Try putting a * on the end of xmlDir, i.e. xmlDir = fdfs:///abc/def/*
Rather than xmlDir = Hdfs://abc/def and see what happens. I don't know why, but that appears to be more reliable for me with S3 as the filesystem. I'm also using binaryFiles, but I've tried running the same command while wholeTextFiles and had the same error. Ewan -----Original Message----- From: Kostas Kougios [mailto:kostas.koug...@googlemail.com] Sent: 08 June 2015 15:02 To: user@spark.apache.org Subject: spark timesout maybe due to binaryFiles() with more than 1 million files in HDFS I am reading millions of xml files via val xmls = sc.binaryFiles(xmlDir) The operation runs fine locally but on yarn it fails with: client token: N/A diagnostics: Application application_1433491939773_0012 failed 2 times due to ApplicationMaster for attempt appattempt_1433491939773_0012_000002 timed out. Failing the application. ApplicationMaster host: N/A ApplicationMaster RPC port: -1 queue: default start time: 1433750951883 final status: FAILED tracking URL: http://controller01:8088/cluster/app/application_1433491939773_0012 user: ariskk Exception in thread "main" org.apache.spark.SparkException: Application finished with failed status at org.apache.spark.deploy.yarn.Client.run(Client.scala:622) at org.apache.spark.deploy.yarn.Client$.main(Client.scala:647) at org.apache.spark.deploy.yarn.Client.main(Client.scala) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:497) at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:569) at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:166) at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:189) at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:110) at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala) On hadoops/userlogs logs I am frequently getting these messages: 15/06/08 09:15:38 WARN util.AkkaUtils: Error sending message [message = Heartbeat(1,[Lscala.Tuple2;@2b4f336b,BlockManagerId(1, controller01.stratified, 58510))] in 2 attempts java.util.concurrent.TimeoutException: Futures timed out after [30 seconds] at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:219) at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:223) at scala.concurrent.Await$$anonfun$result$1.apply(package.scala:107) at scala.concurrent.BlockContext$DefaultBlockContext$.blockOn(BlockContext.scala:53) at scala.concurrent.Await$.result(package.scala:107) at org.apache.spark.util.AkkaUtils$.askWithReply(AkkaUtils.scala:195) at org.apache.spark.executor.Executor$$anon$1.run(Executor.scala:427) I run my spark job via spark-submit and it works for an other HDFS directory that contains only 37k files. Any ideas how to resolve this? -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/spark-timesout-maybe-due-to-binaryFiles-with-more-than-1-million-files-in-HDFS-tp23208.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
