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https://issues.apache.org/jira/browse/SPARK-2418?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14057081#comment-14057081
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Guoqiang Li commented on SPARK-2418:
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I think we should design it into pluggable interfaces.
reference:
[SPARK-2044|https://issues.apache.org/jira/browse/SPARK-2044]
> 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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