Github user mridulm commented on the issue:
https://github.com/apache/spark/pull/16574
Couple of points :
a) Can recomputation be expensive ? Unfortunately, yes if not used
properly. For better or for worse, this has been the implementation in spark
since early days - pre-0.5; and the costs are known. Particularly given Apache
spark's ability to cache/checkpoint data, the assumption is that shuffle is
more expensive. This might not hold anymore actually, given improvements since
1.0 - but only redoing benchmarks will give a better picture.
b) If we were to do a shuffle for cartesian, I would implement it
differently - take a look at how Apache Pig has implemented it for a more
efficient way to do it. (Btw, I dont think the impl in the PR actually works,
but I have not looked at it in detail).
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