singhpk234 commented on code in PR #5143:
URL: https://github.com/apache/iceberg/pull/5143#discussion_r908119520
##########
spark/v3.2/spark/src/main/java/org/apache/iceberg/spark/source/SparkBatch.java:
##########
@@ -65,18 +63,24 @@ public InputPartition[] planInputPartitions() {
Broadcast<Table> tableBroadcast =
sparkContext.broadcast(SerializableTable.copyOf(table));
String expectedSchemaString = SchemaParser.toJson(expectedSchema);
- InputPartition[] readTasks = new InputPartition[tasks.size()];
+ InputPartition[] readTasks = new InputPartition[tasks().size()];
Tasks.range(readTasks.length)
.stopOnFailure()
.executeWith(localityEnabled ? ThreadPools.getWorkerPool() : null)
.run(index -> readTasks[index] = new ReadTask(
- tasks.get(index), tableBroadcast, expectedSchemaString,
+ tasks().get(index), tableBroadcast, expectedSchemaString,
Review Comment:
[minor] task() is synchronized, and we might be accessing here with a pool,
should remove synchronized from function def and make it like :
```
private volatile List<CombinedScanTask> tasks = null
protected List<CombinedScanTask> tasks() {
if (tasks == null) {
synchronized(this) {
if (tasks == null) {
task = // assign stuff to task
}
}
}
return tasks;
}
```
I think now we might also want to make `SparkFilesScan#task()` handle
multi-threading.
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