spark-instrumented-optimizer/assembly/pom.xml
Josh Rosen 75879ac3c0 [SPARK-14925][BUILD] Re-introduce 'unused' dependency so that published POMs are flattened
Spark's published POMs are supposed to be flattened and not contain variable substitution (see SPARK-3812), but the dummy dependency that was required for this was accidentally removed. We should re-introduce this dependency in order to fix an issue where the un-flattened POMs cause the wrong dependencies to be included in Scala 2.10 published POMs.

Author: Josh Rosen <joshrosen@databricks.com>

Closes #12706 from JoshRosen/SPARK-14925-published-poms-should-be-flattened.
2016-04-26 15:14:17 -07:00

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7.4 KiB
XML

<?xml version="1.0" encoding="UTF-8"?>
<!--
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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">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>org.apache.spark</groupId>
<artifactId>spark-parent_2.11</artifactId>
<version>2.0.0-SNAPSHOT</version>
<relativePath>../pom.xml</relativePath>
</parent>
<groupId>org.apache.spark</groupId>
<artifactId>spark-assembly_2.11</artifactId>
<name>Spark Project Assembly</name>
<url>http://spark.apache.org/</url>
<packaging>pom</packaging>
<properties>
<sbt.project.name>assembly</sbt.project.name>
<build.testJarPhase>none</build.testJarPhase>
<build.copyDependenciesPhase>package</build.copyDependenciesPhase>
</properties>
<dependencies>
<!-- Prevent our dummy JAR from being included in Spark distributions or uploaded to YARN -->
<dependency>
<groupId>org.spark-project.spark</groupId>
<artifactId>unused</artifactId>
<version>1.0.0</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_${scala.binary.version}</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-mllib_${scala.binary.version}</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming_${scala.binary.version}</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-graphx_${scala.binary.version}</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_${scala.binary.version}</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-repl_${scala.binary.version}</artifactId>
<version>${project.version}</version>
</dependency>
<!--
Because we don't shade dependencies anymore, we need to restore Guava to compile scope so
that the libraries Spark depend on have it available. We'll package the version that Spark
uses (14.0.1) which is not the same as Hadoop dependencies, but works.
-->
<dependency>
<groupId>com.google.guava</groupId>
<artifactId>guava</artifactId>
<scope>${hadoop.deps.scope}</scope>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-deploy-plugin</artifactId>
<configuration>
<skip>true</skip>
</configuration>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-install-plugin</artifactId>
<configuration>
<skip>true</skip>
</configuration>
</plugin>
<!-- zip pyspark archives to run python application on yarn mode -->
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-antrun-plugin</artifactId>
<executions>
<execution>
<phase>package</phase>
<goals>
<goal>run</goal>
</goals>
</execution>
</executions>
<configuration>
<target>
<delete dir="${basedir}/../python/lib/pyspark.zip"/>
<zip destfile="${basedir}/../python/lib/pyspark.zip">
<fileset dir="${basedir}/../python/" includes="pyspark/**/*"/>
</zip>
</target>
</configuration>
</plugin>
</plugins>
</build>
<profiles>
<profile>
<id>yarn</id>
<dependencies>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-yarn_${scala.binary.version}</artifactId>
<version>${project.version}</version>
</dependency>
</dependencies>
</profile>
<profile>
<id>hive</id>
<dependencies>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-hive_${scala.binary.version}</artifactId>
<version>${project.version}</version>
</dependency>
</dependencies>
</profile>
<profile>
<id>hive-thriftserver</id>
<dependencies>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-hive-thriftserver_${scala.binary.version}</artifactId>
<version>${project.version}</version>
</dependency>
</dependencies>
</profile>
<profile>
<id>spark-ganglia-lgpl</id>
<dependencies>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-ganglia-lgpl_${scala.binary.version}</artifactId>
<version>${project.version}</version>
</dependency>
</dependencies>
</profile>
<profile>
<id>bigtop-dist</id>
<!-- This profile uses the assembly plugin to create a special "dist" package for BigTop
that contains Spark but not the Hadoop JARs it depends on. -->
<build>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-assembly-plugin</artifactId>
<executions>
<execution>
<id>dist</id>
<phase>package</phase>
<goals>
<goal>single</goal>
</goals>
<configuration>
<descriptors>
<descriptor>src/main/assembly/assembly.xml</descriptor>
</descriptors>
</configuration>
</execution>
</executions>
</plugin>
</plugins>
</build>
</profile>
<!-- Profiles that disable inclusion of certain dependencies. -->
<profile>
<id>hadoop-provided</id>
<properties>
<hadoop.deps.scope>provided</hadoop.deps.scope>
</properties>
</profile>
<profile>
<id>hive-provided</id>
<properties>
<hive.deps.scope>provided</hive.deps.scope>
</properties>
</profile>
<profile>
<id>parquet-provided</id>
<properties>
<parquet.deps.scope>provided</parquet.deps.scope>
</properties>
</profile>
</profiles>
</project>