kbendick commented on a change in pull request #2803:
URL: https://github.com/apache/iceberg/pull/2803#discussion_r667568889
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File path: spark2/src/main/java/org/apache/iceberg/spark/source/Reader.java
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@@ -205,35 +215,62 @@ public StructType readSchema() {
// 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)));
+ int taskSize = tasks().size();
+ InputPartition<ColumnarBatch>[] readTasks = new InputPartition[taskSize];
+ Long startTime = System.currentTimeMillis();
+ try {
+ pool.submit(() -> IntStream.range(0, taskSize).parallel()
+ .mapToObj(taskId -> {
+ LOG.trace("The size of scanTasks is {}, current taskId is {},
current thread id is {}",
+ taskSize, taskId, Thread.currentThread().getName());
+ readTasks[taskId] = new ReadTask<>(
+ tasks().get(taskId), tableBroadcast,
expectedSchemaString, caseSensitive,
+ localityPreferred, new BatchReaderFactory(batchSize));
+ return true;
+ }).collect(Collectors.toList())).get();
+ } catch (Exception e) {
+ e.printStackTrace();
+ System.exit(-1);
}
- LOG.info("Batching input partitions with {} tasks.", readTasks.size());
-
- return readTasks;
+ Long endTime = System.currentTimeMillis();
+ LOG.info("Batching input partitions with {} tasks.", readTasks.length);
+ LOG.info("It took {} s to construct {} readTasks with localityPreferred =
{}.", (endTime - startTime) / 1000,
+ taskSize, localityPreferred);
+ return Arrays.asList(readTasks.clone());
}
/**
* This is called in the Spark Driver when data is to be materialized into
{@link InternalRow}
*/
+ @SuppressWarnings({"checkstyle:LocalVariableName",
"checkstyle:RegexpSinglelineJava"})
@Override
public List<InputPartition<InternalRow>> planInputPartitions() {
String expectedSchemaString = SchemaParser.toJson(lazySchema());
// 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));
+ int taskSize = tasks().size();
+ InputPartition<InternalRow>[] readTasks = new InputPartition[taskSize];
+ Long start_time = System.currentTimeMillis();
Review comment:
We don't use snake case (outside of the python code). This should be
startTime.
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