specify spark version (#1224)
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@ -11,9 +11,9 @@ Currently, XGBoost4J only support installation from source. Building XGBoost4J u
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Before you install XGBoost4J, you need to define environment variable `JAVA_HOME` as your JDK directory to ensure that your compiler can find `jni.h` correctly, since XGBoost4J relies on JNI to implement the interaction between the JVM and native libraries.
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Before you install XGBoost4J, you need to define environment variable `JAVA_HOME` as your JDK directory to ensure that your compiler can find `jni.h` correctly, since XGBoost4J relies on JNI to implement the interaction between the JVM and native libraries.
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After your `JAVA_HOME` is defined correctly, it is as simple as run `mvn package` under jvm-packages directory to install XGBoost4J.
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After your `JAVA_HOME` is defined correctly, it is as simple as run `mvn package` under jvm-packages directory to install XGBoost4J. You can also skip the tests by running `mvn -DskipTests=true package`, if you are sure about the correctness of your local setup.
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NOTE: XGBoost4J requires to run with Spark 1.6 or newer
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XGBoost4J-Spark which integrates XGBoost with Spark requires to run with Spark 1.6 or newer (the default version is 1.6.1). You can build XGBoost4J-Spark as a component of XGBoost4J by running `mvn package` or specifying the spark version by `mvn -Dspark.version=1.6.0 package`.
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Contents
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Contents
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--------
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--------
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@ -23,6 +23,18 @@
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<module>xgboost4j-spark</module>
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<module>xgboost4j-spark</module>
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<module>xgboost4j-flink</module>
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<module>xgboost4j-flink</module>
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</modules>
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</modules>
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<profiles>
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<profile>
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<id>spark-1.x</id>
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<activation>
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<activeByDefault>true</activeByDefault>
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</activation>
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<properties>
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<spark.version>1.6.1</spark.version>
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<scala.binary.version>2.10</scala.binary.version>
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</properties>
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</profile>
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</profiles>
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<build>
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<build>
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<plugins>
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<plugins>
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<plugin>
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<plugin>
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@ -28,8 +28,8 @@
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</dependency>
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</dependency>
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<dependency>
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<dependency>
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<groupId>org.apache.spark</groupId>
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<groupId>org.apache.spark</groupId>
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<artifactId>spark-mllib_2.10</artifactId>
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<artifactId>spark-mllib_${scala.binary.version}</artifactId>
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<version>1.6.1</version>
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<version>${spark.version}</version>
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</dependency>
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</dependency>
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</dependencies>
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</dependencies>
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</project>
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</project>
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