* [jvm-packages] move the dmatrix building into rabit context (#7823)
This fixes the QuantileDeviceDMatrix in distributed environment.
* [doc] update the jvm tutorial to 1.6.1 [skip ci] (#7834)
* [Breaking][jvm-packages] Use barrier execution mode (#7836)
With the introduction of the barrier execution mode. we don't need to kill SparkContext when some xgboost tasks failed. Instead, Spark will handle the errors for us. So in this PR, `killSparkContextOnWorkerFailure` parameter is deleted.
* [doc] remove the doc about killing SparkContext [skip ci] (#7840)
* [jvm-package] remove the coalesce in barrier mode (#7846)
* [jvm-packages] Fix model compatibility (#7845)
* Ignore all Java exceptions when looking for Linux musl support (#7844)
Co-authored-by: Bobby Wang <wbo4958@gmail.com>
Co-authored-by: Michael Allman <msa@allman.ms>
* Add `XGBOOST_RABIT_TRACKER_IP_FOR_TEST` to set rabit tracker IP
* change spark and rabit tracker IP to 127.0.0.1on GitHub Action.
Co-authored-by: fis <jm.yuan@outlook.com>
* Automatically set maximize_evaluation_metrics if not explicitly given.
* When custom_eval is set, require maximize_evaluation_metrics.
* Update documents on early stop in XGBoost4J-Spark.
* Fix code error.
* Fix early stop with xgboost4j-spark
* Update XGBoost.java
* Update XGBoost.java
* Update XGBoost.java
To use -Float.MAX_VALUE as the lower bound, in case there is positive metric.
* Only update best score if the current score is better (no update when equal)
* Update xgboost-spark tutorial to fix early stopping docs.
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* fix scalastyle error
* fix scalastyle error
* fix scalastyle error
* fix scalastyle error
* wrap iterators
* enable copartition training and validationset
* add parameters
* converge code path and have init unit test
* enable multi evals for ranking
* unit test and doc
* update example
* fix early stopping
* address the offline comments
* udpate doc
* test eval metrics
* fix compilation issue
* fix example
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* fix scalastyle error
* fix scalastyle error
* fix scalastyle error
* fix scalastyle error
* documenting tracker
* Make it a separate note
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* fix scalastyle error
* fix scalastyle error
* fix scalastyle error
* fix scalastyle error
* temp
* add method for classifier and regressor
* update tutorial
* address the comments
* update
* Add XGBRanker to Python API doc
* Show inherited members of XGBRegressor in API doc, since XGBRegressor uses default methods from XGBModel
* Add table of contents to Python API doc
* Skip JVM doc download if not available
* Show inherited members for XGBRegressor and XGBRanker
* Expose XGBRanker to Python XGBoost module directory
* Add docstring to XGBRegressor.predict() and XGBRanker.predict()
* Fix rendering errors in Python docstrings
* Fix lint
* Adding Java/Scala doc build to Jenkins CI
* Deploy built doc to S3 bucket
* Build doc only for branches
* Build doc first, to get doc faster for branch updates
* Have ReadTheDocs download doc tarball from S3
* Update JVM doc links
* Put doc build commands in a script
* Specify Spark 2.3+ requirement for XGBoost4J-Spark
* Build GPU wheel without NCCL, to reduce binary size
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* fix scalastyle error
* fix scalastyle error
* add new
* update doc
* finish Gang Scheduling
* more
* intro
* Add sections: Prediction, Model persistence and ML pipeline.
* Add XGBoost4j-Spark MLlib pipeline example
* partial finished version
* finish the doc
* adjust code
* fix the doc
* use rst
* Convert XGBoost4J-Spark tutorial to reST
* Bring XGBoost4J up to date
* add note about using hdfs
* remove duplicate file
* fix descriptions
* update doc
* Wrap HDFS/S3 export support as a note
* update
* wrap indexing_mode example in code block
