Github user MrMathias commented on the issue:
    If anyone are interested; checkpointing is only really documented in the 
scope of Spark streaming, however checkpointing it is extensively used in the 
ml package.
    I think the best solution is to add warnings or even errors to the 
procedures that uses checkpointing, when a checkpoint directory is not set. 
Silently ignoring checkpointInterval on heavily iterative procedures that 
easily causes memory errors, is not a good default behavior.


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