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https://issues.apache.org/jira/browse/HIVE-20512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16648296#comment-16648296
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Sahil Takiar commented on HIVE-20512:
-------------------------------------
I mean time interval. So log the # of rows processed every few minutes (or
something like that). Perhaps an exponentially increasing interval would work
best so the logs don't explode.
> Improve record and memory usage logging in SparkRecordHandler
> -------------------------------------------------------------
>
> Key: HIVE-20512
> URL: https://issues.apache.org/jira/browse/HIVE-20512
> Project: Hive
> Issue Type: Sub-task
> Components: Spark
> Reporter: Sahil Takiar
> Priority: Major
>
> We currently log memory usage and # of records processed in Spark tasks, but
> we should improve the methodology for how frequently we log this info.
> Currently we use the following code:
> {code:java}
> private long getNextLogThreshold(long currentThreshold) {
> // A very simple counter to keep track of number of rows processed by the
> // reducer. It dumps
> // every 1 million times, and quickly before that
> if (currentThreshold >= 1000000) {
> return currentThreshold + 1000000;
> }
> return 10 * currentThreshold;
> }
> {code}
> The issue is that after a while, the increase by 10x factor means that you
> have to process a huge # of records before this gets triggered.
> A better approach would be to log this info at a given interval. This would
> help in debugging tasks that are seemingly hung.
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