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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2016/08/24 07:44:20 UTC
[jira] [Commented] (SPARK-17210) sparkr.zip is not distributed to
executors when run sparkr in RStudio
[ https://issues.apache.org/jira/browse/SPARK-17210?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15434407#comment-15434407 ]
Apache Spark commented on SPARK-17210:
--------------------------------------
User 'zjffdu' has created a pull request for this issue:
https://github.com/apache/spark/pull/14784
> sparkr.zip is not distributed to executors when run sparkr in RStudio
> ---------------------------------------------------------------------
>
> Key: SPARK-17210
> URL: https://issues.apache.org/jira/browse/SPARK-17210
> Project: Spark
> Issue Type: Bug
> Components: SparkR
> Affects Versions: 2.0.0
> Reporter: Jeff Zhang
>
> Here's the code to reproduce this issue.
> {code}
> Sys.setenv(SPARK_HOME="/Users/jzhang/github/spark")
> .libPaths(c(file.path(Sys.getenv(), "R", "lib"), .libPaths()))
> library(SparkR)
> sparkR.session(master="yarn-client", sparkConfig = list(spark.executor.instances="1"))
> df <- as.DataFrame(mtcars)
> head(df)
> {code}
> And this is the exception in executor log.
> {noformat}
> 16/08/24 15:33:45 INFO BufferedStreamThread: Fatal error: cannot open file '/Users/jzhang/Temp/hadoop_tmp/nm-local-dir/usercache/jzhang/appcache/application_1471846125517_0022/container_1471846125517_0022_01_000002/sparkr/SparkR/worker/daemon.R': No such file or directory
> 16/08/24 15:33:55 ERROR Executor: Exception in task 0.0 in stage 3.0 (TID 6)
> java.net.SocketTimeoutException: Accept timed out
> at java.net.PlainSocketImpl.socketAccept(Native Method)
> at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:404)
> at java.net.ServerSocket.implAccept(ServerSocket.java:545)
> at java.net.ServerSocket.accept(ServerSocket.java:513)
> at org.apache.spark.api.r.RRunner$.createRWorker(RRunner.scala:367)
> at org.apache.spark.api.r.RRunner.compute(RRunner.scala:69)
> at org.apache.spark.api.r.BaseRRDD.compute(RRDD.scala:49)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
> at org.apache.spark.scheduler.Task.run(Task.scala:86)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> {noformat}
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