Github user marmbrus commented on the pull request:
https://github.com/apache/spark/pull/5714#issuecomment-107257458
In my opinion this bug is pretty minor and has an easy workaround (just
create a new dataframe) so I don't really think we need to rush in a solution.
I was suggesting a better solution that does not make the dataframe have
mutable state. Change the internals of `CacheManager` to create its own query
execution instead of using the `executedPlan` from the DataFrame itself, so
that `withCachedData` is not materialized by calling `.cache()`.
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