Hi Luke,

I changed the seek-read logic in HdfsBroker to use HDFS's build-in
pread API last week on a 11-node cluster. As expected the number of
socket connections per node drops drastically from hundreds to about
20. Meanwhile there is no significant change in performance.

I am reading the HDFS 0.19 code and doing some tests these days,
results show HDFS create/write/close fails with high probability when
some nodes are under heavy load, especially when the number of nodes
is small. I'll post my analysis in details later in a new thread.

Donald

On Mar 8, 4:25 pm, "Liu Kejia (Donald)" <[email protected]> wrote:
> Get it! I was so careless not to find the problem of HdfsBroker...
> I'll give it a try and post the result soon. Thanks very much.
>
> Donald
>
> On Sun, Mar 8, 2009 at 4:15 PM, Luke <[email protected]> wrote:
>
> > On Mar 8, 12:06 am, "Liu Kejia (Donald)" <[email protected]> wrote:
> > > read(byte[] buf, int off, int len) has much better performance for large
> > > scans (e.g. while doing a merging compaction), if using 128KB buffers, it
> > > can make 80MB/s throughput, while read(long pos, byte[] buf, int off, int
> > > len) can only achieve 40MB/s. To make best utilization of HDFS
> > performance,
> > > we should use positioned read for random read/small scans to achieve
> > shorter
> > > response time. OTOH use plain read for large scans to have better
> > > throughput, and close-reopen the file after the scanner is destroyed to
> > > avoid socket congestion and fd leak.
> > > I then read the current CellCacheScanner code roughly and found it
> > already
> > > has dealt with this issue! I guess Doug's already aware of this long
> > before?
> > > Now I am all confused that we still have hundreds of tcp connections in
> > > FIN_WAIT1 state on every DataNode, I really wonder what's the real cause.
>
> > Yes, Doug's already using the right Hypertable::Filesystem API. The
> > problem is the implementation of PositionRead in HdfsBroker. It is
> > actually using seek and plain read. Doug just made the change on
> > Friday to use positioned read, he didn't see any performance
> > difference in brief tests.
>
> > I wonder if you can do us a favor and test the change on the cluster.
>
> > __Luke
>
> > > Donald
>
> > > On Sat, Mar 7, 2009 at 4:01 AM, Luke <[email protected]> wrote:
>
> > > > Sorry, I didn't read your posts fully (was in a hurry). DfsBroker does
> > > > have pread interface, which is used by range server for random reads.
> > > > We just need to fix our HdfsBroker (PositionRead) to use HDFS
> > > > positioned read interface. Can you check if that improve things for
> > > > you?
>
> > > > On Mar 6, 11:37 am, Luke <[email protected]> wrote:
> > > > > It appears that HDFS does have pread like interface: readFully(pos,
> > > > > buf, len). Can you run the tests again using this API and see if
> > > > > things improve?
>
> > > > > On Mar 6, 11:18 am, Luke Lu <[email protected]> wrote:
>
> > > > > > Great analysis Donald! Thanks for the numbers. It seems to me the
> > > > > > right fix would be enhance the HDFS client library to add a pread
> > like
>
> > > > > > interface to do the right thing for random reads. Maybe you want to
> > > > > > file a Hadoop jira ticket for that?
>
> > > > > > __Luke
>
> > > > > > On Mar 6, 2009, at 3:15 AM, Liu Kejia (Donald) wrote:
>
> > > > > > > On Thu, Mar 5, 2009 at 11:50 PM, donald <[email protected]>
> > > > wrote:
>
> > > > > > > So I have done more digging on this subject...
>
> > > > > > > There is another problem if many files are kept open at the same
> > > > time:
> > > > > > > once you read some data from a HDFS file by calling
> > > > FSInputStream.read
> > > > > > > (byte[] buf, int off, int len), a tcp connection between
> > HdfsBroker
> > > > > > > and the DataNode that contains the file block is set up, this
> > > > > > > connection is kept until you read another block (by default 64MB
> > in
> > > > > > > size) of the file, or close the file entirely. There is a timeout
> > on
> > > > > > > the server side, but I see no clue on the client side. So you
> > quickly
> > > > > > > end up with a lot of idle connections between the HdfsBroker and
> > many
> > > > > > > DataNodes.
>
> > > > > > > What's even worse, no matter how many bytes the application wants
> > to
> > > > > > > read, the HDFS client library always requests the the chosen
> > DataNode
> > > > > > > to send all the remaining bytes of the block. Which means if you
> > read
> > > > > > > 1 byte from the beginning of a block, the DataNode actually gets
> > the
> > > > > > > request of sending the whole block, of which only the first few
> > bytes
> > > > > > > are read. Consequences are: if the client reads nothing for quite
> > a
> > > > > > > long while, 1) the kernel tcp send queue on the DataNode side and
> > the
> > > > > > > tcp receive queue on the client side are quickly fed up; 2) the
> > > > > > > DataNode Xceiver thread (there is a max count of 256 by default)
> > is
> > > > > > > blocked. Eventually the Xceiver timeouts, and closes the
> > connection.
> > > > > > > However this FIN packet cannot reach client side as send&receive
> > > > > > > queues are still blocked. Here is what I observe from one node of
> > our
> > > > > > > test cluster:
> > > > > > > $ netstat -ntp
> > > > > > > (Not all processes could be identified, non-owned process info
