The Hortonworks Community Connection is now live. A completely rebuilt Q&A forum, Knowledge Base, Code Hub and more, backed by the experts in the industry.

You will be redirected here in 10 seconds. If your are not redirected, click here to visit the new site.

The legacy Hortonworks Forum is now closed. You can view a read-only version of the former site by clicking here. The site will be taken offline on January 31,2016

Spark Forum

Exception over HDP: 2.0.6

  • #57455
    Abel Coronado
    Participant

    Hi Everybody :)
    I´m Triyng to run an App in a Spark installation over HDP: 2.0.6 and Hadoop:2.2.0 but something is wrong, anybody can give me some hint???

    The example runs OK:
    SPARK_JAR=lib/spark-assembly_2.10-0.9.1.2.1.1.0-22-hadoop2.4.0.2.1.1.0-385.jar ./bin/spark-class org.apache.spark.deploy.yarn.Client –jar examples/lib/spark-examples_2.10-0.9.1.2.1.1.0-22.jar –class org.apache.spark.examples.SparkPi –args yarn-standalone –num-workers 20 –master-memory 512m –worker-memory 512m –worker-cores 1

    But my JAR fails:
    SPARK_JAR=/usr/lib/spark/lib/spark-assembly_2.10-0.9.1.2.1.1.0-22-hadoop2.4.0.2.1.1.0-385.jar /usr/lib/spark/bin/spark-class org.apache.spark.deploy.yarn.Client –jar /home/abel/spark/geoProcessingSpark-0.9.1/target/scala-2.10/SparkGeoprocessing-0.9.1-assembly-1.0.jar –class SimpleApp –args yarn-standalone –num-workers 2 –master-memory 512m –worker-memory 512m –worker-cores 1

    ERROR:
    appDiagnostics: Application application_1403012744101_0477 failed 2 times due to AM Container for appattempt_1403012744101_0477_000002 exited with exitCode: 1 due to: Exception from container-launch:
    org.apache.hadoop.util.Shell$ExitCodeException:
    at org.apache.hadoop.util.Shell.runCommand(Shell.java:464)

    I think that the issue is in the configuration, here build.sbt:

    import AssemblyKeys._

    assemblySettings

    excludedJars in assembly <<= (fullClasspath in assembly) map { cp =>
    cp filter { c=>List(“asm-3.2.jar”,”javax.servlet-2.5.0.v201103041518.jar”,”hadoop-yarn-common-2.2.0.jar”,”jcl-over-slf4j-1.7.5.jar”,”xsd-2.6.0.jar”,”ecore-2.6.1.jar”,”jt-zonalstats-1.3.1.jar”,”javax.transaction-1.1.1.v201105210645.jar”,”javax.servlet-3.0.0.v201112011016.jar”,”javax.mail.glassfish-1.4.1.v201005082020.jar”,”javax.activation-1.1.0.v201105071233.jar”,”commons-collections-3.1.jar”,”hsqldb-1.8.0.10.jar”,”commons-beanutils-1.7.0.jar”,”commons-collections-3.2.1.jar”) exists { c.data.getName contains _} }
    }

    name := “SparkGeoprocessing-0.9.1”

    version := “1.0”

    scalaVersion := “2.10.0”

    libraryDependencies += “org.apache.hadoop” % “hadoop-client” % “2.2.0”

    libraryDependencies ++= Seq(
    ( “org.apache.spark” %% “spark-core” % “0.9.1”).
    exclude(“org.mortbay.jetty”, “servlet-api”).
    exclude(“commons-beanutils”, “commons-beanutils-core”).
    exclude(“commons-collections”, “commons-collections”).
    exclude(“commons-collections”, “commons-collections”).
    exclude(“com.esotericsoftware.minlog”, “minlog”)
    )

    libraryDependencies ++= Seq(
    “com.vividsolutions” % “jts” % “1.13”,
    “org.geotools” % “gt-main” % “11.1”,
    “org.geotools” % “gt-epsg-hsql” % “11.1”,
    “org.geotools” % “gt-shapefile” % “11.1”,
    “org.geotools” % “gt-render” % “11.1”,
    “org.geotools” % “gt-xml” % “11.1”,
    “org.geotools” % “gt-geojson” % “11.1”,
    “org.geotools.jdbc” % “gt-jdbc-postgis” % “11.1”,
    “org.geotools.jdbc” % “gt-jdbc-spatialite” % “11.1”,
    “org.geotools” % “gt-coverage” % “11.1”,
    “org.geotools” % “gt-geotiff” % “11.1”,
    […]

  • Author
    Replies
  • #57456
    Abel Coronado
    Participant

    At this moment the code is very simple:

    import org.apache.spark.SparkContext
    import org.apache.spark.SparkContext._
    import org.apache.spark.SparkConf
    import org.geoscript.feature._
    import org.geoscript.geometry._
    import org.geoscript.geometry.builder._
    import com.vividsolutions.jts._
    import org.geoscript.layer.Shapefile
    import org.geotools.feature.FeatureCollection

    object SimpleApp {
    def main(args: Array[String]){
    val conf = new SparkConf().setMaster(“local”).setAppName(“Csv Clipper”).set(“spark.executor.memory”, “1g”)
    val sc = new SparkContext(conf)
    }
    }

    Thanks!!!!!

    #57541
    Abel Coronado
    Participant

    May be you can let me see the build.sbt used to assembly the SparkPi example?

The forum ‘Spark’ is closed to new topics and replies.

Support from the Experts

A HDP Support Subscription connects you experts with deep experience running Apache Hadoop in production, at-scale on the most demanding workloads.

Enterprise Support »

Become HDP Certified

Real world training designed by the core architects of Hadoop. Scenario-based training courses are available in-classroom or online from anywhere in the world

Training »

Hortonworks Data Platform
The Hortonworks Data Platform is a 100% open source distribution of Apache Hadoop that is truly enterprise grade having been built, tested and hardened with enterprise rigor.
Get started with Sandbox
Hortonworks Sandbox is a self-contained virtual machine with Apache Hadoop pre-configured alongside a set of hands-on, step-by-step Hadoop tutorials.
Modern Data Architecture
Tackle the challenges of big data. Hadoop integrates with existing EDW, RDBMS and MPP systems to deliver lower cost, higher capacity infrastructure.