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Xudong Zheng commented on SPARK-18115: -------------------------------------- Hello everyone, Can anybody give a short status about this issue? It has been fixed? > Custom metrics Sink/Source prevent Executor from starting > --------------------------------------------------------- > > Key: SPARK-18115 > URL: https://issues.apache.org/jira/browse/SPARK-18115 > Project: Spark > Issue Type: Bug > Components: Spark Core > Affects Versions: 1.6.0 > Reporter: Kostya Golikov > > Even though there is a semi-official support for custom metrics, in practice > specifying either custom sink or custom source will lead to NoClassDefFound > exceptions on executor side (but will be fine on driver side). > The initialization goes as: > 1. CoarseGrainedExecutorBackend [prepares SparkEnv for > executor|https://github.com/apache/spark/blob/6ee28423ad1b2e6089b82af64a31d77d3552bb38/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala#L223] > 2. SparkEnv [initializes > MetricSystem|https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/SparkEnv.scala#L338-L351]. > In case of executor it also starts it > 3. On [`.start()` MetricsSystem parses configuration files and creates > instances of sinks and > sources|https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/metrics/MetricsSystem.scala#L101-L102]. > This is where the issue actually happens -- it tries to instantiate classes > which are not there yet -- [jars and files are downloaded downstream, in > Executor|https://github.com/apache/spark/blob/6ee28423ad1b2e6089b82af64a31d77d3552bb38/core/src/main/scala/org/apache/spark/executor/Executor.scala#L257] > One of the possible solutions is to NOT start MetricSystem this fast, just > like driver does, but postpone it until jar with user defined code is fetched > and available on classpath. -- This message was sent by Atlassian JIRA (v6.4.14#64029) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org