I downloaded the 1.3.1 source distribution and built on Windows (laptop 8.0 and desktop 8.1)
Here’s what I’m running: Desktop: Spark Master (%SPARK_HOME%\bin\spark-class2.cmd org.apache.spark.deploy.master.Master -h desktop --port 7077) Spark Worker (%SPARK_HOME%\bin\spark-class2.cmd org.apache.spark.deploy.worker.Worker spark://desktop:7077) Kafka Broker ZooKeeper Server Laptop: 2 Kafka Producers each sending to a unique topic to broker running on Desktop Driver App In this scenario, I get no messages showing up in the Driver App’s console. If on the other hand, I either move the driver app to the desktop or run the worker on the laptop instead of the desktop, then I see the counts as expected (meaning the driver and the worker/executor are on the same machine). When I moved this scenario to a set of machines in a separate network, separating the executor and driver worked as expected. So it seems a networking issue was causing the failure. Now to the followup question: which property do I set to configure the port so that I can ensure it’s a port that isn’t blocked by Systems? The candidates I see: spark.blockManager.port spark.blockManager.port spark.driver.host spark.driver.port spark.executor.port -Javier From: Akhil Das [mailto:ak...@sigmoidanalytics.com] Sent: Monday, May 4, 2015 12:42 AM To: Javier Delgadillo Cc: user@spark.apache.org Subject: Re: Remoting warning when submitting to cluster Looks like a version incompatibility, just make sure you have the proper version of spark. Also look further in the stacktrace what is causing Futures timed out (it could be a network issue also if the ports aren't opened properly) Thanks Best Regards On Sat, May 2, 2015 at 12:04 AM, javidelgadillo <jdelgadi...@esri.com<mailto:jdelgadi...@esri.com>> wrote: Hello all!! We've been prototyping some spark applications to read messages from Kafka topics. The application is quite simple, we use KafkaUtils.createStream to receive a stream of CSV messages from a Kafka Topic. We parse the CSV and count the number of messages we get in each RDD. At a high-level (removing the abstractions of our appliction), it looks like this: val sc = new SparkConf() .setAppName(appName) .set("spark.executor.memory", "1024m") .set("spark.cores.max", "3") .set("spark.app.name<http://spark.app.name>", appName) .set("spark.ui.port", sparkUIPort) val ssc = new StreamingContext(sc, Milliseconds(emitInterval.toInt)) KafkaUtils .createStream(ssc, zookeeperQuorum, consumerGroup, topicMap) .map(_._2) .foreachRDD( (rdd:RDD, time: Time) => { println("Time %s: (%s total records)".format(time, rdd.count())) } When I submit this using to spark master as local[3] everything behaves as I'd expect. After some startup overhead, I'm seeing the count printed to be the same as the count I'm simulating (1 every second for example). When I submit this to a spark master using spark://master.host:7077, the behavior is different. The overhead go start receiving seems longer and some runs I don't see anything for 30 seconds even though my simulator is sending messages to the topic. I also see the following error written to stderr by every executor assigned to the job: Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties 15/05/01 10:11:38 INFO SecurityManager: Changing view acls to: username 15/05/01 10:11:38 INFO SecurityManager: Changing modify acls to: username 15/05/01 10:11:38 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(javi4211); users with modify permissions: Set(username) 15/05/01 10:11:38 INFO Slf4jLogger: Slf4jLogger started 15/05/01 10:11:38 INFO Remoting: Starting remoting 15/05/01 10:11:39 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://driverpropsfetc...@master.host:56534] 15/05/01 10:11:39 INFO Utils: Successfully started service 'driverPropsFetcher' on port 56534. 15/05/01 10:11:40 WARN Remoting: Tried to associate with unreachable remote address [akka.tcp://sparkdri...@driver.host:51837]. Address is now gated for 5000 ms, all messages to this address will be delivered to dead letters. Reason: Connection refused: no further information: driver.host/10.27.51.214:51837<http://10.27.51.214:51837> 15/05/01 10:12:09 ERROR UserGroupInformation: PriviledgedActionException as:username cause:java.util.concurrent.TimeoutException: Futures timed out after [30 seconds] Exception in thread "main" java.lang.reflect.UndeclaredThrowableException: Unknown exception in doAs at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1134) at org.apache.spark.deploy.SparkHadoopUtil.runAsSparkUser(SparkHadoopUtil.scala:59) at org.apache.spark.executor.CoarseGrainedExecutorBackend$.run(CoarseGrainedExecutorBackend.scala:128) at org.apache.spark.executor.CoarseGrainedExecutorBackend$.main(CoarseGrainedExecutorBackend.scala:224) at org.apache.spark.executor.CoarseGrainedExecutorBackend.main(CoarseGrainedExecutorBackend.scala) Caused by: java.security.PrivilegedActionException: java.util.concurrent.TimeoutException: Futures timed out after [30 seconds] at java.security.AccessController.doPrivileged(Native Method) at javax.security.auth.Subject.doAs(Subject.java:422) at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1121) ... 4 more Caused by: 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) Is there something else I need to do configure to ensure akka remoting will work correctly when running spark cluster? Or can I ignore this error? -Javier -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Remoting-warning-when-submitting-to-cluster-tp22733.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org<mailto:user-unsubscr...@spark.apache.org> For additional commands, e-mail: user-h...@spark.apache.org<mailto:user-h...@spark.apache.org>
