Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/13419
I will prefer refreshing the dataset every time a dataset is reloaded but
keeping existing ones unchanged.
~~~scala
val df1 = sqlContext.read.parquet(dir).cache()
df1.count() // outputs 1000
sqlContext.range(10).write.mode("overwrite").parquet(dir)
val df2 = sqlContext.read.parquet(dir).count() // outputs 10
df2.count() // outputs 10
df1.count() // still outputs 1000 because it was cached
~~~
Neither approach is perfectly safe. So I don't have no strong preference on
either.
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