Here's one of the settings that i used for a closed environment:
.set("spark.blockManager.port","40010")
.set("spark.broadcast.port","40020")
.set("spark.driver.port","40030")
.set("spark.executor.port","40040")
.set("spark.fileserver.port","40050")
.set("spark.replClassServer.port","40060")
Thanks
Best Regards
On Wed, May 6, 2015 at 1:49 AM, Javier Delgadillo <jdelgadi...@esri.com>
wrote:
> 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>
> 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", 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
> 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
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>
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