You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Mukul Murthy (JIRA)" <ji...@apache.org> on 2018/09/10 21:27:00 UTC
[jira] [Updated] (SPARK-25399) Reusing execution threads from
continuous processing for microbatch streaming can result in correctness
issues
[ https://issues.apache.org/jira/browse/SPARK-25399?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Mukul Murthy updated SPARK-25399:
---------------------------------
Priority: Major (was: Blocker)
> Reusing execution threads from continuous processing for microbatch streaming can result in correctness issues
> --------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-25399
> URL: https://issues.apache.org/jira/browse/SPARK-25399
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
> Affects Versions: 2.4.0
> Reporter: Mukul Murthy
> Priority: Major
>
> Continuous processing sets some thread local variables that, when read by a thread running a microbatch stream, may result in incorrect or no previous state being read and resulting in wrong answers. This was caught by a job running the StreamSuite tests, and only repros occasionally when the same threads are used.
> The issue is in StateStoreRDD.compute - when we compute currentVersion, we read from a thread local variable which is set by continuous processing threads. If this value is set, we then think we're on the wrong state version.
> I imagine very few people, if any, would run into this bug, because you'd have to use continuous processing and then microbatch processing in the same cluster. However, it can result in silent correctness issues, and it would be very difficult for someone to tell if they were impacted by this or not.
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org