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author | jerryshao <sshao@hortonworks.com> | 2016-06-29 08:17:27 -0500 |
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committer | Tom Graves <tgraves@yahoo-inc.com> | 2016-06-29 08:17:27 -0500 |
commit | 272a2f78f3ff801b94a81fa8fcc6633190eaa2f4 (patch) | |
tree | 116630944456f0dbc3599d82694239c4e2a67c54 /docs | |
parent | 393db655c3c43155305fbba1b2f8c48a95f18d93 (diff) | |
download | spark-272a2f78f3ff801b94a81fa8fcc6633190eaa2f4.tar.gz spark-272a2f78f3ff801b94a81fa8fcc6633190eaa2f4.tar.bz2 spark-272a2f78f3ff801b94a81fa8fcc6633190eaa2f4.zip |
[SPARK-15990][YARN] Add rolling log aggregation support for Spark on yarn
## What changes were proposed in this pull request?
Yarn supports rolling log aggregation since 2.6, previously log will only be aggregated to HDFS after application is finished, it is quite painful for long running applications like Spark Streaming, thriftserver. Also out of disk problem will be occurred when log file is too large. So here propose to add support of rolling log aggregation for Spark on yarn.
One limitation for this is that log4j should be set to change to file appender, now in Spark itself uses console appender by default, in which file will not be created again once removed after aggregation. But I think lots of production users should have changed their log4j configuration instead of default on, so this is not a big problem.
## How was this patch tested?
Manually verified with Hadoop 2.7.1.
Author: jerryshao <sshao@hortonworks.com>
Closes #13712 from jerryshao/SPARK-15990.
Diffstat (limited to 'docs')
-rw-r--r-- | docs/running-on-yarn.md | 24 |
1 files changed, 24 insertions, 0 deletions
diff --git a/docs/running-on-yarn.md b/docs/running-on-yarn.md index dbd46cc48c..4e92042da6 100644 --- a/docs/running-on-yarn.md +++ b/docs/running-on-yarn.md @@ -472,6 +472,30 @@ To use a custom metrics.properties for the application master and executors, upd Currently supported services are: <code>hive</code>, <code>hbase</code> </td> </tr> +<tr> + <td><code>spark.yarn.rolledLog.includePattern</code></td> + <td>(none)</td> + <td> + Java Regex to filter the log files which match the defined include pattern + and those log files will be aggregated in a rolling fashion. + This will be used with YARN's rolling log aggregation, to enable this feature in YARN side + <code>yarn.nodemanager.log-aggregation.roll-monitoring-interval-seconds</code> should be + configured in yarn-site.xml. + This feature can only be used with Hadoop 2.6.1+. The Spark log4j appender needs be changed to use + FileAppender or another appender that can handle the files being removed while its running. Based + on the file name configured in the log4j configuration (like spark.log), the user should set the + regex (spark*) to include all the log files that need to be aggregated. + </td> +</tr> +<tr> + <td><code>spark.yarn.rolledLog.excludePattern</code></td> + <td>(none)</td> + <td> + Java Regex to filter the log files which match the defined exclude pattern + and those log files will not be aggregated in a rolling fashion. If the log file + name matches both the include and the exclude pattern, this file will be excluded eventually. + </td> +</tr> </table> # Important notes |