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https://issues.apache.org/jira/browse/FLINK-7508?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16166709#comment-16166709
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ASF GitHub Bot commented on FLINK-7508:
---------------------------------------
Github user bowenli86 commented on a diff in the pull request:
https://github.com/apache/flink/pull/4656#discussion_r138965647
--- Diff:
flink-connectors/flink-connector-kinesis/src/main/java/org/apache/flink/streaming/connectors/kinesis/FlinkKinesisProducer.java
---
@@ -171,8 +171,9 @@ public void open(Configuration parameters) throws
Exception {
super.open(parameters);
// check and pass the configuration properties
- KinesisProducerConfiguration producerConfig =
KinesisConfigUtil.validateProducerConfiguration(configProps);
+ KinesisProducerConfiguration producerConfig =
KinesisConfigUtil.getValidatedProducerConfiguration(configProps);
producerConfig.setCredentialsProvider(AWSUtil.getCredentialsProvider(configProps));
+
producerConfig.setThreadingModel(KinesisProducerConfiguration.ThreadingModel.POOLED);
--- End diff --
On a second thought for this. Though I believe POOLED model is the best
option for most of the use cases I can think of, we should give users the
flexibility to make decisions.
Adding PER_REQUEST model
> switch FlinkKinesisProducer to use KPL's ThreadingMode to ThreadedPool mode
> rather than Per_Request mode
> --------------------------------------------------------------------------------------------------------
>
> Key: FLINK-7508
> URL: https://issues.apache.org/jira/browse/FLINK-7508
> Project: Flink
> Issue Type: Improvement
> Components: Kinesis Connector
> Affects Versions: 1.3.0
> Reporter: Bowen Li
> Assignee: Bowen Li
> Priority: Critical
> Fix For: 1.4.0
>
>
> KinesisProducerLibrary (KPL) 0.10.x had been using a
> One-New-Thread-Per-Request model for all requests sent to AWS Kinesis, which
> is very expensive.
> 0.12.4 introduced a new [ThreadingMode -
> Pooled|https://github.com/awslabs/amazon-kinesis-producer/blob/master/java/amazon-kinesis-producer/src/main/java/com/amazonaws/services/kinesis/producer/KinesisProducerConfiguration.java#L225],
> which will use a thread pool. This hugely improves KPL's performance and
> reduces consumed resources. By default, KPL still uses per-request mode. We
> should explicitly switch FlinkKinesisProducer's KPL threading mode to
> 'Pooled'.
> This work depends on FLINK-7366 and FLINK-7508
> Benchmarking I did:
> * Environment: Running a Flink hourly-sliding windowing job on 18-node EMR
> cluster with R4.2xlarge instances. Each hourly-sliding window in the Flink
> job generates about 21million UserRecords, which means that we generated a
> test load of 21million UserRecords at the first minute of each hour.
> * Criteria: Test KPL throughput per minute. Since the default RecordTTL for
> KPL is 30 sec, we can be sure that either all UserRecords are sent by KPL
> within a minute, or we will see UserRecord expiration errors.
> * One-New-Thread-Per-Request model: max throughput is about 2million
> UserRecords per min; it doesn't go beyond that because CPU utilization goes
> to 100%, everything stopped working and that Flink job crashed.
> * Thread-Pool model with pool size of 10: it sends out 21million UserRecords
> within 30 sec without any UserRecord expiration errors. The average peak CPU
> utilization is about 20% - 30%. So 21million UserRecords/min is not the max
> throughput of thread-pool model. We didn't go any further because 1) this
> throughput is already a couple times more than what we really need, and 2) we
> don't have a quick way of increasing the test load
> Thus, I propose switching FlinkKinesisProducer to Thread-Pool mode.
> [~tzulitai] What do you think
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