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https://issues.apache.org/jira/browse/SPARK-1855?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14001378#comment-14001378
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Mridul Muralidharan commented on SPARK-1855:
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[email protected]'s comment --
We do actually have replicated StorageLevels in Spark. You can use
MEMORY_AND_DISK_2 or construct your own StorageLevel with your own custom
replication factor.
BTW you guys should probably have this discussion on the JIRA rather than the
dev list; I think the replies somehow ended up on the dev list.
> Provide memory-and-local-disk RDD checkpointing
> -----------------------------------------------
>
> Key: SPARK-1855
> URL: https://issues.apache.org/jira/browse/SPARK-1855
> Project: Spark
> Issue Type: New Feature
> Components: MLlib, Spark Core
> Affects Versions: 1.0.0
> Reporter: Xiangrui Meng
>
> Checkpointing is used to cut long lineage while maintaining fault tolerance.
> The current implementation is HDFS-based. Using the BlockRDD we can create
> in-memory-and-local-disk (with replication) checkpoints that are not as
> reliable as HDFS-based solution but faster.
> It can help applications that require many iterations.
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