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? > > > > > > > > > > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > For additional commands, e-mail: user-h...@spark.apache.org > > -- Daniel Siegmann, Software Developer Velos Accelerating Machine Learning 440 NINTH AVENUE, 11TH FLOOR, NEW YORK, NY 10001 E: daniel.siegm...@velos.io W: www.velos.io
