* cancel job instead of killing SparkContext
This PR changes the default behavior that kills SparkContext. Instead, This PR
cancels jobs when coming across task failed. That means the SparkContext is
still alive even some exceptions happen.
* add a parameter to control if killing SparkContext
* cancel the jobs the failed task belongs to
* remove the jobId from the map when one job failed.
* resolve comments
* [jvm-packages] add gpu_hist tree method
* change updater hist to grow_quantile_histmaker
* add gpu scheduling
* pass correct parameters to xgboost library
* remove debug info
* add use.cuda for pom
* add CI for gpu_hist for jvm
* add gpu unit tests
* use gpu node to build jvm
* use nvidia-docker
* Add CLI interface to create_jni.py using argparse
Co-authored-by: Hyunsu Cho <chohyu01@cs.washington.edu>
* fix type error
* Validate number of features.
* resolve comments
* add feature size for LabelPoint and DataBatch
* pass the feature size to native
* move feature size validating tests into a separate suite
* resolve comments
Co-authored-by: fis <jm.yuan@outlook.com>