Github user maropu commented on a diff in the pull request: https://github.com/apache/spark/pull/16114#discussion_r90754922 --- Diff: external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisRecordProcessor.scala --- @@ -56,6 +56,31 @@ private[kinesis] class KinesisRecordProcessor[T](receiver: KinesisReceiver[T], w logInfo(s"Initialized workerId $workerId with shardId $shardId") } + private def addRecords(batch: List[Record], checkpointer: IRecordProcessorCheckpointer): Unit = { + 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. + */ + private def processRecordsWithLimit( + batch: List[Record], checkpointer: IRecordProcessorCheckpointer): Unit = { + val maxRecords = receiver.getCurrentLimit + if (batch.size() <= maxRecords) { + addRecords(batch, checkpointer) --- End diff -- Aha, I see. I'll fix, thanks!
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