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From "Jim Kellerman (JIRA)" <j...@apache.org>
Subject [jira] Commented: (HADOOP-3113) Provide a configurable way for DFSOututStream.flush() to flush data to real block file on DataNode.
Date Sun, 30 Mar 2008 16:49:24 GMT

    [ https://issues.apache.org/jira/browse/HADOOP-3113?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12583460#action_12583460
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Jim Kellerman commented on HADOOP-3113:
---------------------------------------

> dhruba borthakur - 29/Mar/08 11:03 PM
> I can make the configurable to be per file, but maybe it makes more sense to make it
applicable to the
> entire system. The reason being that datanodes do not know much about the name of the
HDFS file
> that a block belongs to. To make this configurable "per file" would need lots of protocol
change.

I don't think it needs to be per file. Aside from our redo log, other files are written and
then immediately
closed and re-opened for read.

> If a client dies while writing to the last block of that file, that block is not yet
part of the blocksmap in the
> namenode. (A block gets inserted in the blocksmap when a complete block is received by
the datanode
> and it sends a blockReceived message to the namenode). If the lease for this file on
the namenode
> expires before the block report from the datanode arrives, then the namenode will erroneously
think
> that no datanodes have a copy of that block. As part of lease recovery, the namenode
will delete the
> last block of the file because it has no entry in the blocksMap. To prevent this from
occuring, the block
> report periodicity should be set to 30 minutes.

I think this is ok, but let me give a scenario to verify that my understanding is correct.

We open our redo log and flush it either every N seconds or after M records have been written.
If the process writing the log crashes, we will notice much sooner than the file lease timeout.
At that point another process should be able to open the file for read, and all flushed data

will be visible, unflushed data will not. Since the amount of unflushed data should be small
the amount of data lost should be minimal. Once the redo log has been read and processed,
the file will be deleted by the process reading the file.

If this is how this patch works, +1.

> Provide a configurable way for DFSOututStream.flush() to flush data to real block file
on DataNode.
> ---------------------------------------------------------------------------------------------------
>
>                 Key: HADOOP-3113
>                 URL: https://issues.apache.org/jira/browse/HADOOP-3113
>             Project: Hadoop Core
>          Issue Type: Bug
>          Components: dfs
>            Reporter: dhruba borthakur
>            Assignee: dhruba borthakur
>         Attachments: noTmpFile.patch
>
>
> DFSOutputStream has a method called flush() that persists block locations on the namenode
and sends all outstanding data to all datanodes in the pipeline. However, this data goes to
the tmp file on the datanode(s). When the block is closed, the tmp files is renamed to be
the real block file. If the datanode(s) dies before the block is compete, then entire block
is lost. This behaviour wil be fixed in HADOOP-1700.
> However, in the short term, a configuration paramater can be used to allow datanodes
to write to the real block file directly, thereby avoiding writing to the tmp file. This means
that data that is flushed successfully by a client does not get lost even if the datanode(s)
or client dies.
> The Namenode already has code to pick the largest replica (if multiple datanodes have
different sizes of this block). Also, the namenode has code to not trigger replication request
if the file is still being written to.
> The only caveat that I can think of is that the block report periodicity should be much
much smaller that the lease timeout period. A block report adds the being-written-to blocks
to the blocksMap thereby avoiding any cleanup that a lease expiry processing might have otherwise
done.
> Not all requirements specified by HADOOP-1700 are supported by this approach, but it
could still be helpful (in the short term) for a wide range of applications.

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