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https://issues.apache.org/jira/browse/HIVE-20512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16655439#comment-16655439
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Sahil Takiar commented on HIVE-20512:
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A few comments:
(1) I think the logging should be done in a separate thread so that we don't
have to invoke {{logMemoryInfo()}} for each record, which can add significant
overhead to per-record processing
(2) I think we should start with a lower interval, something like 15 seconds
You could try and add a unit test that logs to a string buffers, and then parse
that string buffer in a unit test. However, I don't think its necessary.
CC: [~asinkovits]
> 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
>
>
> 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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