FrankChen021 commented on code in PR #19510:
URL: https://github.com/apache/druid/pull/19510#discussion_r3294101280
##########
extensions-contrib/druid-iceberg-extensions/src/main/java/org/apache/druid/iceberg/input/IcebergInputSource.java:
##########
@@ -113,6 +125,16 @@ public InputSourceReader reader(
File temporaryDirectory
)
{
+ if (useArrowReader) {
Review Comment:
[P1] Arrow path bypasses residual FAIL handling
The useArrowReader branch returns an IcebergArrowInputSourceReader before
retrieveIcebergDatafiles() runs, so it skips the residual detection that
enforces residualFilterMode=FAIL. IcebergArrowInputSourceReaderTest documents
that a non-partition equality filter returns all rows from the file, so a spec
with useArrowReader=true and residualFilterMode=FAIL will silently ingest
residual rows instead of rejecting the ingestion. Please run the same residual
check for the Arrow scan or otherwise honor the fail mode before reading.
##########
extensions-contrib/druid-iceberg-extensions/src/main/java/org/apache/druid/iceberg/input/IcebergInputSource.java:
##########
@@ -113,6 +125,16 @@ public InputSourceReader reader(
File temporaryDirectory
)
{
+ if (useArrowReader) {
Review Comment:
[P2] Parallel ingestion bypasses the Arrow reader
This special case only affects direct reader() calls. The input source still
reports itself as splittable, and Druid's parallel task runners call
createSplits() and then withSplit(); withSplit() returns the delegate input
source, so subtasks read raw files through the old delegate path instead of
IcebergArrowInputSourceReader. With useArrowReader=true, behavior therefore
changes based on maxNumConcurrentSubTasks and can lose the Arrow path's Iceberg
semantics. Please make the Arrow mode non-splittable or return split-aware
Iceberg input sources that preserve useArrowReader.
##########
extensions-contrib/druid-iceberg-extensions/src/main/java/org/apache/druid/iceberg/input/IcebergArrowInputSourceReader.java:
##########
@@ -0,0 +1,383 @@
+/*
+ * 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.druid.iceberg.input;
+
+import com.google.common.collect.Maps;
+import org.apache.arrow.vector.BigIntVector;
+import org.apache.arrow.vector.BitVector;
+import org.apache.arrow.vector.DateDayVector;
+import org.apache.arrow.vector.DecimalVector;
+import org.apache.arrow.vector.FieldVector;
+import org.apache.arrow.vector.FixedSizeBinaryVector;
+import org.apache.arrow.vector.Float4Vector;
+import org.apache.arrow.vector.Float8Vector;
+import org.apache.arrow.vector.IntVector;
+import org.apache.arrow.vector.SmallIntVector;
+import org.apache.arrow.vector.TimeMicroVector;
+import org.apache.arrow.vector.TimeStampMicroTZVector;
+import org.apache.arrow.vector.TimeStampMicroVector;
+import org.apache.arrow.vector.TimeStampMilliTZVector;
+import org.apache.arrow.vector.TimeStampMilliVector;
+import org.apache.arrow.vector.TimeStampNanoTZVector;
+import org.apache.arrow.vector.TimeStampNanoVector;
+import org.apache.arrow.vector.TinyIntVector;
+import org.apache.arrow.vector.VarBinaryVector;
+import org.apache.arrow.vector.VarCharVector;
+import org.apache.druid.data.input.InputRow;
+import org.apache.druid.data.input.InputRowListPlusRawValues;
+import org.apache.druid.data.input.InputRowSchema;
+import org.apache.druid.data.input.InputSourceReader;
+import org.apache.druid.data.input.InputStats;
+import org.apache.druid.data.input.MapBasedInputRow;
+import org.apache.druid.iceberg.filter.IcebergFilter;
+import org.apache.druid.java.util.common.parsers.CloseableIterator;
+import org.apache.iceberg.CombinedScanTask;
+import org.apache.iceberg.Table;
+import org.apache.iceberg.TableScan;
+import org.apache.iceberg.arrow.vectorized.ArrowReader;
+import org.apache.iceberg.arrow.vectorized.ColumnarBatch;
+import org.apache.iceberg.io.CloseableIterable;
+import org.apache.iceberg.util.TableScanUtil;
+import org.joda.time.DateTime;
+
+import javax.annotation.Nullable;
+import java.io.IOException;
+import java.nio.charset.StandardCharsets;
+import java.util.ArrayList;
+import java.util.List;
+import java.util.Map;
+import java.util.NoSuchElementException;
+import java.util.concurrent.TimeUnit;
+
+/**
+ * Reads an Iceberg table via iceberg-arrow's {@link ArrowReader}, yielding
{@link InputRow} objects.
