Update index.md (#3228)
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@ -34,6 +34,13 @@ This command will publish the xgboost binaries, the compiled java classes as wel
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After integrating with Dataframe/Dataset APIs of Spark 2.0, XGBoost4J-Spark only supports compile with Spark 2.x. You can build XGBoost4J-Spark as a component of XGBoost4J by running `mvn package`, and you can specify the version of spark with `mvn -Dspark.version=2.0.0 package`. (To continue working with Spark 1.x, the users are supposed to update pom.xml by modifying the properties like `spark.version`, `scala.version`, and `scala.binary.version`. Users also need to change the implementation by replacing SparkSession with SQLContext and the type of API parameters from Dataset[_] to Dataframe)
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After integrating with Dataframe/Dataset APIs of Spark 2.0, XGBoost4J-Spark only supports compile with Spark 2.x. You can build XGBoost4J-Spark as a component of XGBoost4J by running `mvn package`, and you can specify the version of spark with `mvn -Dspark.version=2.0.0 package`. (To continue working with Spark 1.x, the users are supposed to update pom.xml by modifying the properties like `spark.version`, `scala.version`, and `scala.binary.version`. Users also need to change the implementation by replacing SparkSession with SQLContext and the type of API parameters from Dataset[_] to Dataframe)
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#### Enabling OpenMP for Mac OS
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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
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```python
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CONFIG["USE_OPENMP"] = "OFF"
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```
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in order to get the benefit of multi-threading.
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Contents
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Contents
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--------
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--------
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* [Java Overview Tutorial](java_intro.md)
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* [Java Overview Tutorial](java_intro.md)
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