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From "Todd Lipcon (JIRA)" <j...@apache.org>
Subject [jira] Commented: (HDFS-347) DFS read performance suboptimal when client co-located on nodes with data
Date Mon, 12 Oct 2009 08:38:31 GMT

    [ https://issues.apache.org/jira/browse/HDFS-347?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12764603#action_12764603
] 

Todd Lipcon commented on HDFS-347:
----------------------------------

Hey Dhruba,

The connect-back is definitely still up for discussion. I think it's good from a security
standpoint to verify that the client is speaking to the datanode and not an imposter. This
is definitely the simplest part of the code, though, so we can easily change it if people
disagree with me.

I'm still trying to figure out the reason for the overhead. So far, my thoughts are:
# Checksumming (I was comparing to RawLocalFileSystem, not ChecksumFileSystem). This is better
in 0.21 with the new PureJavaCrc32, but still accounts for some overhead
# In the above measurements I'm using FileChannel.map to get MappedByteBuffers for the block
and metadata files, then using .get() to do copies into the provided arrays. Profiling shows
most of the time in java.nio.Bits.copyToByteArray. Right now all transfers from these mapped
buffers are checksum-sized (512 bytes by default) and there appears to be a lot of overhead
there. Next order of business, performance wise, is to see if introducing a 64KB byte[] buffer
will improve things somewhat. This does not apply to BlockSender, though, since that already
forms packets of (I think) 10 checksum chunks at a time.

More theories of course are welcome :) http://nadeausoftware.com/articles/2008/02/java_tip_how_read_files_quickly
is an interesting resource on this topic as well.

> 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
>            Reporter: George Porter
>         Attachments: HADOOP-4801.1.patch, HADOOP-4801.2.patch, HADOOP-4801.3.patch, 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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