289373b28c
This patch changes Spark's build to make Scala 2.11 the default Scala version. To be clear, this does not mean that Spark will stop supporting Scala 2.10: users will still be able to compile Spark for Scala 2.10 by following the instructions on the "Building Spark" page; however, it does mean that Scala 2.11 will be the default Scala version used by our CI builds (including pull request builds). The Scala 2.11 compiler is faster than 2.10, so I think we'll be able to look forward to a slight speedup in our CI builds (it looks like it's about 2X faster for the Maven compile-only builds, for instance). After this patch is merged, I'll update Jenkins to add new compile-only jobs to ensure that Scala 2.10 compilation doesn't break. Author: Josh Rosen <joshrosen@databricks.com> Closes #10608 from JoshRosen/SPARK-6363.
253 lines
9 KiB
XML
253 lines
9 KiB
XML
<?xml version="1.0" encoding="UTF-8"?>
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<!--
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~ Licensed to the Apache Software Foundation (ASF) under one or more
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~ contributor license agreements. See the NOTICE file distributed with
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~ this work for additional information regarding copyright ownership.
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~ The ASF licenses this file to You under the Apache License, Version 2.0
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~ (the "License"); you may not use this file except in compliance with
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~ the License. You may obtain a copy of the License at
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~
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~ http://www.apache.org/licenses/LICENSE-2.0
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~
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~ Unless required by applicable law or agreed to in writing, software
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~ distributed under the License is distributed on an "AS IS" BASIS,
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~ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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~ See the License for the specific language governing permissions and
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~ limitations under the License.
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-->
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<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
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<modelVersion>4.0.0</modelVersion>
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<parent>
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<groupId>org.apache.spark</groupId>
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<artifactId>spark-parent_2.11</artifactId>
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<version>2.0.0-SNAPSHOT</version>
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<relativePath>../pom.xml</relativePath>
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</parent>
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<groupId>org.apache.spark</groupId>
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<artifactId>spark-assembly_2.11</artifactId>
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<name>Spark Project Assembly</name>
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<url>http://spark.apache.org/</url>
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<packaging>pom</packaging>
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<properties>
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<sbt.project.name>assembly</sbt.project.name>
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<spark.jar.dir>scala-${scala.binary.version}</spark.jar.dir>
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<spark.jar.basename>spark-assembly-${project.version}-hadoop${hadoop.version}.jar</spark.jar.basename>
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<spark.jar>${project.build.directory}/${spark.jar.dir}/${spark.jar.basename}</spark.jar>
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</properties>
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<dependencies>
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<dependency>
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<groupId>org.apache.spark</groupId>
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<artifactId>spark-core_${scala.binary.version}</artifactId>
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<version>${project.version}</version>
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</dependency>
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<dependency>
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<groupId>org.apache.spark</groupId>
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<artifactId>spark-mllib_${scala.binary.version}</artifactId>
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<version>${project.version}</version>
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</dependency>
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<dependency>
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<groupId>org.apache.spark</groupId>
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<artifactId>spark-streaming_${scala.binary.version}</artifactId>
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<version>${project.version}</version>
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</dependency>
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<dependency>
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<groupId>org.apache.spark</groupId>
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<artifactId>spark-graphx_${scala.binary.version}</artifactId>
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<version>${project.version}</version>
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</dependency>
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<dependency>
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<groupId>org.apache.spark</groupId>
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<artifactId>spark-sql_${scala.binary.version}</artifactId>
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<version>${project.version}</version>
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</dependency>
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<dependency>
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<groupId>org.apache.spark</groupId>
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<artifactId>spark-repl_${scala.binary.version}</artifactId>
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<version>${project.version}</version>
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</dependency>
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</dependencies>
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<build>
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<plugins>
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<plugin>
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<groupId>org.apache.maven.plugins</groupId>
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<artifactId>maven-deploy-plugin</artifactId>
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<configuration>
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<skip>true</skip>
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</configuration>
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</plugin>
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<plugin>
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<groupId>org.apache.maven.plugins</groupId>
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<artifactId>maven-install-plugin</artifactId>
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<configuration>
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<skip>true</skip>
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</configuration>
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</plugin>
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<!-- zip pyspark archives to run python application on yarn mode -->
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<plugin>
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<groupId>org.apache.maven.plugins</groupId>
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<artifactId>maven-antrun-plugin</artifactId>
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<executions>
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<execution>
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<phase>package</phase>
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<goals>
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<goal>run</goal>
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</goals>
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</execution>
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</executions>
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<configuration>
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<target>
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<delete dir="${basedir}/../python/lib/pyspark.zip"/>
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<zip destfile="${basedir}/../python/lib/pyspark.zip">
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<fileset dir="${basedir}/../python/" includes="pyspark/**/*"/>
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</zip>
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</target>
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</configuration>
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</plugin>
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<!-- Use the shade plugin to create a big JAR with all the dependencies -->
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<plugin>
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<groupId>org.apache.maven.plugins</groupId>
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<artifactId>maven-shade-plugin</artifactId>
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<configuration>
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<shadedArtifactAttached>false</shadedArtifactAttached>
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<outputFile>${spark.jar}</outputFile>
