anuragmantri commented on code in PR #14948:
URL: https://github.com/apache/iceberg/pull/14948#discussion_r3321910327
##########
spark/v4.1/spark/src/main/java/org/apache/iceberg/spark/source/SparkScan.java:
##########
@@ -366,7 +367,18 @@ public CustomMetric[] supportedCustomMetrics() {
};
}
+ protected boolean isOrderingEnabled() {
+ return false;
+ }
+
protected long adjustSplitSize(List<? extends ScanTask> tasks, long
splitSize) {
+ if (readConf.preserveDataOrdering() && readConf.preserveDataGrouping()) {
Review Comment:
Added `table.isSorted()` as additional condition for this since the
downstream code does not prevent the case you described since splits are
planned initially.
##########
spark/v4.1/spark/src/main/java/org/apache/iceberg/spark/source/SparkPartitioningAwareScan.java:
##########
@@ -123,6 +128,34 @@ public Partitioning outputPartitioning() {
}
}
+ @Override
+ public SortOrder[] outputOrdering() {
+ if (!isOrderingEnabled()) {
+ return new SortOrder[0];
+ }
+
+ org.apache.iceberg.SortOrder sortOrder = table().sortOrder();
+ SortOrder[] ordering = Spark3Util.toOrdering(sortOrder);
+ LOG.info(
+ "Reporting sort order {} for table {}: {}", sortOrder.orderId(),
table().name(), ordering);
+
+ return ordering;
+ }
+
+ @Override
+ protected boolean isOrderingEnabled() {
+ if (orderingEnabled == null) {
+ orderingEnabled =
+ !groupingKeyType().fields().isEmpty()
+ && preserveDataOrdering
+ && SortOrderAnalyzer.canReportOrdering(table(), taskGroups(),
groupingKeyType());
+ if (!orderingEnabled) {
+ LOG.info("Not reporting ordering for table {}", table().name());
Review Comment:
I added a validation check for this.
##########
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:
Thanks for the pointers. I found
[ProjectingInternalRow](https://github.com/apache/spark/blob/c0690c763bafabd08e7079d1137fa0a769a05bae/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/ProjectingInternalRow.scala#L29)
in spark which is already used in Iceberg for row lineage stuff. I used that
now to avoid copying values.
--
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.
To unsubscribe, e-mail: [email protected]
For queries about this service, please contact Infrastructure at:
[email protected]
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
