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From "Doug Cutting (JIRA)" <j...@apache.org>
Subject [jira] Commented: (HADOOP-66) dfs client writes all data for a chunk to /tmp
Date Tue, 07 Mar 2006 20:33:40 GMT
    [ http://issues.apache.org/jira/browse/HADOOP-66?page=comments#action_12369308 ] 

Doug Cutting commented on HADOOP-66:
------------------------------------

It's hard to resume writing a block when a connection fails, since you don't know how much
of the previous write succeeded.  Currently the block is streamed over TCP connections.  We
could instead write it as a series of length-prefixed buffers, and query the remote datanode
on reconnect about which buffers it had recieved, etc.  But that seems like reinventing a
lot of TCP.

If the datanode goes down then currently the entire block is in a temp file so that it can
instead be written to a different datanode.  Thus if datanodes die during, e.g., a reduce,
then the reduce task does not have to restart.  But if reduce tasks are running on the same
pool of machines as datanodes, then, when a node fails, some reduce tasks will need to be
restarted anyway.  So I agree that this may not be helping us much.  I think throwing an exception
when the connection to the datanode fails would be fine.

> dfs client writes all data for a chunk to /tmp
> ----------------------------------------------
>
>          Key: HADOOP-66
>          URL: http://issues.apache.org/jira/browse/HADOOP-66
>      Project: Hadoop
>         Type: Bug
>   Components: dfs
>     Versions: 0.1
>     Reporter: Sameer Paranjpye
>      Fix For: 0.1

>
> The dfs client writes all the data for the current chunk to a file in /tmp, when the
chunk is complete it is shipped out to the Datanodes. This can cause /tmp to fill up fast
when a lot of files are being written. A potentially better scheme is to buffer the written
data in RAM (application code can set the buffer size) and flush it to the Datanodes when
the buffer fills up.

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