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Posted to issues@hive.apache.org by "Bharathkrishna Guruvayoor Murali (JIRA)" <ji...@apache.org> on 2018/10/16 17:54:00 UTC
[jira] [Updated] (HIVE-20512) Improve record and memory usage
logging in SparkRecordHandler
[ https://issues.apache.org/jira/browse/HIVE-20512?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Bharathkrishna Guruvayoor Murali updated HIVE-20512:
----------------------------------------------------
Attachment: HIVE-20512.1.patch
Status: Patch Available (was: Open)
[~stakiar] Can you please check the attached patch if this approach looks good.
I tried adding unit tests, but not sure if it is needed, as I should parse the log in a hard-coded way to check the String "processed " + rowNumber + " rows: used memory ="
and probably sleep() till the threshold to check if logs are printed again. What do you suggest?
> 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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