After playing a bit, I have been able to create a fatjar this way: lazy val rootDependencies = Seq( "org.apache.spark" %% "spark-core" % "1.0.0" % "provided", "org.apache.spark" %% "spark-streaming" % "1.0.0" % "provided", "org.apache.spark" %% "spark-streaming-twitter" % "1.0.0" exclude("org.apache.spark", "spark-core_2.10") exclude("org.apache.spark", "spark-streaming_2.10") )
Excluding those transitive dependencies, we can create a fatjar ~400Kb instead of 40Mb. My problem is not to run the streaming job locally but trying to submit it to standalone cluster using spark-submit, everytime I ran the following command, my workers died: ~/development/tools/spark/1.0.0/bin/spark-submit \ --class "org.apache.spark.examples.streaming.TwitterPopularTags" \ --master "spark://int-spark-master:7077" \ --deploy-mode "cluster" \ file:///tmp/spark-test-0.1-SNAPSHOT.jar I have copied my fatjar to my master /tmp folder. 2014-06-17 10:30 GMT+01:00 Michael Cutler <mich...@tumra.com>: > Admittedly getting Spark Streaming / Kafka working for the first time can > be a bit tricky with the web of dependencies that get pulled in. I've > taken the KafkaWorkCount example from the Spark project and set up a simple > standalone SBT project that shows you how to get it working and using > spark-submit. > > *https://github.com/cotdp/spark-example-kafka > <https://github.com/cotdp/spark-example-kafka>* > > The key trick is in the use of sbt-assembly instead of relying on any of > the "add jars" functionality. You mark "spark-core" and "spark-streaming" > as provided, because they are part of the core spark-assembly already > running your cluster. However "spark-streaming-kafka" is not, so you need > to package it in your 'fat JAR' while excluding all the mess that causes > the build to break. > > build.sbt > <https://github.com/cotdp/spark-example-kafka/blob/master/build.sbt>: > > import AssemblyKeys._ > > assemblySettings > > name := "spark-example-kafka" > > version := "1.0" > > scalaVersion := "2.10.4" > > jarName in assembly := "spark-example-kafka_2.10-1.0.jar" > > assemblyOption in assembly ~= { _.copy(includeScala = false) } > > libraryDependencies ++= Seq( > "org.apache.spark" %% "spark-core" % "1.0.0" % "provided", > "org.apache.spark" %% "spark-streaming" % "1.0.0" % "provided", > ("org.apache.spark" %% "spark-streaming-kafka" % "1.0.0"). > exclude("commons-beanutils", "commons-beanutils"). > exclude("commons-collections", "commons-collections"). > exclude("com.esotericsoftware.minlog", "minlog") > ) > > mergeStrategy in assembly <<= (mergeStrategy in assembly) { (old) => > { > case x if x.startsWith("META-INF/ECLIPSEF.RSA") => MergeStrategy.last > case x if x.startsWith("META-INF/mailcap") => MergeStrategy.last > case x if x.startsWith("plugin.properties") => MergeStrategy.last > case x => old(x) > } > } > > > You can see the "exclude()" has to go around the spark-streaming-kafka > dependency, > and I've used a MergeStrategy to solve the "deduplicate: different file > contents found in the following" errors. > > Build the JAR with sbt assembly and use the scripts in bin/ to run the > examples. > > I'm using this same approach to run my Spark Streaming jobs with > spark-submit and have them managed using Mesos/Marathon > <http://mesosphere.io/> to handle failures and restarts with long running > processes. > > Good luck! > > MC > > > > > > *Michael Cutler* > Founder, CTO > > > * Mobile: +44 789 990 7847 Email: mich...@tumra.com <mich...@tumra.com> > Web: tumra.com > <http://tumra.com/?utm_source=signature&utm_medium=email> * > *Visit us at our offices in Chiswick Park <http://goo.gl/maps/abBxq>* > *Registered in England & Wales, 07916412. VAT No. 130595328* > > > This email and any files transmitted with it are confidential and may also > be privileged. It is intended only for the person to whom it is addressed. > If you have received this email in error, please inform the sender > immediately. > If you are not the intended recipient you must not use, disclose, copy, > print, distribute or rely on this email. > > > On 17 June 2014 02:51, Gino Bustelo <lbust...@gmail.com> wrote: > >> +1 for this issue. Documentation for spark-submit are misleading. Among >> many issues, the jar support is bad. HTTP urls do not work. This is because >> spark is using hadoop's FileSystem class. You have to specify the jars >> twice to get things to work. Once for the DriverWrapper to laid your >> classes and a 2nd time in the Context to distribute to workers. >> >> I would like to see some contrib response to this issue. >> >> Gino B. >> >> On Jun 16, 2014, at 1:49 PM, Luis Ángel Vicente Sánchez < >> langel.gro...