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From Khaled Elmeleegy <kd...@hotmail.com>
Subject RE: HBase read performance
Date Sun, 05 Oct 2014 06:24:52 GMT
I tried creating my own HConnections pool to use for my HBase calls, so that not all the (2K)
threads share the same HConnection. However, I could only have 10 HConnections. Beyond that
I get ZK exceptions, please find it below. Also, with 10 HConnections, I don't see noticeable
improvement in performance so far.
2014-10-05 06:11:26,490 WARN  [main] zookeeper.RecoverableZooKeeper (RecoverableZooKeeper.java:retryOrThrow(253))
- Possibly transient ZooKeeper, quorum=54.68.206.252:2181, exception=org.apache.zookeeper.KeeperException$ConnectionLossException:
KeeperErrorCode = ConnectionLoss for /hbase/hbaseid2014-10-05 06:11:26,490 INFO  [main] util.RetryCounter
(RetryCounter.java:sleepUntilNextRetry(155)) - Sleeping 1000ms before retry #0...2014-10-05
06:11:27,845 WARN  [main] zookeeper.RecoverableZooKeeper (RecoverableZooKeeper.java:retryOrThrow(253))
- Possibly transient ZooKeeper, quorum=54.68.206.252:2181, exception=org.apache.zookeeper.KeeperException$ConnectionLossException:
KeeperErrorCode = ConnectionLoss for /hbase/hbaseid2014-10-05 06:11:27,849 INFO  [main] util.RetryCounter
(RetryCounter.java:sleepUntilNextRetry(155)) - Sleeping 2000ms before retry #1...2014-10-05
06:11:30,405 WARN  [main] zookeeper.RecoverableZooKeeper (RecoverableZooKeeper.java:retryOrThrow(253))
- Possibly transient ZooKeeper, quorum=54.68.206.252:2181, exception=org.apache.zookeeper.KeeperException$ConnectionLossException:
KeeperErrorCode = ConnectionLoss for /hbase/hbaseid2014-10-05 06:11:30,405 INFO  [main] util.RetryCounter
(RetryCounter.java:sleepUntilNextRetry(155)) - Sleeping 4000ms before retry #2...2014-10-05
06:11:35,278 WARN  [main] zookeeper.RecoverableZooKeeper (RecoverableZooKeeper.java:retryOrThrow(253))
- Possibly transient ZooKeeper, quorum=54.68.206.252:2181, exception=org.apache.zookeeper.KeeperException$ConnectionLossException:
KeeperErrorCode = ConnectionLoss for /hbase/hbaseid2014-10-05 06:11:35,279 INFO  [main] util.RetryCounter
(RetryCounter.java:sleepUntilNextRetry(155)) - Sleeping 8000ms before retry #3...2014-10-05
06:11:44,393 WARN  [main] zookeeper.RecoverableZooKeeper (RecoverableZooKeeper.java:retryOrThrow(253))
- Possibly transient ZooKeeper, quorum=54.68.206.252:2181, exception=org.apache.zookeeper.KeeperException$ConnectionLossException:
KeeperErrorCode = ConnectionLoss for /hbase/hbaseid2014-10-05 06:11:44,393 ERROR [main] zookeeper.RecoverableZooKeeper
(RecoverableZooKeeper.java:retryOrThrow(255)) - ZooKeeper exists failed after 4 attempts2014-10-05
06:11:44,394 WARN  [main] zookeeper.ZKUtil (ZKUtil.java:checkExists(482)) - hconnection-0x4e174f3b,
quorum=54.68.206.252:2181, baseZNode=/hbase Unable to set watcher on znode (/hbase/hbaseid)org.apache.zookeeper.KeeperException$ConnectionLossException:
KeeperErrorCode = ConnectionLoss for /hbase/hbaseid	at org.apache.zookeeper.KeeperException.create(KeeperException.java:99)
at org.apache.zookeeper.KeeperException.create(KeeperException.java:51)	at org.apache.zookeeper.ZooKeeper.exists(ZooKeeper.java:1041)
at org.apache.hadoop.hbase.zookeeper.RecoverableZooKeeper.exists(RecoverableZooKeeper.java:199)
at org.apache.hadoop.hbase.zookeeper.ZKUtil.checkExists(ZKUtil.java:479)	at org.apache.hadoop.hbase.zookeeper.ZKClusterId.readClusterIdZNode(ZKClusterId.java:65)
at org.apache.hadoop.hbase.client.ZooKeeperRegistry.getClusterId(ZooKeeperRegistry.java:83)
at org.apache.hadoop.hbase.client.HConnectionManager$HConnectionImplementation.retrieveClusterId(HConnectionManager.java:857)
at org.apache.hadoop.hbase.client.HConnectionManager$HConnectionImplementation.<init>(HConnectionManager.java:662)
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)	at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:57)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:526)	at org.apache.hadoop.hbase.client.HConnectionManager.createConnection(HConnectionManager.java:414)
at org.apache.hadoop.hbase.client.HConnectionManager.createConnection(HConnectionManager.java:335)...
