Merge remote-tracking branch 'asf/master'

Conflicts:
	external/flume/src/main/scala/org/apache/spark/streaming/flume/FlumeInputDStream.scala
	project/SparkBuild.scala

Author: harishreedharan

.rat-excludes

@@ -4,6 +4,8 @@ target
 .classpath
 .mima-excludes
 .generated-mima-excludes
+.generated-mima-class-excludes
+.generated-mima-member-excludes
 .rat-excludes
 .*md
 derby.log
@@ -20,6 +22,8 @@ slaves
 spark-env.sh
 spark-env.sh.template
 log4j-defaults.properties
+bootstrap-tooltip.js
+jquery-1.11.1.min.js
 sorttable.js
 .*txt
 .*json

README.md

@@ -69,29 +69,28 @@ can be run using:
 Spark uses the Hadoop core library to talk to HDFS and other Hadoop-supported
 storage systems. Because the protocols have changed in different versions of
 Hadoop, you must build Spark against the same version that your cluster runs.
-You can change the version by setting the `SPARK_HADOOP_VERSION` environment
-when building Spark.
+You can change the version by setting `-Dhadoop.version` when building Spark.
 
 For Apache Hadoop versions 1.x, Cloudera CDH MRv1, and other Hadoop
 versions without YARN, use:
 
     # Apache Hadoop 1.2.1
-    $ SPARK_HADOOP_VERSION=1.2.1 sbt/sbt assembly
+    $ sbt/sbt -Dhadoop.version=1.2.1 assembly
 
     # Cloudera CDH 4.2.0 with MapReduce v1
-    $ SPARK_HADOOP_VERSION=2.0.0-mr1-cdh4.2.0 sbt/sbt assembly
+    $ sbt/sbt -Dhadoop.version=2.0.0-mr1-cdh4.2.0 assembly
 
 For Apache Hadoop 2.2.X, 2.1.X, 2.0.X, 0.23.x, Cloudera CDH MRv2, and other Hadoop versions
 with YARN, also set `SPARK_YARN=true`:
 
     # Apache Hadoop 2.0.5-alpha
-    $ SPARK_HADOOP_VERSION=2.0.5-alpha SPARK_YARN=true sbt/sbt assembly
+    $ sbt/sbt -Dhadoop.version=2.0.5-alpha -Pyarn assembly
 
     # Cloudera CDH 4.2.0 with MapReduce v2
-    $ SPARK_HADOOP_VERSION=2.0.0-cdh4.2.0 SPARK_YARN=true sbt/sbt assembly
+    $ sbt/sbt -Dhadoop.version=2.0.0-cdh4.2.0 -Pyarn assembly
 
     # Apache Hadoop 2.2.X and newer
-    $ SPARK_HADOOP_VERSION=2.2.0 SPARK_YARN=true sbt/sbt assembly
+    $ sbt/sbt -Dhadoop.version=2.2.0 -Pyarn assembly
 
 When developing a Spark application, specify the Hadoop version by adding the
 "hadoop-client" artifact to your project's dependencies. For example, if you're

assembly/pom.xml

@@ -32,6 +32,7 @@
   <packaging>pom</packaging>
 
   <properties>
+    <sbt.project.name>assembly</sbt.project.name>
     <spark.jar.dir>scala-${scala.binary.version}</spark.jar.dir>
     <spark.jar.basename>spark-assembly-${project.version}-hadoop${hadoop.version}.jar</spark.jar.basename>
     <spark.jar>${project.build.directory}/${spark.jar.dir}/${spark.jar.basename}</spark.jar>

bagel/pom.xml

@@ -27,6 +27,9 @@
 
   <groupId>org.apache.spark</groupId>
   <artifactId>spark-bagel_2.10</artifactId>
+  <properties>
+     <sbt.project.name>bagel</sbt.project.name>
+  </properties>
   <packaging>jar</packaging>
   <name>Spark Project Bagel</name>
   <url>http://spark.apache.org/</url>

