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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 Tue, 13 Nov 2012 05:05:12 GMT

    [ https://issues.apache.org/jira/browse/HDFS-347?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13495963#comment-13495963
] 

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

This is no longer insecure - it uses file descriptor passing over a unix socket so that the
DN is the one arbitrating all access.

I implemented a couple of the optimizations mentioned above (avoiding CallIntMethod and adding
sendfile() support) and now the unix data path is a little bit faster than the TCP path:

{code}
over unix sockets:
todd@todd-w510:~/git/hadoop-common/hadoop-dist/target/hadoop-3.0.0-SNAPSHOT$ time ./bin/hadoop
fs -Ddfs.datanode.domain.socket.path=/tmp/dn-sock  -cat $(for x in $(seq 1 20) ; do echo /user/todd/1GB
; done) | wc -c

datanode utime: 2.02
datanode stime: 11.22
real    0m24.137s
user    0m12.530s
sys     0m16.270s

over TCP:
todd@todd-w510:~/git/hadoop-common/hadoop-dist/target/hadoop-3.0.0-SNAPSHOT$ time ./bin/hadoop
fs   -cat $(for x in $(seq 1 20) ; do echo /user/todd/1GB ; done) | wc -c
20971520000
datanode utime: 5.47
datanode stime: 6.52
real    0m26.473s
user    0m12.750s
sys     0m21.010s
{code}
The results above are a bit strange that the system time is better on the DN for TCP vs local
sockets. I'm guessing a little investigation there will make it a bit more clear - perhaps
a similar improvement to the writeBuffer code would yield a speedup.


Something seems to be wrong with the fd-passing (short-circuit) path in this patch, though.
When I enabled it, I could tell from jstacks that it was "working" but I got really slow performance:
{code}
real    1m5.366s
user    0m35.710s
sys     0m37.700s
{code}

I couldn't understand from the code why BlockReaderLocal is substantially rewritten. I'd think
it would be pretty much identical after the point where you get the files open. I'm guessing
the rewrite is what killed performance here.
                
> 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.

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