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https://issues.apache.org/jira/browse/FLINK-4821?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15979749#comment-15979749
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ASF GitHub Bot commented on FLINK-4821:
---------------------------------------
Github user tzulitai commented on a diff in the pull request:
https://github.com/apache/flink/pull/3001#discussion_r112802078
--- Diff:
flink-connectors/flink-connector-kinesis/src/main/java/org/apache/flink/streaming/connectors/kinesis/FlinkKinesisConsumer.java
---
@@ -194,26 +212,30 @@ 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) {
- for (Map.Entry<KinesisStreamShard, SequenceNumber>
restored : lastStateSnapshot.entrySet()) {
+ List<KinesisStreamShard>
newShardsCreatedWhileNotRunning = fetcher.discoverNewShardsToSubscribe();
--- End diff --
We should add a comment within the code on why we need this.
> 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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