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https://issues.apache.org/jira/browse/FLINK-4391?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15642997#comment-15642997
]
ASF GitHub Bot commented on FLINK-4391:
---------------------------------------
Github user bjlovegithub commented on a diff in the pull request:
https://github.com/apache/flink/pull/2629#discussion_r86709933
--- Diff:
flink-streaming-java/src/main/java/org/apache/flink/streaming/runtime/tasks/StreamTask.java
---
@@ -540,15 +540,12 @@ private boolean performCheckpoint(CheckpointMetaData
checkpointMetaData) throws
synchronized (lock) {
if (isRunning) {
+ checkpointState(checkpointMetaData);
- // Since both state checkpointing and
downstream barrier emission occurs in this
- // lock scope, they are an atomic operation
regardless of the order in which they occur.
- // Given this, we immediately emit the
checkpoint barriers, so the downstream operators
- // can start their checkpoint work as soon as
possible
+ // broadcast barriers after snapshot operators'
states.
operatorChain.broadcastCheckpointBarrier(
-
checkpointMetaData.getCheckpointId(), checkpointMetaData.getTimestamp());
-
- checkpointState(checkpointMetaData);
+
checkpointMetaData.getCheckpointId(), checkpointMetaData.getTimestamp()
+ );
--- End diff --
Can you share the test program and test result? I write an sample program
to test the performance to acquire and release lock with `Object` /
`ReentrantLock` / `ReentrantReadWriteLock`, finding that for one thread to use
the lock, they have similar results. But referring to multiple thread cases,
`ReentrantLock` and ` ReentrantReadWriteLock` excels `Object` lock.
Here is my benchmark program:
[link](https://github.com/bjlovegithub/JavaLockTest/blob/master/src/LockTest.java)
And this is the sampled results run on my laptop:
[stat](https://github.com/bjlovegithub/JavaLockTest/blob/master/stat/LockTest_result.data)
> Provide support for asynchronous operations over streams
> --------------------------------------------------------
>
> Key: FLINK-4391
> URL: https://issues.apache.org/jira/browse/FLINK-4391
> Project: Flink
> Issue Type: New Feature
> Components: DataStream API
> Reporter: Jamie Grier
> Assignee: david.wang
>
> Many Flink users need to do asynchronous processing driven by data from a
> DataStream. The classic example would be joining against an external
> database in order to enrich a stream with extra information.
> It would be nice to add general support for this type of operation in the
> Flink API. Ideally this could simply take the form of a new operator that
> manages async operations, keeps so many of them in flight, and then emits
> results to downstream operators as the async operations complete.
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