> From: kdiaa@hotmail.com
> To: user@hbase.apache.org
> Subject: RE: HBase read performance
> Date: Fri, 3 Oct 2014 12:37:39 -0700
> 
> Lars, Ted, and Qiang,
> Thanks for all the input. 
> Qiang: yes all the threads are in the same client process sharing the same connection.
And since I don't see hardware contention, may be there is contention over this code path.
I'll try using many connections and see if it alleviates the problems and I'll report back.
> Thanks again,Khaled
> 
> > Date: Fri, 3 Oct 2014 15:18:30 +0800
> > Subject: Re: HBase read performance
> > From: tianq01@gmail.com
> > To: user@hbase.apache.org
> > 
> > Regarding to profiling, Andrew introduced
> > http://www.brendangregg.com/blog/2014-06-12/java-flame-graphs.html months
> > ago.
> > 
> > processCallTime comes from RpcServer#call, so it looks good?
> > 
> > I have a suspect: https://issues.apache.org/jira/browse/HBASE-11306
> > 
> > how many processes do you have for your 2000 threads?
> > if olny 1 process, those threads will share just 1 connection to that
> > regionserver, there might be big contention on the RPC code path. ---for
> > such case, could you try using different connections?
> > https://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HConnectionManager.html
> > 
> > 
> > 
> > 
> > On Fri, Oct 3, 2014 at 9:55 AM, Ted Yu <yuzhihong@gmail.com> wrote:
> > 
> > > Khaled:
> > > Do you have profiler such as jprofiler ?
> > > Profiling would give us more hint.
> > >
> > > Otherwise capturing stack trace during the period of reverse scan would
> > > help.
> > >
> > > Cheers
> > >
> > > On Thu, Oct 2, 2014 at 4:52 PM, lars hofhansl <larsh@apache.org> wrote:
> > >
> > > > You might have the data in the OS buffer cache, without short circuit
> > > > reading the region server has to request the block from the data node
> > > > process, which then reads it from the block cache.
> > > > That is a few context switches per RPC that do not show up in CPU
> > > metrics.
> > > > In that you also would not see disk IO.
> > > >
> > > >
> > > > If - as you say - you see a lot of evicted blocks the data *has* to come
> > > > from the OS. If you do not see disk IO is *has* to come from the OS
> > > cache.
> > > > I.e. there's more RAM on your boxes, and you should increase the heap
> > > block
> > > > cache.
> > > >
> > > >
> > > > You can measure the context switches with vmstat. Other than that I have
> > > > no suggestion until I reproduce the problem.
> > > > Also check the data locality index of the region server it should be
> > > close
> > > > to 100%.
> > > >
> > > >
> > > > -- Lars
> > > >
> > > >
> > > >
> > > > ________________________________
> > > >  From: Khaled Elmeleegy <kdiaa@hotmail.com>
> > > > To: "user@hbase.apache.org" <user@hbase.apache.org>
> > > > Sent: Thursday, October 2, 2014 3:24 PM
> > > > Subject: RE: HBase read performance
> > > >
> > > >
> > > > Lars thanks a lot about all the tips. I'll make sure I cover all of them
> > > > and get back to you. I am not sure they are the bottleneck though as they
> > > > all are about optimizing physical resource usage. As I said, I don't see
> > > > any contended physical resources now. I'll also try to reproduce this
> > > > problem in a simpler environment and pass to you the test program to play
> > > > with.
