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https://issues.apache.org/jira/browse/FLINK-4821?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15974231#comment-15974231
]
ASF GitHub Bot commented on FLINK-4821:
---------------------------------------
Github user tony810430 commented on a diff in the pull request:
https://github.com/apache/flink/pull/3001#discussion_r112132994
--- Diff:
flink-connectors/flink-connector-kinesis/src/main/java/org/apache/flink/streaming/connectors/kinesis/FlinkKinesisConsumer.java
---
@@ -194,26 +216,30 @@ public void run(SourceContext<T> sourceContext)
throws Exception {
// all subtasks will run a fetcher, regardless of whether or
not the subtask will initially have
// shards to subscribe to; fetchers will continuously poll for
changes in the shard list, so all subtasks
// can potentially have new shards to subscribe to later on
- fetcher = new KinesisDataFetcher<>(
- streams, sourceContext, getRuntimeContext(),
configProps, deserializer);
+ fetcher = createFetcher(streams, sourceContext,
getRuntimeContext(), configProps, deserializer);
boolean isRestoringFromFailure = (sequenceNumsToRestore !=
null);
fetcher.setIsRestoringFromFailure(isRestoringFromFailure);
// if we are restoring from a checkpoint, we iterate over the
restored
// state and accordingly seed the fetcher with subscribed
shards states
if (isRestoringFromFailure) {
--- End diff --
@tzulitai
Because the behavior in `KinesisDataFetcher.discoverNewShardsToSubscribe()`
will always discover new shards from the latest discovered shard id, that may
cause the problem if some subtasks miss to discover new shards before rescaling
and new subtasks also miss to discover those shards.
You can get the concrete example from comment for
`FlinkKinesisConsumerTest.testFetcherShouldBeCorrectlySeededWithNewDiscoveredKinesisStreamShard()`
> Implement rescalable non-partitioned state for Kinesis Connector
> ----------------------------------------------------------------
>
> Key: FLINK-4821
> URL: https://issues.apache.org/jira/browse/FLINK-4821
> Project: Flink
> Issue Type: New Feature
> Components: Kinesis Connector
> Reporter: Tzu-Li (Gordon) Tai
> Assignee: Wei-Che Wei
>
> FLINK-4379 added the rescalable non-partitioned state feature, along with the
> implementation for the Kafka connector.
> The AWS Kinesis connector will benefit from the feature and should implement
> it too. This ticket tracks progress for this.
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