[jvm-packages] Require vanilla Apache Spark (#3854)

This commit is contained in:
Philip Hyunsu Cho 2018-11-01 19:15:40 -07:00 committed by Nan Zhu
parent 2febc105a4
commit 583c88bce7
2 changed files with 10 additions and 4 deletions

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@ -58,9 +58,11 @@ For sbt, please add the repository and dependency in build.sbt as following:
If you want to use XGBoost4J-Spark, replace ``xgboost4j`` with ``xgboost4j-spark``.
.. note:: XGBoost4J-Spark requires Spark 2.3+
.. note:: XGBoost4J-Spark requires Apache Spark 2.3+
XGBoost4J-Spark now requires 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.
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 <https://spark.apache.org/>`_. **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
============================

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@ -61,9 +61,13 @@ and then refer to the snapshot dependency by adding:
<version>next_version_num-SNAPSHOT</version>
</dependency>
.. note:: XGBoost4J-Spark requires Spark 2.3+
.. note:: XGBoost4J-Spark requires Apache Spark 2.3+
XGBoost4J-Spark now requires 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.
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 <https://spark.apache.org/>`_. **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
.. note:: Use of Python in XGBoost4J-Spark