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Posted to issues@spark.apache.org by "Hyukjin Kwon (Jira)" <ji...@apache.org> on 2019/10/08 05:44:20 UTC
[jira] [Resolved] (SPARK-25377) spark sql dataframe cache is
invalid
[ https://issues.apache.org/jira/browse/SPARK-25377?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon resolved SPARK-25377.
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Resolution: Incomplete
> spark sql dataframe cache is invalid
> ------------------------------------
>
> Key: SPARK-25377
> URL: https://issues.apache.org/jira/browse/SPARK-25377
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.3.0
> Environment: spark version 2.3.0
> scala version 2.1.8
> Reporter: Iverson Hu
> Priority: Major
> Labels: bulk-closed
>
> When I use SQL dataframe in application, I found that dataframe.cache is invalid, the first time to execute Action like count() took me 40 seconds, and the seconds time to execute Action also.So I use dataframe.rdd.cache, second execution time is less than first execution time. And I think it's SQL dataframe's bug.
> This is my codes and console log, and I have cached the datafame of result before.
> this is my codes
> logger.info("start to consuming result count")
> logger.info(s"consuming ${result.count} output records")
> //result.show(false)
> logger.info("starting go to MysqlSink")
> logger.info(s"consuming ${result.count} output records")
> logger.info("starting go to MysqlSink")
>
> And console log is below
> 18/09/08 14:15:17 INFO MySQLRiskScenarioRunner: start to consuming result count
> 18/09/08 14:15:49 INFO MySQLRiskScenarioRunner: consuming 5 output records
> 18/09/08 14:15:49 INFO MySQLRiskScenarioRunner: starting go to MysqlSink
> 18/09/08 14:16:22 INFO MySQLRiskScenarioRunner: consuming 5 output records
> 18/09/08 14:16:22 INFO MySQLRiskScenarioRunner: starting go to MysqlSink
>
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>
>
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>
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