Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/16114#discussion_r91206300
--- Diff:
external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisRecordProcessor.scala
---
@@ -68,9 +69,16 @@ private[kinesis] class
KinesisRecordProcessor[T](receiver: KinesisReceiver[T], w
override def processRecords(batch: List[Record], checkpointer:
IRecordProcessorCheckpointer) {
if (!receiver.isStopped()) {
try {
- receiver.addRecords(shardId, batch)
- logDebug(s"Stored: Worker $workerId stored ${batch.size} records
for shardId $shardId")
- receiver.setCheckpointer(shardId, checkpointer)
+ // Limit the number of processed records from Kinesis stream. This
is because the KCL cannot
+ // control the number of aggregated records to be fetched even if
we set `MaxRecords`
+ // in `KinesisClientLibConfiguration`. For example, if we set 10
to the number of max
+ // records in a worker and a producer aggregates two records into
one message, the worker
+ // possibly 20 records every callback function called.
+ batch.asScala.grouped(receiver.getCurrentLimit).foreach { batch =>
+ receiver.addRecords(shardId, batch.asJava)
+ logDebug(s"Stored: Worker $workerId stored ${batch.size} records
for shardId $shardId")
+ receiver.setCheckpointer(shardId, checkpointer)
--- End diff --
Yeah, that's what I suspected at
https://github.com/apache/spark/pull/16114#discussion_r90756702 -- thanks for
confirming
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