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Posted to dev@tinkerpop.apache.org by "stephen mallette (JIRA)" <ji...@apache.org> on 2018/10/27 14:35:00 UTC
[jira] [Updated] (TINKERPOP-2081) PersistedOutputRDD materialises
rdd lazily with Spark 2.x
[ https://issues.apache.org/jira/browse/TINKERPOP-2081?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
stephen mallette updated TINKERPOP-2081:
----------------------------------------
Component/s: hadoop
> PersistedOutputRDD materialises rdd lazily with Spark 2.x
> ---------------------------------------------------------
>
> Key: TINKERPOP-2081
> URL: https://issues.apache.org/jira/browse/TINKERPOP-2081
> Project: TinkerPop
> Issue Type: Bug
> Components: hadoop
> Affects Versions: 3.3.4
> Reporter: Artem Aliev
> Priority: Major
>
> PersistedOutputRDD is not actually persist RDD in spark memory but mark it for lazy caching in the future. It looks like caching was eager in Spark 1.6, but in spark 2.0 it lazy.
> The lazy caching looks wrong for this case, the source graph could be changed after snapshot is created and snapshot should not be affected by that changes.
> The fix itself is simple: PersistedOutputRDD should call any spark action to trigger eager caching. For example count()
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