Spark’s cache is fault-tolerant – if any partition of an RDD is lost, it will
automatically be recomputed using the transformations that originally created
it.
> On Mar 23, 2017, at 4:11 AM, nayan sharma wrote:
>
> In case of task failures,does spark clear the
In case of task failures,does spark clear the persisted RDD
(StorageLevel.MEMORY_ONLY_SER) and recompute them again when the task is
attempted to start from beginning. Or will the cached RDD be appended.
How does spark checks whether the RDD has been cached and skips the caching
step for a
I am not pretty sure, but:
- if RDD persisted in memory then on task fail executor JVM process fails
too, so the memory is released
- if RDD persisted on disk then on task fail Spark shutdown hook just
wipes temp files
On Thu, Mar 23, 2017 at 10:55 AM, Jörn Franke wrote:
What do you mean by clear ? What is the use case?
> On 23 Mar 2017, at 10:16, nayan sharma wrote:
>
> Does Spark clears the persisted RDD in case if the task fails ?
>
> Regards,
>
> Nayan
Does Spark clears the persisted RDD in case if the task fails ?
Regards,
Nayan