+ *
+ * Delete application (V2 equality and positional deletes), type coercion, and
schema evolution are
+ * handled entirely by the Iceberg library. Druid only consumes the resulting
{@link ColumnarBatch}
+ * batches and maps them to {@link MapBasedInputRow}.
+ *
+ * Column projection and predicate push-down are applied at scan planning time
so only requested
+ * columns and matching files are read from storage.
+ *
+ * Note: iceberg-arrow currently supports Parquet data files only. ORC and
Avro files will throw
+ * {@link UnsupportedOperationException} at read time; use the standard
delegate path for those.
+ */
+public class IcebergArrowInputSourceReader implements InputSourceReader
+{
+ static final int DEFAULT_BATCH_SIZE = 1024;
+
+ private final Table table;
+ @Nullable
+ private final IcebergFilter icebergFilter;
+ @Nullable
+ private final DateTime snapshotTime;
+ private final boolean caseSensitive;
+ private final InputRowSchema schema;
+ private final int batchSize;
+
+ public IcebergArrowInputSourceReader(
+ final Table table,
+ @Nullable final IcebergFilter icebergFilter,
+ @Nullable final DateTime snapshotTime,
+ final boolean caseSensitive,
+ final InputRowSchema schema,
+ final int batchSize
+ )
+ {
+ this.table = table;
+ this.icebergFilter = icebergFilter;
+ this.snapshotTime = snapshotTime;
+ this.caseSensitive = caseSensitive;
+ this.schema = schema;
+ this.batchSize = batchSize;
+ }
+
+ @Override
+ public CloseableIterator<InputRow> read(final InputStats inputStats) throws
IOException
+ {
+ final TableScan scan = buildScan();
+ final CloseableIterable<CombinedScanTask> tasks = TableScanUtil.planTasks(
+ scan.planFiles(),
+ scan.targetSplitSize(),
+ scan.splitLookback(),
+ scan.splitOpenFileCost()
+ );
+ final ArrowReader arrowReader = new ArrowReader(scan, batchSize, true);
+ final org.apache.iceberg.io.CloseableIterator<ColumnarBatch> batchIter =
arrowReader.open(tasks);
+ return new ArrowInputRowIterator(batchIter, arrowReader, tasks,
inputStats);
+ }
+
+ @Override
+ public CloseableIterator<InputRowListPlusRawValues> sample() throws
IOException
+ {
+ final CloseableIterator<InputRow> rows = read(new NoopInputStats());
+ return new CloseableIterator<InputRowListPlusRawValues>()
+ {
+ @Override
+ public boolean hasNext()
+ {
+ return rows.hasNext();
+ }
+
+ @Override
+ public InputRowListPlusRawValues next()
+ {
+ final InputRow row = rows.next();
+ return InputRowListPlusRawValues.of(row, ((MapBasedInputRow)
row).getEvent());
+ }
+
+ @Override
+ public void close() throws IOException
+ {
+ rows.close();
+ }
+ };
+ }
+
+ private TableScan buildScan()
+ {
+ TableScan scan = table.newScan().caseSensitive(caseSensitive);
+
+ // Push column projection into the scan planner — only requested columns
are read from disk.
+ final List<String> configuredDims =
schema.getDimensionsSpec().getDimensionNames();
+ final String timestampColumn =
schema.getTimestampSpec().getTimestampColumn();
+ if (!configuredDims.isEmpty()) {
Review Comment:
[P1] Projection omits required non-dimension columns
When fixed dimensions are configured, this projection selects only those
dimension names plus the timestamp column. Druid carries required transform
inputs and aggregator source fields through InputRowSchema.getColumnsFilter(),
not DimensionsSpec alone. For example, dimensions=[name] with an aggregator
over value will scan only ts/name, so value is missing from the event and
downstream metrics/transforms read null. Please drive projection from the full
columnsFilter/required fields, or avoid pruning when those required columns
cannot be represented safely.
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