diff options
| -rw-r--r-- | docs/running-on-yarn.md | 6 | ||||
| -rw-r--r-- | resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala | 25 |
2 files changed, 23 insertions, 8 deletions
diff --git a/docs/running-on-yarn.md b/docs/running-on-yarn.md index c95f627c12..cf95b95afd 100644 --- a/docs/running-on-yarn.md +++ b/docs/running-on-yarn.md @@ -445,7 +445,7 @@ To use a custom metrics.properties for the application master and executors, upd 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 + This feature can only be used with Hadoop 2.6.4+. 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. @@ -524,8 +524,8 @@ pre-packaged distribution. 1. In the `yarn-site.xml` on each node, add `spark_shuffle` to `yarn.nodemanager.aux-services`, then set `yarn.nodemanager.aux-services.spark_shuffle.class` to `org.apache.spark.network.yarn.YarnShuffleService`. -1. Increase `NodeManager's` heap size by setting `YARN_HEAPSIZE` (1000 by default) in `etc/hadoop/yarn-env.sh` -to avoid garbage collection issues during shuffle. +1. Increase `NodeManager's` heap size by setting `YARN_HEAPSIZE` (1000 by default) in `etc/hadoop/yarn-env.sh` +to avoid garbage collection issues during shuffle. 1. Restart all `NodeManager`s in your cluster. The following extra configuration options are available when the shuffle service is running on YARN: diff --git a/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala b/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala index 635c1ac5e3..70826ed326 100644 --- a/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala +++ b/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala @@ -245,12 +245,27 @@ private[spark] class Client( } sparkConf.get(ROLLED_LOG_INCLUDE_PATTERN).foreach { includePattern => - val logAggregationContext = Records.newRecord(classOf[LogAggregationContext]) - logAggregationContext.setRolledLogsIncludePattern(includePattern) - sparkConf.get(ROLLED_LOG_EXCLUDE_PATTERN).foreach { excludePattern => - logAggregationContext.setRolledLogsExcludePattern(excludePattern) + try { + val logAggregationContext = Records.newRecord(classOf[LogAggregationContext]) + + // These two methods were added in Hadoop 2.6.4, so we still need to use reflection to + // avoid compile error when building against Hadoop 2.6.0 ~ 2.6.3. + val setRolledLogsIncludePatternMethod = + logAggregationContext.getClass.getMethod("setRolledLogsIncludePattern", classOf[String]) + setRolledLogsIncludePatternMethod.invoke(logAggregationContext, includePattern) + + sparkConf.get(ROLLED_LOG_EXCLUDE_PATTERN).foreach { excludePattern => + val setRolledLogsExcludePatternMethod = + logAggregationContext.getClass.getMethod("setRolledLogsExcludePattern", classOf[String]) + setRolledLogsExcludePatternMethod.invoke(logAggregationContext, excludePattern) + } + + appContext.setLogAggregationContext(logAggregationContext) + } catch { + case NonFatal(e) => + logWarning(s"Ignoring ${ROLLED_LOG_INCLUDE_PATTERN.key} because the version of YARN " + + "does not support it", e) } - appContext.setLogAggregationContext(logAggregationContext) } appContext |