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<artifactSet>
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<includes>
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<include>*:*</include>
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</includes>
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</artifactSet>
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<filters>
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<filter>
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<artifact>*:*</artifact>
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<excludes>
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<exclude>org/datanucleus/**</exclude>
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<exclude>META-INF/*.SF</exclude>
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<exclude>META-INF/*.DSA</exclude>
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<exclude>META-INF/*.RSA</exclude>
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</excludes>
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</filter>
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</filters>
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</configuration>
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<executions>
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<execution>
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<phase>package</phase>
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<goals>
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<goal>shade</goal>
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</goals>
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<configuration>
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<transformers>
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<transformer implementation="org.apache.maven.plugins.shade.resource.ServicesResourceTransformer" />
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<transformer implementation="org.apache.maven.plugins.shade.resource.AppendingTransformer">
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<resource>META-INF/services/org.apache.hadoop.fs.FileSystem</resource>
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</transformer>
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<transformer implementation="org.apache.maven.plugins.shade.resource.AppendingTransformer">
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<resource>reference.conf</resource>
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</transformer>
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<transformer implementation="org.apache.maven.plugins.shade.resource.DontIncludeResourceTransformer">
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<resource>log4j.properties</resource>
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</transformer>
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<transformer implementation="org.apache.maven.plugins.shade.resource.ApacheLicenseResourceTransformer"/>
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<transformer implementation="org.apache.maven.plugins.shade.resource.ApacheNoticeResourceTransformer"/>
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</transformers>
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</configuration>
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</execution>
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</executions>
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</plugin>
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</plugins>
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</build>
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<profiles>
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<profile>
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<id>yarn</id>
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<dependencies>
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<dependency>
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<groupId>org.apache.spark</groupId>
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<artifactId>spark-yarn_${scala.binary.version}</artifactId>
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<version>${project.version}</version>
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</dependency>
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</dependencies>
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</profile>
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<profile>
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<id>hive</id>
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<dependencies>
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<dependency>
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<groupId>org.apache.spark</groupId>
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<artifactId>spark-hive_${scala.binary.version}</artifactId>
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<version>${project.version}</version>
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</dependency>
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</dependencies>
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</profile>
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<profile>
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<id>hive-thriftserver</id>
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<dependencies>
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<dependency>
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<groupId>org.apache.spark</groupId>
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<artifactId>spark-hive-thriftserver_${scala.binary.version}</artifactId>
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<version>${project.version}</version>
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</dependency>
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</dependencies>
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</profile>
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<profile>
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<id>spark-ganglia-lgpl</id>
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<dependencies>
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<dependency>
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<groupId>org.apache.spark</groupId>
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<artifactId>spark-ganglia-lgpl_${scala.binary.version}</artifactId>
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<version>${project.version}</version>
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</dependency>
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</dependencies>
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</profile>
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<profile>
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<id>bigtop-dist</id>
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<!-- This profile uses the assembly plugin to create a special "dist" package for BigTop
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that contains Spark but not the Hadoop JARs it depends on. -->
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<build>
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<plugins>
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<plugin>
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<groupId>org.apache.maven.plugins</groupId>
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<artifactId>maven-assembly-plugin</artifactId>
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<executions>
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<execution>
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<id>dist</id>
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<phase>package</phase>
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<goals>
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<goal>single</goal>
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</goals>
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<configuration>
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<descriptors>
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<descriptor>src/main/assembly/assembly.xml</descriptor>
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</descriptors>
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</configuration>
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</execution>
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</executions>
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</plugin>
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</plugins>
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</build>
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</profile>
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<!-- Profiles that disable inclusion of certain dependencies. -->
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<profile>
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<id>hadoop-provided</id>
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<properties>
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<hadoop.deps.scope>provided</hadoop.deps.scope>
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</properties>
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</profile>
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<profile>
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<id>hive-provided</id>
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<properties>
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<hive.deps.scope>provided</hive.deps.scope>
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</properties>
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</profile>
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<profile>
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<id>parquet-provided</id>
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<properties>
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<parquet.deps.scope>provided</parquet.deps.scope>
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</properties>
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</profile>
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</profiles>
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</project>
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