But that requires an (unnecessary) load from disk.
I have run into this same issue, where we want to save intermediate results
but continue processing. The cache / persist feature of Spark doesn't seem
designed for this case. Unfortunately I'm not aware of a better solution
with the current version of Spark.
On Mon, Nov 10, 2014 at 5:15 PM, Sean Owen so...@cloudera.com wrote:
Well you can always create C by loading B from disk, and likewise for
E / D. No need for any custom procedure.
On Mon, Nov 10, 2014 at 7:33 PM, Benyi Wang bewang.t...@gmail.com wrote:
When I have a multi-step process flow like this:
A - B - C - D - E - F
I need to store B and D's results into parquet files
B.saveAsParquetFile
D.saveAsParquetFile
If I don't cache/persist any step, spark might recompute from A,B,C,D
and E
if something is wrong in F.
Of course, I'd better cache all steps if I have enough memory to avoid
this
re-computation, or persist result to disk. But persisting B and D seems
duplicate with saving B and D as parquet files.
I'm wondering if spark can restore B and D from the parquet files using a
customized persist and restore procedure?
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