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https://issues.apache.org/jira/browse/FLINK-9374?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16481606#comment-16481606
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ASF GitHub Bot commented on FLINK-9374:
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Github user fmthoma commented on the issue:
https://github.com/apache/flink/pull/6021
@tzulitai I agree on adding additional docs, where do you suggest I should
put them? In the Javadoc on `setQueueLimit()`?
My current suggestion is to look at the size of your individual records,
and choose the queue limit so that about 10MB per shard are aggregated. 1MB
would be too small (since the KPL aggregates the user records to 1MB batches).
But I'll run some more performance tests, in particular also with the
`wait()`/`notify()` change you suggested above.
> Flink Kinesis Producer does not backpressure
> --------------------------------------------
>
> Key: FLINK-9374
> URL: https://issues.apache.org/jira/browse/FLINK-9374
> Project: Flink
> Issue Type: Bug
> Components: Kinesis Connector
> Reporter: Franz Thoma
> Priority: Critical
> Attachments: after.png, before.png
>
>
> The {{FlinkKinesisProducer}} just accepts records and forwards it to a
> {{KinesisProducer}} from the Amazon Kinesis Producer Library (KPL). The KPL
> internally holds an unbounded queue of records that have not yet been sent.
> Since Kinesis is rate-limited to 1MB per second per shard, this queue may
> grow indefinitely if Flink sends records faster than the KPL can forward them
> to Kinesis.
> One way to circumvent this problem is to set a record TTL, so that queued
> records are dropped after a certain amount of time, but this will lead to
> data loss under high loads.
> Currently the only time the queue is flushed is during checkpointing:
> {{FlinkKinesisProducer}} consumes records at arbitrary rate, either until a
> checkpoint is reached (and will wait until the queue is flushed), or until
> out-of-memory, whichever is reached first. (This gets worse due to the fact
> that the Java KPL is only a thin wrapper around a C++ process, so it is not
> even the Java process that runs out of memory, but the C++ process.) The
> implicit rate-limit due to checkpointing leads to a ragged throughput graph
> like this (the periods with zero throughput are the wait times before a
> checkpoint):
> !file:///home/fthoma/projects/flink/before.png!!before.png! Throughput
> limited by checkpointing only
> My proposed solution is to add a config option {{queueLimit}} to set a
> maximum number of records that may be waiting in the KPL queue. If this limit
> is reached, the {{FlinkKinesisProducer}} should trigger a {{flush()}} and
> wait (blocking) until the queue length is below the limit again. This
> automatically leads to backpressuring, since the {{FlinkKinesisProducer}}
> cannot accept records while waiting. For compatibility, {{queueLimit}} is set
> to {{Integer.MAX_VALUE}} by default, so the behavior is unchanged unless a
> client explicitly sets the value. Setting a »sane« default value is not
> possible unfortunately, since sensible values for the limit depend on the
> record size (the limit should be chosen so that about 10–100MB of records per
> shard are accumulated before flushing, otherwise the maximum Kinesis
> throughput may not be reached).
> !after.png! Throughput with a queue limit of 100000 records (the spikes are
> checkpoints, where the queue is still flushed completely)
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