> > > >
> > > >
> > > > Couple of high level points to make. You are right that my use case is
> > > > kind of a worst case for HBase reads. But, if things go the way you
> > > > described them, there should be tons of disk IO and that should be
> > > clearly
> > > > the bottleneck. This is not the case though. That's for the simple reason
> > > > that this is done in a test environment (I am still prototyping), and
> > > not a
> > > > lot of data is yet written to HBase. However for the real use case, there
> > > > should writers constantly writing data to HBase and readers occasionally
> > > > doing this scatter/gather. At steady state, things should only get worse
> > > > and all the issues you mentioned should get far more pronounced. At this
> > > > point, one can try to mitigate it using more memory or so. I am not there
> > > > yet as I think I am hitting some software bottleneck, which I don't know
> > > > how to work around.
> > > >
> > > > Khaled
> > > >
> > > >
> > > >
> > > >
> > > >
> > > >
> > > > ----------------------------------------
> > > > > Date: Thu, 2 Oct 2014 14:20:47 -0700
> > > > > From: larsh@apache.org
> > > > > Subject: Re: HBase read performance
> > > > > To: user@hbase.apache.org
> > > > >
> > > > > OK... We might need to investigate this.
> > > > > Any chance that you can provide a minimal test program and instruction
> > > > about how to set it up.
> > > > > We can do some profiling then.
> > > > >
> > > > > One thing to note is that with scanning HBase cannot use bloom filters
> > > > to rule out HFiles ahead of time, it needs to look into all of them.
> > > > > So you kind of hit on the absolute worst case:
> > > > > - random reads that do not fit into the block cache
> > > > > - cannot use bloom filters
> > > > >
> > > > >
> > > > > Few more question/comments:
> > > > > - Do you have short circuit reading enabled? If not, you should.
> > > > > - Is your table major compacted? That will reduce the number of files
> > > to
> > > > look at.
> > > > > - Did you disable Nagle's everywhere (enabled tcpnodelay)? It disabled
> > > > by default in HBase, but necessarily in your install of HDFS.
> > > > > - Which version of HDFS are you using as backing filesystem?
> > > > > - If your disk is idle, it means the data fits into the OS buffer
> > > cache.
> > > > In turn that means that you increase the heap for the region servers.
You
> > > > can also use block encoding (FAST_DIFF) to try to make sure the entire
> > > > working set fits into the cache.
> > > > >
> > > > > - Also try to reduce the block size - although if your overall working
> > > > set does not fit in the heap it won't help much.
> > > > >
> > > > >
> > > > > This is a good section of the book to read through generally (even
> > > > though you might know most of this already):
> > > > http://hbase.apache.org/book.html#perf.configurations
> > > > >
> > > > >
> > > > > -- Lars
> > > > >
> > > > >
> > > > >
> > > > > ----- Original Message -----
> > > > > From: Khaled Elmeleegy <kdiaa@hotmail.com>
> > > > > To: "user@hbase.apache.org" <user@hbase.apache.org>
> > > > > Cc:
> > > > > Sent: Thursday, October 2, 2014 11:27 AM
> > > > > Subject: RE: HBase read performance
> > > > >
> > > > > I do see a very brief spike in CPU (user/system), but it's no where
> > > near
> > > > 0% idle. It goes from 99% idle down to something like 40% idle for a
> > > second
> > > > or so. The thing to note, this is all on a test cluster, so no real load.
> > > > Things are generally idle until i issue 2-3 of these multi-scan-requests
> > > to
> > > > render a web page. Then, you see the spike in the cpu and some activity
> > > in
> > > > the network and disk, but nowhere near saturation.
> > > > >
> > > > >
> > > > > If there are specific tests you'd like me to do to debug this, I'd
be
> > > > more than happy to do it.
> > > > >
> > > > >
> > > > > Khaled
> > > > >
> > > > >
> > > > >
> > > > >
> > > > > ----------------------------------------
> > > > >> Date: Thu, 2 Oct 2014 11:15:59 -0700
> > > > >> From: larsh@apache.org
> > > > >> Subject: Re: HBase read performance
> > > > >> To: user@hbase.apache.org
> > > > >>
> > > > >> I still think you're waiting on disk. No IOWAIT? So CPU is not
waiting
> > > > a lot for IO. No high User/System CPU either?
