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From Liang-Chi Hsieh <vii...@gmail.com>
Subject Re: How to checkpoint and RDD after a stage and before reaching an action?
Date Mon, 06 Feb 2017 02:45:12 GMT

Hi Leo,

The checkpointing of a RDD will be performed after a job using this RDD has
completed. Since you have only one job, rdd1 will only be checkpointed after
it is finished.

To checkpoint rdd1, you can simply materialize (and maybe cache it to avoid
recomputation) rdd1 (e.g., rdd1.count) after calling rdd1.checkpoint().



leo9r wrote
> Hi,
> 
> I have a 1-action job (saveAsObjectFile at the end), that includes several
> stages. One of those stages is an expensive join "rdd1.join(rdd2)". I
> would like to checkpoint rdd1 right before the join to improve the
> stability of the job. However, what I'm seeing is that the job gets
> executed all the way to the end (saveAsObjectFile) without doing any
> checkpointing, and then re-runing the computation to checkpoint rdd1 (when
> I see the files saved to the checkpoint directory). I have no issue with
> recomputing, given that I'm not caching rdd1, but the fact that the
> checkpointing of rdd1 happens after the join brings no benefit because the
> whole DAG is executed in one piece and the job fails. If that is actually
> what is happening, what would be the best approach to solve this? 
> What I'm currently doing is to manually save rdd1 to HDFS right after the
> filter in line (4) and then load it back right before the join in line
> (11). That prevents the job from failing by splitting it into 2 jobs (ie.
> 2 actions). My expectations was that rdd1.checkpoint in line (8) was going
> to have the same effect but without the hassle of manually saving and
> loading intermediate files.
> 
> ///////////////////////////////////////////////
> 
> (1)   val rdd1 = loadData1
> (2)     .map
> (3)     .groupByKey
> (4)     .filter
> (5)
> (6)   val rdd2 = loadData2
> (7)
> (8)   rdd1.checkpoint()
> (9)
> (10)  rdd1
> (11)    .join(rdd2)
> (12)    .saveAsObjectFile(...)
> 
> /////////////////////////////////////////////
> 
> Thanks in advance,
> Leo





-----
Liang-Chi Hsieh | @viirya 
Spark Technology Center 
http://www.spark.tc/ 
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