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From "Antal Sinkovits (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HIVE-20512) Improve record and memory usage logging in SparkRecordHandler
Date Wed, 31 Oct 2018 23:26:00 GMT

    [ https://issues.apache.org/jira/browse/HIVE-20512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16670892#comment-16670892
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Antal Sinkovits commented on HIVE-20512:
----------------------------------------

LGTM

> 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
>            Assignee: Bharathkrishna Guruvayoor Murali
>            Priority: Major
>         Attachments: HIVE-20512.1.patch, HIVE-20512.2.patch, HIVE-20512.3.patch, HIVE-20512.4.patch,
HIVE-20512.5.patch, HIVE-20512.6.patch
>
>
> 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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