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https://issues.apache.org/jira/browse/HDFS-347?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13570378#comment-13570378
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Colin Patrick McCabe commented on HDFS-347:
-------------------------------------------

Hi Liang,

Thanks for offering to do some tests.  Unfortunately, at this point, rebasing 
off of branch-2 would be a lot of work.  Are you sure that you can't simply run 
against trunk?

There should be no problem running against trunk with something like this:
{code}
cd hbase
git clean -fdqx
mvn package -Dtar -Pnative -Dhadoop.profile=2.0 -Dhadoop.version=3.0.0-SNAPSHOT 
\
  -Dcdh.hadoop.version=3.0.0-SNAPSHOT -DskipTests -Dmaven.javadoc.skip=true
{code}

Obviously, when you untar {{./target/hbase-0.94.2-cdh4.3.0-SNAPSHOT.tar.gz}} 
(or whatever it ends up being called), you have to be sure to replace the 
3.0.0-SNAPSHOT Hadoop jars it pulled from upstream with the hadoop jars you 
built yourself from HDFS-347.  But aside from that, it should all just work.
                
> DFS read performance suboptimal when client co-located on nodes with data
> -------------------------------------------------------------------------
>
>                 Key: HDFS-347
>                 URL: https://issues.apache.org/jira/browse/HDFS-347
>             Project: Hadoop HDFS
>          Issue Type: Improvement
>          Components: datanode, hdfs-client, performance
>            Reporter: George Porter
>            Assignee: Colin Patrick McCabe
>         Attachments: 2013.01.28.design.pdf, 2013.01.31.consolidated2.patch, 
> 2013.01.31.consolidated.patch, all.tsv, BlockReaderLocal1.txt, full.patch, 
> HADOOP-4801.1.patch, HADOOP-4801.2.patch, HADOOP-4801.3.patch, 
> HDFS-347-016_cleaned.patch, HDFS-347.016.patch, HDFS-347.017.clean.patch, 
> HDFS-347.017.patch, HDFS-347.018.clean.patch, HDFS-347.018.patch2, 
> HDFS-347.019.patch, HDFS-347.020.patch, HDFS-347.021.patch, 
> HDFS-347.022.patch, HDFS-347.024.patch, HDFS-347.025.patch, 
> HDFS-347.026.patch, HDFS-347.027.patch, HDFS-347.029.patch, 
> HDFS-347.030.patch, HDFS-347.033.patch, HDFS-347.035.patch, 
> HDFS-347-branch-20-append.txt, hdfs-347-merge.txt, hdfs-347-merge.txt, 
> hdfs-347-merge.txt, hdfs-347.png, hdfs-347.txt, local-reads-doc
>
>
> One of the major strategies Hadoop uses to get scalable data processing is to 
> move the code to the data.  However, putting the DFS client on the same 
> physical node as the data blocks it acts on doesn't improve read performance 
> as much as expected.
> After looking at Hadoop and O/S traces (via HADOOP-4049), I think the problem 
> is due to the HDFS streaming protocol causing many more read I/O operations 
> (iops) than necessary.  Consider the case of a DFSClient fetching a 64 MB 
> disk block from the DataNode process (running in a separate JVM) running on 
> the same machine.  The DataNode will satisfy the single disk block request by 
> sending data back to the HDFS client in 64-KB chunks.  In BlockSender.java, 
> this is done in the sendChunk() method, relying on Java's transferTo() 
> method.  Depending on the host O/S and JVM implementation, transferTo() is 
> implemented as either a sendfilev() syscall or a pair of mmap() and write().  
> In either case, each chunk is read from the disk by issuing a separate I/O 
> operation for each chunk.  The result is that the single request for a 64-MB 
> block ends up hitting the disk as over a thousand smaller requests for 64-KB 
> each.
> Since the DFSClient runs in a different JVM and process than the DataNode, 
> shuttling data from the disk to the DFSClient also results in context 
> switches each time network packets get sent (in this case, the 64-kb chunk 
> turns into a large number of 1500 byte packet send operations).  Thus we see 
> a large number of context switches for each block send operation.
> I'd like to get some feedback on the best way to address this, but I think 
> providing a mechanism for a DFSClient to directly open data blocks that 
> happen to be on the same machine.  It could do this by examining the set of 
> LocatedBlocks returned by the NameNode, marking those that should be resident 
> on the local host.  Since the DataNode and DFSClient (probably) share the 
> same hadoop configuration, the DFSClient should be able to find the files 
> holding the block data, and it could directly open them and send data back to 
> the client.  This would avoid the context switches imposed by the network 
> layer, and would allow for much larger read buffers than 64KB, which should 
> reduce the number of iops imposed by each read block operation.

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