> > > > >>
> > > > >> If you see a lot of evicted block then each RPC has a high chance
of
> > > > requiring to bring an entire 64k block in. You'll see bad performance
> > > with
> > > > this.
> > > > >>
> > > > >> We might need to trace this specific scenario.
> > > > >>
> > > > >> -- Lars
> > > > >>
> > > > >>
> > > > >>
> > > > >> ________________________________
> > > > >> From: Khaled Elmeleegy <kdiaa@hotmail.com>
> > > > >> To: "user@hbase.apache.org" <user@hbase.apache.org>
> > > > >> Sent: Thursday, October 2, 2014 10:46 AM
> > > > >> Subject: RE: HBase read performance
> > > > >>
> > > > >>
> > > > >> I've set the heap size to 6GB and I do have gc logging. No long
pauses
> > > > there -- occasional 0.1s or 0.2s.
> > > > >>
> > > > >> Other than the discrepancy between what's reported on the client
and
> > > > what's reported at the RS, there is also the issue of not getting proper
> > > > concurrency. So, even if a reverse get takes 100ms or so (this has to
be
> > > > mostly blocking on various things as no physical resource is contended),
> > > > then the other gets/scans should be able to proceed in parallel, so a
> > > > thousand concurrent gets/scans should finish in few hundreds of ms not
> > > many
> > > > seconds. That's why I thought I'd increase the handlers count to try to
> > > get
> > > > more concurrency, but it didn't help. So, there must be something else.
> > > > >>
> > > > >> Khaled
> > > > >>
> > > > >> ----------------------------------------
> > > > >>> From: ndimiduk@gmail.com
> > > > >>> Date: Thu, 2 Oct 2014 10:36:39 -0700
> > > > >>> Subject: Re: HBase read performance
> > > > >>> To: user@hbase.apache.org
> > > > >>>
> > > > >>> Do check again on the heap size of the region servers. The
default
> > > > >>> unconfigured size is 1G; too small for much of anything.
Check your
> > > RS
> > > > logs
> > > > >>> -- look for lines produced by the JVMPauseMonitor thread.
They
> > > usually
> > > > >>> correlate with long GC pauses or other process-freeze events.
> > > > >>>
> > > > >>> Get is implemented as a Scan of a single row, so a reverse
scan of a
> > > > single
> > > > >>> row should be functionally equivalent.
> > > > >>>
> > > > >>> In practice, I have seen discrepancy between the latencies
reported
> > > by
> > > > the
> > > > >>> RS and the latencies experienced by the client. I've not
investigated
> > > > this
> > > > >>> area thoroughly.
> > > > >>>
> > > > >>> On Thu, Oct 2, 2014 at 10:05 AM, Khaled Elmeleegy <kdiaa@hotmail.com
> > > >
> > > > wrote:
> > > > >>>
> > > > >>>> Thanks Lars for your quick reply.
> > > > >>>>
> > > > >>>> Yes performance is similar with less handlers (I tried
with 100
> > > > first).
> > > > >>>>
> > > > >>>> The payload is not big ~1KB or so. The working set doesn't
seem to
> > > > fit in
> > > > >>>> memory as there are many cache misses. However, disk
is far from
> > > > being a
> > > > >>>> bottleneck. I checked using iostat. I also verified that
neither the
> > > > >>>> network nor the CPU of the region server or the client
are a
> > > > bottleneck.
> > > > >>>> This leads me to believe that likely this is a software
bottleneck,
> > > > >>>> possibly due to a misconfiguration on my side. I just
don't know how
> > > > to
> > > > >>>> debug it. A clear disconnect I see is the individual
request latency
> > > > as
> > > > >>>> reported by metrics on the region server (IPC processCallTime
vs
> > > > scanNext)
> > > > >>>> vs what's measured on the client. Does this sound right?
Any ideas
> > > on
> > > > how
> > > > >>>> to better debug it?
> > > > >>>>
> > > > >>>> About this trick with the timestamps to be able to do
a forward
> > > scan,
> > > > >>>> thanks for pointing it out. Actually, I am aware of it.
