################### XGBoost JVM Package ################### .. raw:: html Build Status GitHub license You have found the XGBoost JVM Package! ************ Installation ************ Installation from source ======================== Building XGBoost4J using Maven requires Maven 3 or newer, Java 7+ and CMake 3.2+ for compiling the JNI bindings. 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. 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. To publish the artifacts to your local maven repository, run .. code-block:: bash mvn install Or, if you would like to skip tests, run .. code-block:: bash mvn -DskipTests install This command will publish the xgboost binaries, the compiled java classes as well as the java sources to your local repository. Then you can use XGBoost4J in your Java projects by including the following dependency in ``pom.xml``: .. code-block:: xml ml.dmlc xgboost4j latest_source_version_num For sbt, please add the repository and dependency in build.sbt as following: .. code-block:: scala resolvers += "Local Maven Repository" at "file://"+Path.userHome.absolutePath+"/.m2/repository" "ml.dmlc" % "xgboost4j" % "latest_source_version_num" If you want to use XGBoost4J-Spark, replace ``xgboost4j`` with ``xgboost4j-spark``. .. note:: XGBoost4J-Spark requires Apache Spark 2.3+ XGBoost4J-Spark now requires **Apache Spark 2.3+**. Latest versions of XGBoost4J-Spark uses facilities of `org.apache.spark.ml.param.shared` extensively to provide for a tight integration with Spark MLLIB framework, and these facilities are not fully available on earlier versions of Spark. Also, make sure to install Spark directly from `Apache website `_. **Upstream XGBoost is not guaranteed to work with third-party distributions of Spark, such as Cloudera Spark.** Consult appropriate third parties to obtain their distribution of XGBoost. Installation from maven repo ============================ Access release version ---------------------- .. code-block:: xml :caption: maven ml.dmlc xgboost4j latest_version_num .. code-block:: scala :caption: sbt "ml.dmlc" % "xgboost4j" % "latest_version_num" This will checkout the latest stable version from the Maven Central. For the latest release version number, please check `here `_. if you want to use XGBoost4J-Spark, replace ``xgboost4j`` with ``xgboost4j-spark``. Access SNAPSHOT version ----------------------- You need to add GitHub as repo: .. code-block:: xml :caption: maven GitHub Repo GitHub Repo https://raw.githubusercontent.com/CodingCat/xgboost/maven-repo/ .. code-block:: scala :caption: sbt resolvers += "GitHub Repo" at "https://raw.githubusercontent.com/CodingCat/xgboost/maven-repo/" Then add dependency as following: .. code-block:: xml :caption: maven ml.dmlc xgboost4j latest_version_num .. code-block:: scala :caption: sbt "ml.dmlc" % "xgboost4j" % "latest_version_num" For the latest release version number, please check `here `_. .. note:: Windows not supported by published JARs The published JARs from the Maven Central and GitHub currently only supports Linux and MacOS. Windows users should consider building XGBoost4J / XGBoost4J-Spark from the source. Alternatively, checkout pre-built JARs from `criteo-forks/xgboost-jars `_. Enabling OpenMP for Mac OS -------------------------- If you are on Mac OS and using a compiler that supports OpenMP, you need to go to the file ``xgboost/jvm-packages/create_jni.py`` and comment out the line .. code-block:: python CONFIG["USE_OPENMP"] = "OFF" in order to get the benefit of multi-threading. ******** Contents ******** .. toctree:: :maxdepth: 2 java_intro XGBoost4J-Spark Tutorial Code Examples XGBoost4J Java API XGBoost4J Scala API XGBoost4J-Spark Scala API XGBoost4J-Flink Scala API