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https://issues.apache.org/jira/browse/IMPALA-6997?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Joe McDonnell resolved IMPALA-6997.
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Resolution: Fixed
Fix Version/s: Impala 3.1.0
Impala 2.13.0
> Query execution should notice UDF MemLimitExceeded errors more quickly
> ----------------------------------------------------------------------
>
> Key: IMPALA-6997
> URL: https://issues.apache.org/jira/browse/IMPALA-6997
> Project: IMPALA
> Issue Type: Bug
> Components: Backend
> Affects Versions: Impala 2.13.0
> Reporter: Joe McDonnell
> Assignee: Joe McDonnell
> Priority: Major
> Fix For: Impala 2.13.0, Impala 3.1.0
>
>
> When a UDF hits a memory limit, it calls RuntimeState::SetMemLimitExceeded()
> which sets the query status, but it has no way of returning status directly.
> It relies on the caller checking status periodically.
> HdfsTableSink::Send() checks for errors by calling
> RuntimeState::CheckQueryState() once at the beginning. If it is evaluating a
> UDF and that UDF hits the memory limit, it will need to process the whole
> RowBatch before it aborts the query. This could be 1024 rows and each row may
> hit a memory limit in that UDF. Other locations that process UDFs may be
> processing considerably more rows.
> There are two general approaches:
> # Code locations should check for status more frequently and thus abort
> faster after a RuntimeState::SetMemLImitExceeded() call.
> # RuntimeState::SetMemLimitExceeded() should be substantially cheaper,
> allowing the rows to be processed faster.
> RuntimeState::SetMemLimitExceeded() currently calls
> MemTracker::MemLimitExceeded() unconditionally. It then checks to see if it
> should update query_status_ (i.e. query_status_ is currently ok). Then it
> logs this error. This is wasteful, because MemTracker::MemLimitExceeded() is
> not a cheap function, and this is flooding the log for each row.
> RuntimeState::SetMemLimitExceeded() should check status before running
> MemTracker::MemoryLimitExceeded(). If query_status_ is already not ok, it can
> avoid the cost of the dump and logging.
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