroup resources; + private final CloseableIterator<InternalRow> mergedIterator; + private final List<RowDataReader> fileReaders; + // non-null only when sort key columns were added to the read schema beyond what Spark projected + private final int[] outputPositions; + private final DataType[] outputDataTypes; + private final Object[] outputValues; // reused per row to avoid per-row allocation + private InternalRow current; + + MergingSortedRowDataReader(SparkInputPartition partition) { + Table table = partition.table(); + ScanTaskGroup<FileScanTask> taskGroup = partition.taskGroup(); + Schema projection = partition.projection(); + SortOrder sortOrder = table.sortOrder(); + + int numFiles = taskGroup.tasks().size(); + + Preconditions.checkState( + sortOrder.isSorted(), "Cannot create merging reader for unsorted table %s", table.name()); + Preconditions.checkState( + numFiles > 1, "Merging reader requires multiple files, got %s", numFiles); + + LOG.info( + "Creating merging reader for {} files with sort order {} in table {}", + numFiles, + sortOrder.orderId(), + table.name()); + + // Augment the projected schema with any sort key columns Spark did not request so that + // SortOrderComparators can access every sort key field during the merge. + Schema mergeReadSchema = mergeReadSchema(projection, sortOrder, table); + this.outputPositions = buildOutputPositions(projection, mergeReadSchema); + this.outputDataTypes = buildOutputDataTypes(projection, outputPositions); + this.outputValues = outputPositions != null ? new Object[outputPositions.length] : null; + + this.resources = new CloseableGroup(); + this.fileReaders = + taskGroup.tasks().stream() + .map( + task -> + new RowDataReader( + table, + partition.io(), + new BaseScanTaskGroup<>(Collections.singletonList(task)), + mergeReadSchema, + partition.isCaseSensitive(), + partition.cacheDeleteFilesOnExecutors())) + .toList(); + // Wrap each reader as a CloseableIterable and feed into SortedMerge. + List<CloseableIterable<InternalRow>> fileIterables = + fileReaders.stream().map(this::readerToIterable).toList(); + SortedMerge<InternalRow> sortedMerge = + new SortedMerge<>(buildComparator(mergeReadSchema, sortOrder), fileIterables); + resources.addCloseable(sortedMerge); + this.mergedIterator = sortedMerge.iterator(); + } + + /** + * Adapts a {@link RowDataReader} to a {@link CloseableIterable} for use with {@link SortedMerge}. + * Each row is copied before it enters the priority queue because Spark's Parquet/ORC readers + * reuse {@link InternalRow} instances for performance. + */ + private CloseableIterable<InternalRow> readerToIterable(RowDataReader reader) { + return CloseableIterable.withNoopClose( + () -> + new CloseableIterator<>() { + private boolean advanced = false; + private boolean hasNext = false; + + @Override + public boolean hasNext() { + if (!advanced) { + try { + hasNext = reader.next(); + advanced = true; + } catch (IOException e) { + throw new UncheckedIOException("Failed to advance reader", e); + } + } + return hasNext; + } + + @Override + public InternalRow next() { + if (!advanced) { + hasNext(); + } + advanced = false; + return reader.get().copy(); + } + + @Override + public void close() throws IOException { + reader.close(); + } + }); + } + + @Override + public boolean next() throws IOException { + if (!mergedIterator.hasNext()) { + return false; + } + + InternalRow merged = mergedIterator.next(); + if (outputPositions == null) { + this.current = merged; + } else { + // Strip the extra sort key columns that were added for comparison purposes. + for (int i = 0; i < outputPositions.length; i++) { + outputValues[i] = merged.get(outputPositions[i], outputDataTypes[i]); + } + this.current = new GenericInternalRow(outputValues); Review Comment: This is probably an uncessary allocation. The Spark contract allows us to re-use the container so rather than making an ew row each time we can just use a single wrapper and put new values in for each returned row. So do something like In initalizer make a MergedRow For each output, set the values in the merged row Return that over and over on each "get()" There are a few options for doing the wrapping without a copy (of even the field values) I don't think we have exactly the right thing already in Iceberg but essentially you want something like InternalRowWrapper(schema, mapping: Int -> Int) which does get(i) { internal.get(mapping[i])} There may be a better solution so think on it a bit Anyway, think about it. We definitely don't want to create a bunch of objects here when we are re-using containers in all of our readers -- 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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