bin/compute-classpath.sh

@@ -81,10 +81,10 @@ ASSEMBLY_JAR=$(ls "$assembly_folder"/spark-assembly*hadoop*.jar 2>/dev/null)
 # Verify that versions of java used to build the jars and run Spark are compatible
 jar_error_check=$("$JAR_CMD" -tf "$ASSEMBLY_JAR" nonexistent/class/path 2>&1)
 if [[ "$jar_error_check" =~ "invalid CEN header" ]]; then
-  echo "Loading Spark jar with '$JAR_CMD' failed. "
-  echo "This is likely because Spark was compiled with Java 7 and run "
-  echo "with Java 6. (see SPARK-1703). Please use Java 7 to run Spark "
-  echo "or build Spark with Java 6."
+  echo "Loading Spark jar with '$JAR_CMD' failed. " 1>&2
+  echo "This is likely because Spark was compiled with Java 7 and run " 1>&2
+  echo "with Java 6. (see SPARK-1703). Please use Java 7 to run Spark " 1>&2
+  echo "or build Spark with Java 6." 1>&2
   exit 1
 fi
 

bin/pyspark

@@ -26,7 +26,7 @@ export SPARK_HOME="$FWDIR"
 SCALA_VERSION=2.10
 
 if [[ "$@" = *--help ]] || [[ "$@" = *-h ]]; then
-  echo "Usage: ./bin/pyspark [options]"
+  echo "Usage: ./bin/pyspark [options]" 1>&2
   $FWDIR/bin/spark-submit --help 2>&1 | grep -v Usage 1>&2
   exit 0
 fi
@@ -36,8 +36,8 @@ if [ ! -f "$FWDIR/RELEASE" ]; then
   # Exit if the user hasn't compiled Spark
   ls "$FWDIR"/assembly/target/scala-$SCALA_VERSION/spark-assembly*hadoop*.jar >& /dev/null
   if [[ $? != 0 ]]; then
-    echo "Failed to find Spark assembly in $FWDIR/assembly/target" >&2
-    echo "You need to build Spark before running this program" >&2
+    echo "Failed to find Spark assembly in $FWDIR/assembly/target" 1>&2
+    echo "You need to build Spark before running this program" 1>&2
     exit 1
   fi
 fi

bin/run-example

@@ -27,9 +27,9 @@ if [ -n "$1" ]; then
   EXAMPLE_CLASS="$1"
   shift
 else
-  echo "Usage: ./bin/run-example <example-class> [example-args]"
-  echo "  - set MASTER=XX to use a specific master"
-  echo "  - can use abbreviated example class name (e.g. SparkPi, mllib.LinearRegression)"
+  echo "Usage: ./bin/run-example <example-class> [example-args]" 1>&2
+  echo "  - set MASTER=XX to use a specific master" 1>&2
+  echo "  - can use abbreviated example class name (e.g. SparkPi, mllib.LinearRegression)" 1>&2
   exit 1
 fi
 
@@ -40,8 +40,8 @@ elif [ -e "$EXAMPLES_DIR"/target/scala-$SCALA_VERSION/spark-examples-*hadoop*.ja
 fi
 
 if [[ -z $SPARK_EXAMPLES_JAR ]]; then
-  echo "Failed to find Spark examples assembly in $FWDIR/lib or $FWDIR/examples/target" >&2
-  echo "You need to build Spark before running this program" >&2
+  echo "Failed to find Spark examples assembly in $FWDIR/lib or $FWDIR/examples/target" 1>&2
+  echo "You need to build Spark before running this program" 1>&2
   exit 1
 fi
 

bin/spark-class

@@ -33,13 +33,13 @@ export SPARK_HOME="$FWDIR"
 . $FWDIR/bin/load-spark-env.sh
 
 if [ -z "$1" ]; then
-  echo "Usage: spark-class <class> [<args>]" >&2
+  echo "Usage: spark-class <class> [<args>]" 1>&2
   exit 1
 fi
 
 if [ -n "$SPARK_MEM" ]; then
-  echo "Warning: SPARK_MEM is deprecated, please use a more specific config option"
-  echo "(e.g., spark.executor.memory or SPARK_DRIVER_MEMORY)."
+  echo -e "Warning: SPARK_MEM is deprecated, please use a more specific config option" 1>&2
+  echo -e "(e.g., spark.executor.memory or SPARK_DRIVER_MEMORY)." 1>&2
 fi
 
