Github user witgo commented on the pull request:
https://github.com/apache/spark/pull/929#issuecomment-45069637
@mengxr
By calling this method `RDD.checkpoint`, `ContextCleaner` can clean up the
shuffle data, reduce disk usage.
Just as described in the table below.
| Item | Description |
| ------------- | ----------- |
|data| `700 million`|
|code|`val model = ALS.trainImplicit(ratings, 25, 30, 0.065, -1, 40.0)`|
|shuffle write| `4.72T`|
|largest local dir|`200G`|
|checkpoint dir|`16.6G`|
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