[
https://issues.apache.org/jira/browse/HDFS-347?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13565655#comment-13565655
]
Brandon Li commented on HDFS-347:
---------------------------------
I did some tests comparing the read performance with and without unix domain
socket enabled. The result is not what I expected.
1. Apply latest patch to trunk and start a one-datanode cluster on a linux
box(Linux version 2.6.18-238, 15GB memory).
2. copy a 1GB local file to HDFS.
3. read it back 4 times (copyToLocal) without enabling unix domain socket
support, and the results:
|| | read 1| read 2 | read 3|read4||
||real | 0m6.655s| 0m7.080s |0m6.680s|0m6.680s ||
||user | 0m4.340s| 0m4.533s|0m4.459s| 0m4.563s ||
||sys |0m3.544s| 0m3.525s |0m3.484s| 0m3.438s ||
4. add the following to hdfs-site.xml
<property>
<name>dfs.domain.socket.path</name>
<value>/grid/0/test/unixsocket</value>
</property>
<property>
<name>dfs.client.domain.socket.data.traffic</name>
<value>true</value>
</property>
5. restart the cluster, format namenode, copy 1GB file, read it back 4 times.
The new results:
|| | read 1| read 2 | read 3|read4||
||real | 0m8.296s|0m7.811s|0m7.960s|0m7.803s ||
||user |0m5.129s |0m5.172s|0m5.197s|0m5.018s ||
||sys | 0m3.643s|0m3.572s|0m3.701s|0m3.910s ||
> 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, 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.
--
This message is automatically generated by JIRA.
If you think it was sent incorrectly, please contact your JIRA administrators
For more information on JIRA, see: http://www.atlassian.com/software/jira
