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Merge branch 'master' into vector
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‎core/pom.xml‎

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<artifactId>json4s-jackson_${scala.binary.version}</artifactId>
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<version>3.2.6</version>
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<!-- see also exclusion for lift-json; this is necessary since it depends on
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scala-library and scalap 2.10.0, but we use 2.10.3, and only override
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scala-library and scalap 2.10.0, but we use 2.10.4, and only override
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scala-library -->
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<exclusions>
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<exclusion>

‎core/src/main/scala/org/apache/spark/ui/JettyUtils.scala‎

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package org.apache.spark.ui
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import java.net.{InetSocketAddress, URL}
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import javax.servlet.DispatcherType
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import javax.servlet.http.{HttpServlet, HttpServletRequest, HttpServletResponse}
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import scala.annotation.tailrec
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import scala.util.{Failure, Success, Try}
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import scala.xml.Node
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import org.eclipse.jetty.server.{DispatcherType, Server}
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import org.eclipse.jetty.server.Server
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import org.eclipse.jetty.server.handler._
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import org.eclipse.jetty.servlet._
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import org.eclipse.jetty.util.thread.QueuedThreadPool

‎core/src/main/scala/org/apache/spark/ui/storage/BlockManagerUI.scala‎

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override def onStageSubmitted(stageSubmitted: SparkListenerStageSubmitted) = synchronized {
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val rddInfo = stageSubmitted.stageInfo.rddInfo
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_rddInfoMap(rddInfo.id) = rddInfo
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_rddInfoMap.getOrElseUpdate(rddInfo.id, rddInfo)
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}
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override def onStageCompleted(stageCompleted: SparkListenerStageCompleted) = synchronized {

‎dev/audit-release/README.md‎

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@@ -4,7 +4,7 @@ run them locally by setting appropriate environment variables.
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```
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$ cd sbt_app_core
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$ SCALA_VERSION=2.10.3 \
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$ SCALA_VERSION=2.10.4 \
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SPARK_VERSION=1.0.0-SNAPSHOT \
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SPARK_RELEASE_REPOSITORY=file:///home/patrick/.ivy2/local \
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sbt run

‎dev/audit-release/audit_release.py‎

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RELEASE_KEY = "9E4FE3AF"
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RELEASE_REPOSITORY = "https://repository.apache.org/content/repositories/orgapachespark-1006/"
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RELEASE_VERSION = "1.0.0"
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SCALA_VERSION = "2.10.3"
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SCALA_VERSION = "2.10.4"
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SCALA_BINARY_VERSION = "2.10"
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##
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‎docker/spark-test/base/Dockerfile‎

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@@ -25,7 +25,7 @@ RUN apt-get update
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# install a few other useful packages plus Open Jdk 7
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RUN apt-get install -y less openjdk-7-jre-headless net-tools vim-tiny sudo openssh-server
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ENV SCALA_VERSION 2.10.3
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ENV SCALA_VERSION 2.10.4
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ENV CDH_VERSION cdh4
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ENV SCALA_HOME /opt/scala-$SCALA_VERSION
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ENV SPARK_HOME /opt/spark

‎docs/_config.yml‎

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SPARK_VERSION: 1.0.0-SNAPSHOT
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SPARK_VERSION_SHORT: 1.0.0
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SCALA_BINARY_VERSION: "2.10"
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SCALA_VERSION: "2.10.3"
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SCALA_VERSION: "2.10.4"
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MESOS_VERSION: 0.13.0
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SPARK_ISSUE_TRACKER_URL: https://spark-project.atlassian.net
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SPARK_GITHUB_URL: https://github.com/apache/spark

‎docs/running-on-yarn.md‎

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SPARK_JAR=<SPARK_ASSEMBLY_JAR_FILE> ./bin/spark-class org.apache.spark.deploy.yarn.Client \
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--jar <YOUR_APP_JAR_FILE> \
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--class <APP_MAIN_CLASS> \
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--args <APP_MAIN_ARGUMENTS> \
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--arg <APP_MAIN_ARGUMENT> \
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--num-executors <NUMBER_OF_EXECUTOR_PROCESSES> \
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--driver-memory <MEMORY_FOR_ApplicationMaster> \
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--executor-memory <MEMORY_PER_EXECUTOR> \
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--files <files_for_distributed_cache> \
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--archives <archives_for_distributed_cache>
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For example:
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To pass multiple arguments the "arg" option can be specified multiple times. For example:
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# Build the Spark assembly JAR and the Spark examples JAR
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$ SPARK_HADOOP_VERSION=2.0.5-alpha SPARK_YARN=true sbt/sbt assembly
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./bin/spark-class org.apache.spark.deploy.yarn.Client \
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--jar examples/target/scala-{{site.SCALA_BINARY_VERSION}}/spark-examples-assembly-{{site.SPARK_VERSION}}.jar \
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--class org.apache.spark.examples.SparkPi \
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--args yarn-cluster \
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--arg yarn-cluster \
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--arg 5 \
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--num-executors 3 \
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--driver-memory 4g \
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--executor-memory 2g \

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