When using xgboost4j-spark I had executors getting killed much more
often than i would expect by yarn for overrunning their memory limits,
based on the memoryOverhead provided. It looks like a significant
amount of this is because dmatrix's were being created but not released,
because they were only released when the GC decided it was time to
cleanup the references.
Rather than waiting for the GC, relesae the DMatrix's when we know
they are no longer necessary.
Storing and then loading a model loses any eval_metric that was
provided. This causes implementations that always store/load, like
xgboost4j-spark, to be unable to eval with the desired metric.
ebernhardson