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Date: Thu, 25 Sep 2014 22:51:36 +0000 (UTC)
From: "Chao (JIRA)" <jira@apache.org>
To: hive-dev@hadoop.apache.org
Message-ID: <JIRA.12744156.1411684981000.126473.1411685496626@Atlassian.JIRA>
In-Reply-To: <JIRA.12744156.1411684981000@Atlassian.JIRA>
References: <JIRA.12744156.1411684981000@Atlassian.JIRA>
 <JIRA.12744156.1411684981911@arcas>
Subject: [jira] [Assigned] (HIVE-8262) Create CacheTran that transforms the
 input RDD by caching it [Spark Branch]
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     [ https://issues.apache.org/jira/browse/HIVE-8262?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Chao reassigned HIVE-8262:
--------------------------

    Assignee: Chao

> Create CacheTran that transforms the input RDD by caching it [Spark Branch]
> ---------------------------------------------------------------------------
>
>                 Key: HIVE-8262
>                 URL: https://issues.apache.org/jira/browse/HIVE-8262
>             Project: Hive
>          Issue Type: Sub-task
>          Components: Spark
>            Reporter: Xuefu Zhang
>            Assignee: Chao
>
> In a few cases we need to cache a RDD to avoid recompute it for better performance. However, caching a map input RDD is different from caching a regular RDD due to SPARK-3693. The way to cache a Hadoop RDD, which is the input to MapWork, is to cache, the result RDD that is transformed from the original Hadoop RDD by applying a map function, in which <key, value> pairs are copied. To cache intermediate RDDs, such as that from a shuffle, is just calling .cache().
> This task is to create a CacheTran to capture this, which can be used to plug in Spark Plan when caching is desirable. 


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