The problem
> > > I
> > > > have
> > > > >>>> is, sometimes I want to get the key after a particular
timestamp and
> > > > >>>> sometimes I want to get the key before, so just relying
on the key
> > > > order
> > > > >>>> doesn't work. Ideally, I want a reverse get(). I thought
reverse
> > > scan
> > > > can
> > > > >>>> do the trick though.
> > > > >>>>
> > > > >>>> Khaled
> > > > >>>>
> > > > >>>> ----------------------------------------
> > > > >>>>> Date: Thu, 2 Oct 2014 09:40:37 -0700
> > > > >>>>> From: larsh@apache.org
> > > > >>>>> Subject: Re: HBase read performance
> > > > >>>>> To: user@hbase.apache.org
> > > > >>>>>
> > > > >>>>> Hi Khaled,
> > > > >>>>> is it the same with fewer threads? 1500 handler threads
seems to
> > > be a
> > > > >>>> lot. Typically a good number of threads depends on the
hardware
> > > > (number of
> > > > >>>> cores, number of spindles, etc). I cannot think of any
type of
> > > > scenario
> > > > >>>> where more than 100 would give any improvement.
> > > > >>>>>
> > > > >>>>> How large is the payload per KV retrieved that way?
If large (as
> > > in a
> > > > >>>> few 100k) you definitely want to lower the number of
the handler
> > > > threads.
> > > > >>>>> How much heap do you give the region server? Does
the working set
> > > fit
> > > > >>>> into the cache? (i.e. in the metrics, do you see the
eviction count
> > > > going
> > > > >>>> up, if so it does not fit into the cache).
> > > > >>>>>
> > > > >>>>> If the working set does not fit into the cache (eviction
count goes
> > > > up)
> > > > >>>> then HBase will need to bring a new block in from disk
on each Get
> > > > >>>> (assuming the Gets are more or less random as far as
the server is
> > > > >>>> concerned).
> > > > >>>>> In case you'll benefit from reducing the HFile block
size (from 64k
> > > > to
> > > > >>>> 8k or even 4k).
> > > > >>>>>
> > > > >>>>> Lastly I don't think we tested the performance of
using reverse
> > > scan
> > > > >>>> this way, there is probably room to optimize this.
> > > > >>>>> Can you restructure your keys to allow forwards scanning?
For
> > > example
> > > > >>>> you could store the time as MAX_LONG-time. Or you could
invert all
> > > > the bits
> > > > >>>> of the time portion of the key, so that it sort the other
way. Then
> > > > you
> > > > >>>> could do a forward scan.
> > > > >>>>>
> > > > >>>>> Let us know how it goes.
> > > > >>>>>
> > > > >>>>> -- Lars
> > > > >>>>>
> > > > >>>>>
> > > > >>>>> ----- Original Message -----
> > > > >>>>> From: Khaled Elmeleegy <kdiaa@hotmail.com>
> > > > >>>>> To: "user@hbase.apache.org" <user@hbase.apache.org>
> > > > >>>>> Cc:
> > > > >>>>> Sent: Thursday, October 2, 2014 12:12 AM
> > > > >>>>> Subject: HBase read performance
> > > > >>>>>
> > > > >>>>> Hi,
> > > > >>>>>
> > > > >>>>> I am trying to do a scatter/gather on hbase (0.98.6.1),
where I
> > > have
> > > > a
> > > > >>>> client reading ~1000 keys from an HBase table. These
keys happen to
> > > > fall on
> > > > >>>> the same region server. For my reads I use reverse scan
to read each
> > > > key as
> > > > >>>> I want the key prior to a specific time stamp (time stamps
are
> > > stored
> > > > in
> > > > >>>> reverse order). I don't believe gets can accomplish that,
right? so
> > > I
> > > > use
> > > > >>>> scan, with caching set to 1.
> > > > >>>>>
> > > > >>>>> I use 2000 reader threads in the client and on HBase,
I've set
> > > > >>>> hbase.regionserver.handler.count to 1500. With this setup,
my
> > > scatter
> > > > >>>> gather is very slow and can take up to 10s in total.