> > > > > > >  will not be shown, you would have to be root to see it all.)
> > > > > > > Active Internet connections (w/o servers)
> > > > > > > Proto Recv-Q Send-Q Local Address               Foreign
> > > > > > > Address             State       PID/Program name
> > > > > > > tcp        0 121937 10.65.25.150:50010
> > > > > > > 10.65.25.150:38595          FIN_WAIT1   -
> > > > > > > [...]
> > > > > > > tcp    74672      0 10.65.25.150:38595
> > > > > > > 10.65.25.150:50010          ESTABLISHED 32667/java
> > > > > > > [...]
> > > > > > > (and hundreds of other connections in the same states)
>
> > > > > > > Possible solutions without modifying hadoop client library are:
> > 1)
> > > > > > > open-read-close the file stream every time the cell store is
> > > > accessed;
> > > > > > > 2) always use postioned read: read(long position, byte[] buf, int
> > > > off,
> > > > > > > int len) instead, because pread doesn't keep the tcp connection
> > with
> > > > > > > DataNodes. Solution 1 is not scalable because every open()
> > operation
> > > > > > > includes interaction with HDFS NameNode, which immediately
> > becomes a
> > > > > > > bottleneck: in our test cluster the NameNode can only handle
> > hundreds
> > > > > > > of parallel open() request per second, with an average delay of
> > > > 2-3ms.
> > > > > > > I haven't tested the performance of solution 2 yet, I will put up
> > > > some
> > > > > > > numbers tomorrow.
>
> > > > > > > Donald
>
> > > > > > > I've created 1000 files in a 11-node hadoop cluster, each file is
> > > > > > > 20MB. Then I wrote simple java programs to do the following
> > tests:
>
> > > > > > > Opening all 1000 files, one process: about 2.5 s (2.5ms latency)
> > > > > > > Closing all 1000files, one process: 50ms
> > > > > > > Opening all 1000 files, 10 processes (running distributedly on
> > the
> > > > > > > 10 datanodes): 15 s (15ms latency, or 700 opens/s)
> > > > > > > Reading the first 1KB data from each file (plain read), one
> > process:
>
> > > > > > > 6s (6ms latency)
> > > > > > > Reading the first 1KB data from each file (positioned read), one
> > > > > > > process: 2.5s (2.5ms latency)
> > > > > > > Reading the first 100KB data from each file, 1KB at a time
> > > > > > > (positioned read), one process: 130s (1.3ms latency, or 0.77MB/s)
> > > > > > > Reading the first 100KB data from each file, 1KB at a time (plain
> > > > > > > read), one process: 8.8s (11MB/s)
>
> > > > > > > The tests are done multiple times to make sure all blocks are
> > > > > > > effectively cached in Linux page cache.The hadoop version was
> > 0.19.0
>
> > > > > > > with a few patches. io.file.buffer.size = 4096
>
> > > > > > > Donald
>
> > > > > > > On Feb 25, 8:59 pm, "Liu Kejia (Donald)" <[email protected]>
> > > > wrote:
> > > > > > > > It turns out the hadoop-default.xml packaged in my custom
> > > > > > > > hadoop-0.19.0-core.jar has set the "io.file.buffer.size" to
> > 131072
>
> > > > > > > (128KB),
> > > > > > > > which means DfsBroker has to open a 128KB buffer for every open
> > > > > > > file. The
> > > > > > > > official hadoop-0.19.0-core.jar sets this value to 4096, which
> > is
> > > > > > > more
> > > > > > > > reasonable for applications like Hypertable.
> > > > > > > > Donald
>
> > > > > > > > On Fri, Feb 20, 2009 at 11:55 AM, Liu Kejia (Donald)
> > > > > > > > <[email protected]>wrote:
>
> > > > > > > > > Caching might not work very well because keys are randomly
> > > > > > > generated,
> > > > > > > > > resulting in bad locality...
> > > > > > > > > Even it's Java, hundreds of kilobytes per file object is
> > still
> > > > > > > very big.
> > > > > > > > > I'll profile HdfsBroker to see what exactly is using so much
> > > > > > > memory, and
> > > > > > > > > post the results later.
>
> > > > > > > > > Donald
>
> > > > > > > > > On Fri, Feb 20, 2009 at 11:20 AM, Doug Judd
> > > > > > > <[email protected]> wrote:
>
> > > > > > > > >> Hi Donald,
>
> > > > > > > > >> Interesting.  One possibility would be to have an open
> > > > > > > CellStore cache.
> > > > > > > > >> Frequently accessed CellStores would remain open, while
> > seldom
> > > > > > > used ones get
> > > > > > > > >> closed.  The effectiveness of this solution would depend on
> > the
>
> > > > > > > workload.
> > > > > > > > >> Do you think this might work for your use case?
>
> > > > > > > > >> - Doug
>
> > > > > > > > >> On Thu, Feb 19, 2009 at 7:09 PM, donald <
> > [email protected]>
>
> > > > > > > wrote:
>
> > > > > > > > >>> Hi all,
>
> > > > > > > > >>> I recently run into the problem that HdfsBroker throws out
> > of
> > > > > > > memory
> > > > > > > > >>> exception, because too many CellStore files in HDFS are
> > kept
> > > > > > > open - I
> > > > > > > > >>> have over 600 ranges per range server, with a maximum of 10
> > > > cell
> > > > > > > > >>> stores per range, that'll be 6,000 open files at the same
> > > > > > > time, making
> > > > > > > > >>> HdfsBroker to take gigabytes of memory.
>
> > > > > > > > >>> If we open the CellStore file on demand, i.e. when a
> > scanner is
> > > > > > > > >>> created on it, this problem is gone. However random-read
> > > > > > > performance
> > > > > > > > >>> may drop due to the the overhead of opening a file in HDFS.
> > > > > > > Any better
>
> ...
>
> read more »
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