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From "Raghu Angadi (JIRA)" <j...@apache.org>
Subject [jira] Commented: (HADOOP-3205) Read multiple chunks directly from FSInputChecker subclass into user buffers
Date Mon, 21 Dec 2009 08:56:18 GMT

    [ https://issues.apache.org/jira/browse/HADOOP-3205?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12793123#action_12793123
] 

Raghu Angadi commented on HADOOP-3205:
--------------------------------------


+1. The patch looks good.  

> Like the new comments and test modifications. 
thanks for good comments and javadoc.

I find it surprising as well, that avoiding a buffer copy does not show any improvement (so
is 13% for function calls or other java voodoo). 

Limit of 32 chunks : it is true that your tests didn't show benefit beyond that for LocalFileSystem..
not sure if that justifies limiting fs implementation's access to user buffer. Is to reduce
memory allocated for checksum buffer?

I will run the tests on my laptop. The jira need not wait for my results.

> Read multiple chunks directly from FSInputChecker subclass into user buffers
> ----------------------------------------------------------------------------
>
>                 Key: HADOOP-3205
>                 URL: https://issues.apache.org/jira/browse/HADOOP-3205
>             Project: Hadoop Common
>          Issue Type: Bug
>          Components: fs
>    Affects Versions: 0.22.0
>            Reporter: Raghu Angadi
>            Assignee: Todd Lipcon
>         Attachments: hadoop-3205.txt, hadoop-3205.txt, hadoop-3205.txt, hadoop-3205.txt,
hadoop-3205.txt
>
>
> Implementations of FSInputChecker and FSOutputSummer like DFS do not have access to full
user buffer. At any time DFS can access only up to 512 bytes even though user usually reads
with a much larger buffer (often controlled by io.file.buffer.size). This requires implementations
to double buffer data if an implementation wants to read or write larger chunks of data from
underlying storage.
> We could separate changes for FSInputChecker and FSOutputSummer into two separate jiras.

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