Timing an
> > > > individual
> > > > >>>> getScanner(..) call on the client side, it can easily
take few
> > > > hundreds of
> > > > >>>> ms. I also got the following metrics from the region
server in
> > > > question:
> > > > >>>>>
> > > > >>>>> "queueCallTime_mean" : 2.190855525775637,
> > > > >>>>> "queueCallTime_median" : 0.0,
> > > > >>>>> "queueCallTime_75th_percentile" : 0.0,
> > > > >>>>> "queueCallTime_95th_percentile" : 1.0,
> > > > >>>>> "queueCallTime_99th_percentile" : 556.9799999999818,
> > > > >>>>>
> > > > >>>>> "processCallTime_min" : 0,
> > > > >>>>> "processCallTime_max" : 12755,
> > > > >>>>> "processCallTime_mean" : 105.64873440912682,
> > > > >>>>> "processCallTime_median" : 0.0,
> > > > >>>>> "processCallTime_75th_percentile" : 2.0,
> > > > >>>>> "processCallTime_95th_percentile" : 7917.95,
> > > > >>>>> "processCallTime_99th_percentile" : 8876.89,
> > > > >>>>>
> > > > >>>>>
> > > > >>>>
> > > >
> > > "namespace_default_table_delta_region_87be70d7710f95c05cfcc90181d183b4_metric_scanNext_min"
> > > > >>>> : 89,
> > > > >>>>>
> > > > >>>>
> > > >
> > > "namespace_default_table_delta_region_87be70d7710f95c05cfcc90181d183b4_metric_scanNext_max"
> > > > >>>> : 11300,
> > > > >>>>>
> > > > >>>>
> > > >
> > > "namespace_default_table_delta_region_87be70d7710f95c05cfcc90181d183b4_metric_scanNext_mean"
> > > > >>>> : 654.4949739797315,
> > > > >>>>>
> > > > >>>>
> > > >
> > > "namespace_default_table_delta_region_87be70d7710f95c05cfcc90181d183b4_metric_scanNext_median"
> > > > >>>> : 101.0,
> > > > >>>>>
> > > > >>>>
> > > >
> > > "namespace_default_table_delta_region_87be70d7710f95c05cfcc90181d183b4_metric_scanNext_75th_percentile"
> > > > >>>> : 101.0,
> > > > >>>>>
> > > > >>>>
> > > >
> > > "namespace_default_table_delta_region_87be70d7710f95c05cfcc90181d183b4_metric_scanNext_95th_percentile"
> > > > >>>> : 101.0,
> > > > >>>>>
> > > > >>>>
> > > >
> > > "namespace_default_table_delta_region_87be70d7710f95c05cfcc90181d183b4_metric_scanNext_99th_percentile"
> > > > >>>> : 113.0,
> > > > >>>>>
> > > > >>>>> Where "delta" is the name of the table I am querying.
> > > > >>>>>
> > > > >>>>> In addition to all this, i monitored the hardware
resources (CPU,
> > > > disk,
> > > > >>>> and network) of both the client and the region server
and nothing
> > > > seems
> > > > >>>> anywhere near saturation. So I am puzzled by what's going
on and
> > > > where this
> > > > >>>> time is going.
> > > > >>>>>
> > > > >>>>> Few things to note based on the above measurements:
both medians of
> > > > IPC
> > > > >>>> processCallTime and queueCallTime are basically zero
(ms I presume,
> > > > >>>> right?). However, scanNext_median is 101 (ms too, right?).
I am not
> > > > sure
> > > > >>>> how this adds up. Also, even though the 101 figure seems
> > > outrageously
> > > > high
> > > > >>>> and I don't know why, still all these scans should be
happening in
> > > > >>>> parallel, so the overall call should finish fast, given
that no
> > > > hardware
> > > > >>>> resource is contended, right? but this is not what's
happening, so I
> > > > have
> > > > >>>> to be missing something(s).
> > > > >>>>>
> > > > >>>>> So, any help is appreciated there.
> > > > >>>>>
> > > > >>>>> Thanks,
> > > > >>>>> Khaled
> > > > >>>>
> > > > >>>>
> > > >
> > >
>  		 	   		  
 		 	   		  
Mime
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