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Spark: Parallelize initializing readTasks when localityPreferred is true #2800

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rdblue merged 5 commits into from
Jul 12, 2021
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Spark: Parallelize initializing readTasks when localityPreferred is true #2800

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98fa40b
Spark: Parallelize initializing readTasks when localityPreferred is true
Jul 9, 2021
6887477
Fix thread-safe problem for array lists
Jul 10, 2021
1313fa9
Use arrays for spark2 to avoid synchronization
Jul 11, 2021
d30bc53
Remove unnecessary ExecutorService variables
Jul 12, 2021
0507bb3
Add parallelization to SparkMicroBatchStream#planInputPartitions
Jul 12, 2021
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39 changes: 24 additions & 15 deletions spark2/src/main/java/org/apache/iceberg/spark/source/Reader.java
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Original file line number Diff line number Diff line change
Expand Up @@ -21,6 +21,7 @@

import java.io.IOException;
import java.io.Serializable;
import java.util.Arrays;
import java.util.List;
import java.util.Locale;
import java.util.Map;
Expand Down Expand Up @@ -52,6 +53,8 @@
import org.apache.iceberg.spark.SparkSchemaUtil;
import org.apache.iceberg.util.PropertyUtil;
import org.apache.iceberg.util.TableScanUtil;
import org.apache.iceberg.util.Tasks;
import org.apache.iceberg.util.ThreadPools;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.broadcast.Broadcast;
import org.apache.spark.sql.RuntimeConfig;
Expand Down Expand Up @@ -205,15 +208,18 @@ public List<InputPartition<ColumnarBatch>> planBatchInputPartitions() {
// broadcast the table metadata as input partitions will be sent to executors
Broadcast<Table> tableBroadcast = sparkContext.broadcast(SerializableTable.copyOf(table));

List<InputPartition<ColumnarBatch>> readTasks = Lists.newArrayList();
for (CombinedScanTask task : tasks()) {
readTasks.add(new ReadTask<>(
task, tableBroadcast, expectedSchemaString, caseSensitive,
localityPreferred, new BatchReaderFactory(batchSize)));
}
LOG.info("Batching input partitions with {} tasks.", readTasks.size());
List<CombinedScanTask> scanTasks = tasks();
InputPartition<ColumnarBatch>[] readTasks = new InputPartition[scanTasks.size()];

Tasks.range(readTasks.length)
.stopOnFailure()
.executeWith(localityPreferred ? ThreadPools.getWorkerPool() : null)
.run(index -> readTasks[index] = new ReadTask<>(
scanTasks.get(index), tableBroadcast, expectedSchemaString, caseSensitive,
localityPreferred, new BatchReaderFactory(batchSize)));
LOG.info("Batching input partitions with {} tasks.", readTasks.length);

return readTasks;
return Arrays.asList(readTasks);
}

/**
Expand All @@ -226,14 +232,17 @@ public List<InputPartition<InternalRow>> planInputPartitions() {
// broadcast the table metadata as input partitions will be sent to executors
Broadcast<Table> tableBroadcast = sparkContext.broadcast(SerializableTable.copyOf(table));

List<InputPartition<InternalRow>> readTasks = Lists.newArrayList();
for (CombinedScanTask task : tasks()) {
readTasks.add(new ReadTask<>(
task, tableBroadcast, expectedSchemaString, caseSensitive,
localityPreferred, InternalRowReaderFactory.INSTANCE));
}
List<CombinedScanTask> scanTasks = tasks();
InputPartition<InternalRow>[] readTasks = new InputPartition[scanTasks.size()];

Tasks.range(readTasks.length)
.stopOnFailure()
.executeWith(localityPreferred ? ThreadPools.getWorkerPool() : null)
.run(index -> readTasks[index] = new ReadTask<>(
scanTasks.get(index), tableBroadcast, expectedSchemaString, caseSensitive,
localityPreferred, InternalRowReaderFactory.INSTANCE));

return readTasks;
return Arrays.asList(readTasks);
}

@Override
Expand Down
14 changes: 9 additions & 5 deletions spark3/src/main/java/org/apache/iceberg/spark/source/SparkBatchScan.java
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Expand Up @@ -40,6 +40,8 @@
import org.apache.iceberg.spark.SparkSchemaUtil;
import org.apache.iceberg.util.PropertyUtil;
import org.apache.iceberg.util.TableScanUtil;
import org.apache.iceberg.util.Tasks;
import org.apache.iceberg.util.ThreadPools;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.broadcast.Broadcast;
import org.apache.spark.sql.RuntimeConfig;
Expand Down Expand Up @@ -132,11 +134,13 @@ public InputPartition[] planInputPartitions() {

List<CombinedScanTask> scanTasks = tasks();
InputPartition[] readTasks = new InputPartition[scanTasks.size()];
for (int i = 0; i < scanTasks.size(); i++) {
readTasks[i] = new ReadTask(
scanTasks.get(i), tableBroadcast, expectedSchemaString,
caseSensitive, localityPreferred);
}

Tasks.range(readTasks.length)
.stopOnFailure()
.executeWith(localityPreferred ? ThreadPools.getWorkerPool() : null)
.run(index -> readTasks[index] = new ReadTask(
scanTasks.get(index), tableBroadcast, expectedSchemaString,
caseSensitive, localityPreferred));

return readTasks;
}
Expand Down
13 changes: 8 additions & 5 deletions spark3/src/main/java/org/apache/iceberg/spark/source/SparkMicroBatchStream.java
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Expand Up @@ -52,6 +52,8 @@
import org.apache.iceberg.util.PropertyUtil;
import org.apache.iceberg.util.SnapshotUtil;
import org.apache.iceberg.util.TableScanUtil;
import org.apache.iceberg.util.Tasks;
import org.apache.iceberg.util.ThreadPools;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.broadcast.Broadcast;
import org.apache.spark.sql.connector.read.InputPartition;
Expand Down Expand Up @@ -136,11 +138,12 @@ public InputPartition[] planInputPartitions(Offset start, Offset end) {
TableScanUtil.planTasks(splitTasks, splitSize, splitLookback, splitOpenFileCost));
InputPartition[] readTasks = new InputPartition[combinedScanTasks.size()];

for (int i = 0; i < combinedScanTasks.size(); i++) {
readTasks[i] = new ReadTask(
combinedScanTasks.get(i), tableBroadcast, expectedSchema,
caseSensitive, localityPreferred);
}
Tasks.range(readTasks.length)
.stopOnFailure()
.executeWith(localityPreferred ? ThreadPools.getWorkerPool() : null)
.run(index -> readTasks[index] = new ReadTask(
combinedScanTasks.get(index), tableBroadcast, expectedSchema,
caseSensitive, localityPreferred));

return readTasks;
}
Expand Down