reduce memory usage in lightgbm, fix frozen jobs, add more debug logging #586
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fixes several issues found by an internal data scientist when running lightgbm:
1.) reduce memory usage and execution time by selecting only relevant columns prior to calling mapPartitions in training
2.) fix frozen jobs if spark.task.cpus > 1 (driver expects more workers than it gets)
3.) add more debug logging for dataset format