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https://issues.apache.org/jira/browse/SPARK-6112?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14594747#comment-14594747
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Arpit Agarwal commented on SPARK-6112:
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Hi [~bghit], thanks for trying out the Lazy Persist feature in HDFS.
The setup requires a few administrative steps.
# Mount a tmpfs volume on each DataNode.
# Tag it with the RAM_DISK storage type via the {{dfs.datanode.data.dir}}
property in hdfs-site.xml.
# Set the {{dfs.datanode.max.locked.memory}} property to limit the total amount
of locked RAM+tmpfs used by each DataNode.
Apache Hadoop 2.7.1 will include detailed documentation and we are looking into
simpler configuration in 2.8.0.
> Provide external block store support through HDFS RAM_DISK
> ----------------------------------------------------------
>
> Key: SPARK-6112
> URL: https://issues.apache.org/jira/browse/SPARK-6112
> Project: Spark
> Issue Type: New Feature
> Components: Block Manager
> Reporter: Zhan Zhang
> Attachments: SparkOffheapsupportbyHDFS.pdf
>
>
> HDFS Lazy_Persist policy provide possibility to cache the RDD off_heap in
> hdfs. We may want to provide similar capacity to Tachyon by leveraging hdfs
> RAM_DISK feature, if the user environment does not have tachyon deployed.
> With this feature, it potentially provides possibility to share RDD in memory
> across different jobs and even share with jobs other than spark, and avoid
> the RDD recomputation if executors crash.
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