 # Use SPARK_MEM or 512m as the default memory, to be overridden by specific options
@@ -110,9 +110,9 @@ export JAVA_OPTS
 
 TOOLS_DIR="$FWDIR"/tools
 SPARK_TOOLS_JAR=""
-if [ -e "$TOOLS_DIR"/target/scala-$SCALA_VERSION/*assembly*[0-9Tg].jar ]; then
+if [ -e "$TOOLS_DIR"/target/scala-$SCALA_VERSION/spark-tools*[0-9Tg].jar ]; then
   # Use the JAR from the SBT build
-  export SPARK_TOOLS_JAR=`ls "$TOOLS_DIR"/target/scala-$SCALA_VERSION/*assembly*[0-9Tg].jar`
+  export SPARK_TOOLS_JAR=`ls "$TOOLS_DIR"/target/scala-$SCALA_VERSION/spark-tools*[0-9Tg].jar`
 fi
 if [ -e "$TOOLS_DIR"/target/spark-tools*[0-9Tg].jar ]; then
   # Use the JAR from the Maven build
@@ -130,6 +130,11 @@ else
 fi
 
 if [[ "$1" =~ org.apache.spark.tools.* ]]; then
+  if test -z "$SPARK_TOOLS_JAR"; then
+    echo "Failed to find Spark Tools Jar in $FWDIR/tools/target/scala-$SCALA_VERSION/" 1>&2
+    echo "You need to build spark before running $1." 1>&2
+    exit 1
+  fi
   CLASSPATH="$CLASSPATH:$SPARK_TOOLS_JAR"
 fi
 
@@ -142,10 +147,9 @@ fi
 export CLASSPATH
 
 if [ "$SPARK_PRINT_LAUNCH_COMMAND" == "1" ]; then
-  echo -n "Spark Command: "
-  echo "$RUNNER" -cp "$CLASSPATH" $JAVA_OPTS "$@"
-  echo "========================================"
-  echo
+  echo -n "Spark Command: " 1>&2
+  echo "$RUNNER" -cp "$CLASSPATH" $JAVA_OPTS "$@" 1>&2
+  echo -e "========================================\n" 1>&2
 fi
 
 exec "$RUNNER" -cp "$CLASSPATH" $JAVA_OPTS "$@"

conf/log4j.properties.template

@@ -7,5 +7,6 @@ log4j.appender.console.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss} %p %c{1}:
 
 # Settings to quiet third party logs that are too verbose
 log4j.logger.org.eclipse.jetty=WARN
+log4j.logger.org.eclipse.jetty.util.component.AbstractLifeCycle=ERROR
 log4j.logger.org.apache.spark.repl.SparkIMain$exprTyper=INFO
 log4j.logger.org.apache.spark.repl.SparkILoop$SparkILoopInterpreter=INFO

core/pom.xml

@@ -27,13 +27,22 @@
 
   <groupId>org.apache.spark</groupId>
   <artifactId>spark-core_2.10</artifactId>
+  <properties>
+     <sbt.project.name>core</sbt.project.name>
+  </properties>
   <packaging>jar</packaging>
   <name>Spark Project Core</name>
   <url>http://spark.apache.org/</url>
   <dependencies>
     <dependency>
       <groupId>org.apache.hadoop</groupId>
       <artifactId>hadoop-client</artifactId>
+      <exclusions>
+        <exclusion>
+          <groupId>javax.servlet</groupId>
+          <artifactId>servlet-api</artifactId>
+        </exclusion>
+      </exclusions>
     </dependency>
     <dependency>
       <groupId>net.java.dev.jets3t</groupId>
@@ -244,6 +253,11 @@
       <artifactId>easymockclassextension</artifactId>
       <scope>test</scope>
     </dependency>
+    <dependency>
+      <groupId>asm</groupId>
+      <artifactId>asm</artifactId>
+      <scope>test</scope>
+    </dependency>
     <dependency>
       <groupId>com.novocode</groupId>
       <artifactId>junit-interface</artifactId>

core/src/main/resources/org/apache/spark/log4j-defaults.properties

@@ -7,5 +7,6 @@ log4j.appender.console.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss} %p %c{1}:
 
 # Settings to quiet third party logs that are too verbose
 log4j.logger.org.eclipse.jetty=WARN
+log4j.logger.org.eclipse.jetty.util.component.AbstractLifeCycle=ERROR
 log4j.logger.org.apache.spark.repl.SparkIMain$exprTyper=INFO
 log4j.logger.org.apache.spark.repl.SparkILoop$SparkILoopInterpreter=INFO