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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2014/11/18 15:55:33 UTC
[jira] [Commented] (SPARK-2418) Custom checkpointing with an
external function as parameter
[ https://issues.apache.org/jira/browse/SPARK-2418?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14216251#comment-14216251 ]
Apache Spark commented on SPARK-2418:
-------------------------------------
User 'Forevian' has created a pull request for this issue:
https://github.com/apache/spark/pull/3346
> Custom checkpointing with an external function as parameter
> -----------------------------------------------------------
>
> Key: SPARK-2418
> URL: https://issues.apache.org/jira/browse/SPARK-2418
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core
> Affects Versions: 1.0.0
> Reporter: András Barják
>
> If a job consists of many shuffle heavy transformations the current resilience model might be unsatisfactory. In our current use-case we need a persistent checkpoint that we can use to save our RDDs on disk in a custom location and load it back even if the driver dies. (Possible other use cases: store the checkpointed data in various formats: SequenceFile, csv, Parquet file, MySQL etc.)
> After talking to [~pwendell] at the Spark Summit 2014 we concluded that a checkpoint where one can customize the saving and RDD reloading behavior can be a good solution. I am open to further suggestions if you have better ideas about how to make checkpointing more flexible.
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