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Posted to issues@spark.apache.org by "Maryann Xue (JIRA)" <ji...@apache.org> on 2018/10/05 16:53:00 UTC
[jira] [Updated] (SPARK-25650) Make analyzer rules used in
once-policy idempotent
[ https://issues.apache.org/jira/browse/SPARK-25650?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Maryann Xue updated SPARK-25650:
--------------------------------
Issue Type: Task (was: Bug)
> Make analyzer rules used in once-policy idempotent
> --------------------------------------------------
>
> Key: SPARK-25650
> URL: https://issues.apache.org/jira/browse/SPARK-25650
> Project: Spark
> Issue Type: Task
> Components: SQL
> Affects Versions: 2.3.2
> Reporter: Maryann Xue
> Priority: Major
>
> Rules like {{HandleNullInputsForUDF}} (https://issues.apache.org/jira/browse/SPARK-24891) do not stabilize (can apply new changes to a plan indefinitely) and can cause problems like SQL cache mismatching.
> Ideally, all rules whether in a once-policy batch or a fixed-point-policy batch should stabilize after the number of runs specified. Once-policy should be considered a performance improvement, a assumption that the rule can stabilize after just one run rather than an assumption that the rule won't be applied more than once. Those once-policy rules should be able to run fine with fixed-point policy rule as well.
> Currently we already have a check for fixed-point and throws an exception if maximum number of runs is reached and the plan is still changing. Here, in this PR, a similar check is added for once-policy and throws an exception if the plan changes between the first run and the second run of a once-policy rule.
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