@gmail.com> wrote: >> >> Did you manage to make it work? I'm facing similar problems and this a >> serious blocker issue. spark-submit seems kind of broken to me if you can >> use it for spark-streaming. >> >> Regards, >> >> Luis >> >> >> 2014-06-11 1:48 GMT+01:00 lannyripple <lanny.rip...@gmail.com>: >> >>> I am using Spark 1.0.0 compiled with Hadoop 1.2.1. >>> >>> I have a toy spark-streaming-kafka program. It reads from a kafka queue >>> and >>> does >>> >>> stream >>> .map {case (k, v) => (v, 1)} >>> .reduceByKey(_ + _) >>> .print() >>> >>> using a 1 second interval on the stream. >>> >>> The docs say to make Spark and Hadoop jars 'provided' but this breaks for >>> spark-streaming. Including spark-streaming (and spark-streaming-kafka) >>> as >>> 'compile' to sweep them into our assembly gives collisions on javax.* >>> classes. To work around this I modified >>> $SPARK_HOME/bin/compute-classpath.sh to include spark-streaming, >>> spark-streaming-kafka, and zkclient. (Note that kafka is included as >>> 'compile' in my project and picked up in the assembly.) >>> >>> I have set up conf/spark-env.sh as needed. I have copied my assembly to >>> /tmp/myjar.jar on all spark hosts and to my hdfs /tmp/jars directory. I >>> am >>> running spark-submit from my spark master. I am guided by the >>> information >>> here https://spark.apache.org/docs/latest/submitting-applications.html >>> >>> Well at this point I was going to detail all the ways spark-submit fails >>> to >>> follow it's own documentation. If I do not invoke sparkContext.setJars() >>> then it just fails to find the driver class. This is using various >>> combinations of absolute path, file:, hdfs: (Warning: Skip remote jar)??, >>> and local: prefixes on the application-jar and --jars arguments. >>> >>> If I invoke sparkContext.setJars() and include my assembly jar I get >>> further. At this point I get a failure from >>> kafka.consumer.ConsumerConnector not being found. I suspect this is >>> because >>> spark-streaming-kafka needs the Kafka dependency it but my assembly jar >>> is >>> too late in the classpath. >>> >>> At this point I try setting spark.files.userClassPathfirst to 'true' but >>> this causes more things to blow up. >>> >>> I finally found something that works. Namely setting environment >>> variable >>> SPARK_CLASSPATH=/tmp/myjar.jar But silly me, this is deprecated and I'm >>> helpfully informed to >>> >>> Please instead use: >>> - ./spark-submit with --driver-class-path to augment the driver >>> classpath >>> - spark.executor.extraClassPath to augment the executor classpath >>> >>> which when put into a file and introduced with --properties-file does not >>> work. (Also tried spark.files.userClassPathFirst here.) These fail with >>> the kafka.consumer.ConsumerConnector error. >>> >>> At a guess what's going on is that using SPARK_CLASSPATH I have my >>> assembly >>> jar in the classpath at SparkSubmit invocation >>> >>> Spark Command: java -cp >>> >>> /tmp/myjar.jar::/opt/spark/conf:/opt/spark/lib/spark-assembly-1.0.0-hadoop1.2.1.jar:/opt/spark/lib/spark-streaming_2.10-1.0.0.jar:/opt/spark/lib/spark-streaming-kafka_2.10-1.0.0.jar:/opt/spark/lib/zkclient-0.4.jar >>> -XX:MaxPermSize=128m -Djava.library.path= -Xms512m -Xmx512m >>> org.apache.spark.deploy.SparkSubmit --class me.KafkaStreamingWC >>> /tmp/myjar.jar >>> >>> but using --properties-file then the assembly is not available for >>> SparkSubmit. >>> >>> I think the root cause is either spark-submit not handling the >>> spark-streaming libraries so they can be 'provided' or the inclusion of >>> org.elicpse.jetty.orbit in the streaming libraries which cause >>> >>> [error] (*:assembly) deduplicate: different file contents found in the >>> following: >>> [error] >>> >>> /Users/lanny/.ivy2/cache/org.eclipse.jetty.orbit/javax.transaction/orbits/javax.transaction-1.1.1.v201105210645.jar:META-INF/ECLIPSEF.RSA >>> [error] >>> >>> /Users/lanny/.ivy2/cache/org.eclipse.jetty.orbit/javax.servlet/orbits/javax.servlet-3.0.0.v201112011016.jar:META-INF/ECLIPSEF.RSA >>> [error] >>> >>> /Users/lanny/.ivy2/cache/org.eclipse.jetty.orbit/javax.mail.glassfish/orbits/javax.mail.glassfish-1.4.1.v201005082020.jar:META-INF/ECLIPSEF.RSA >>> [error] >>> >>> /Users/lanny/.ivy2/cache/org.eclipse.jetty.orbit/javax.activation/orbits/javax.activation-1.1.0.v201105071233.jar:META-INF/ECLIPSEF.RSA >>> >>> I've tried applying mergeStategy in assembly for my assembly.sbt but >>> then I >>> get >>> >>> Invalid signature file digest for Manifest main attributes >>> >>> If anyone knows the magic to get this working a reply would be greatly >>> appreciated. >>> >>> >>> >>> -- >>> View this message in context: >>> http://apache-spark-user-list.1001560.n3.nabble.com/spark-streaming-kafka-SPARK-CLASSPATH-tp7356.html >>> Sent from the Apache Spark User List mailing list archive at Nabble.com. >>> >> >> >