[ https://issues.apache.org/jira/browse/HDFS-347?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13495966#comment-13495966 ]
Todd Lipcon commented on HDFS-347: ---------------------------------- Oops, forgot the link to my improved code: https://github.com/toddlipcon/hadoop-common/tree/hdfs-347-colin (has some hackiness in places, was just doing it to test out the performance of these fixes) > 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: data-node, hdfs client, performance > Reporter: George Porter > Assignee: Colin Patrick McCabe > Attachments: all.tsv, BlockReaderLocal1.txt, 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-branch-20-append.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