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From Jeremy Kepner <kep...@ll.mit.edu>
Subject Re: maximize usage of cluster resources during ingestion
Date Thu, 13 Jul 2017 14:04:39 GMT
https://arxiv.org/abs/1406.4923  contains a number of tricks for maximizing ingest performance.

On Thu, Jul 13, 2017 at 08:13:40AM -0400, Jonathan Wonders wrote:
> Keep in mind that Accumulo puts a much different kind of load on HDFS than
> the DFSIO benchmark.  It might be more appropriate to use a tool like dstat
> to monitor HDD utilization and queue depth.  HDD throughput benchmarks
> usually will involve high queue depths as disks are much more effective
> when they can pipeline and batch updates. Accumulo's WAL workload will
> typically call hflush or hsync periodically which interrupts the IO
> pipeline much like memory barriers can interrupt CPU pipelining except more
> severe.  This is necessary to provide durability guarantees, but definitely
> comes at a cost to throughput.  Any database that has these durability
> guarantees will suffer similarly to an extent.  For Accumulo, it is
> probably worse than for non-distributed databases because the flush or sync
> must happen at each replica prior to the mutation being added into the
> in-memory map.
> 
> I think one of the reasons the recommendation was made to add more tablet
> servers is because each tablet server only writes to one WAL at a time and
> each block will live on N disk based on replication factor.  If you have a
> replication factor of 3, there will be 10x3 blocks being appended to at any
> given time (excluding compactions).  Since you have 120 disks, not all will
> be participating in write-ahead-logging, so you should not count the IO
> capacity of these extra disks towards expected ingest throughput.  10
> tablet servers per node is probably too many because there would likely be
> a lot of contention flushing/syncing WALs.  I'm not sure how smart HDFS is
> about how it distributes the WAL load.  You might see more benefit with 2-4
> tservers per node.  This would mostly likely require more batch writer
> threads in the client as well.
> 
> I'm not too surprised that snappy did not help because the WALs are not
> compressed and are likely a bigger bottleneck than compaction since you
> have many disks not participating in WAL.
> 
> 
> On Wed, Jul 12, 2017 at 11:16 AM, Josh Elser <elserj@apache.org> wrote:
> 
> > You probably want to split the table further than just 4 tablets per
> > tablet server. Try 10's of tablets per server.
> >
> > Also, merging the content from (who I assume is) your coworker on this
> > stackoverflow post[1], I don't believe the suggestion[2] to verify WAL max
> > size, minc threshold, and native maps size was brought up yet.
> >
> > Also, did you look at the JVM GC logs for the TabletServers like was
> > previously suggested to you?
> >
> > [1] https://stackoverflow.com/questions/44928354/accumulo-tablet
> > -server-doesnt-utilize-all-available-resources-on-host-machine/
> > [2] https://accumulo.apache.org/1.8/accumulo_user_manual.html#_n
> > ative_maps_configuration
> >
> > On 7/12/17 10:12 AM, Massimilian Mattetti wrote:
> >
> >> Hi all,
> >>
> >> I ran a few experiments in the last days trying to identify what is the
> >> bottleneck for the ingestion process.
> >> - Running 10 tservers per node instead of only one gave me a very
> >> neglectable performance improvement of about 15%.
> >> - Running the ingestor processes from the two masters give the same
> >> performance as running one ingestor process in each tablet server (10
> >> ingestors)
> >> - neither the network limit (10 Gb network) nor the disk throughput limit
> >> has been reached (1GB/s per node reached while running the TestDFSIO
> >> benchmark on HDFS)
> >> - CPU is always around 20% on each tserver
> >> - changing compression from GZ to snappy did not provide any benefit
> >> - increasing the tserver.total.mutation.queue.maxto 200MB actually
> >> decreased the performance
> >> I am going to run some ingestion experiment with Kudu over the next few
> >> days, but any other suggestion on how improve the performance on Accumulo
> >> is very welcome.
> >> Thanks.
> >>
> >> Best Regards,
> >> Massimiliano
> >>
> >>
> >>
> >> From: Jonathan Wonders <jwonders88@gmail.com>
> >> To: user@accumulo.apache.org, Dave Marion <dlmarion@comcast.net>
> >> Date: 07/07/2017 04:02
> >> Subject: Re: maximize usage of cluster resources during ingestion
> >> ------------------------------------------------------------------------
> >>
> >>
> >>
> >> I've personally never seen full CPU utilization during pure ingest.
> >> Typically the bottleneck has been I/O related. The majority of steady-state
> >> CPU utilization under a heavy ingest load is probably due to compression
> >> unless you have custom constraints running. This can depend on the
> >> compression algorithm you have selected.  There is probably a measurable
> >> contribution from inserting into the in-memory map.  Otherwise, not much
> >> computation occurs during ingest per mutation.
> >>
> >> On Thu, Jul 6, 2017 at 8:18 AM, Dave Marion <_dlmarion@comcast.net_
> >> <mailto:dlmarion@comcast.net>> wrote:
> >> That's a good point. I would also look at increasing
> >> tserver.total.mutation.queue.max. Are you seeing hold times? If not, I
> >> would keep pushing harder until you do, then move to multiple tablet
> >> servers. Do you have any GC logs?
> >>
> >>
> >> On July 6, 2017 at 4:47 AM Cyrille Savelief <_csavelief@gmail.com_
> >> <mailto:csavelief@gmail.com>> wrote:
> >>
> >> Are you sure Accumulo is not waiting for your app's data? There might be
> >> GC pauses in your ingest code (we have already experienced that).
> >>
> >> Le jeu. 6 juil. 2017 à 10:32, Massimilian Mattetti <_MASSIMIL@il.ibm.com_
> >> <mailto:MASSIMIL@il.ibm.com>> a écrit :
> >> Thank you all for the suggestions.
> >>
> >> About the native memory map I checked the logs on each tablet server and
> >> it was loaded correctly (of course the tserver.memory.maps.native.enabled
> >> was set to true), so the GC pauses should not be the problem eventually. I
> >> managed to get much better ingestion graph by reducing the native map size
> >> to *2GB* and increasing the Batch Writer threads number from the default (3
> >> was really bad for my configuration) to *10* (I think it does not make
> >> sense having more threads than tablet servers, am I right?).
> >>
> >> The configuration that I used for the table is:
> >> "table.file.replication": "2",
> >> "table.compaction.minor.logs.threshold": "3",
> >> "table.durability": "flush",
> >> "table.split.threshold": "1G"
> >>
> >> while for the tablet servers is:
> >> "tserver.wal.blocksize": "1G",
> >>   "tserver.walog.max.size": "2G",
> >> "tserver.memory.maps.max": "2G",
> >> "tserver.compaction.minor.concurrent.max": "50",
> >> "tserver.compaction.major.concurrent.max": "20",
> >> "tserver.wal.replication": "2",
> >>   "tserver.compaction.major.thread.files.open.max": "15"
> >>
> >> The new graph:
> >>
> >>
> >> I still have the problem of a CPU usage that is less than*20%.* So I am
> >> thinking to run multiple tablet servers per node (like 5 or 10) in order to
> >> maximize the CPU usage. Besides that I do not have any other idea on how to
> >> stress those servers with ingestion.
> >> Any suggestions are very welcome. Meanwhile, thank you all again for your
> >> help.
> >>
> >>
> >> Best Regards,
> >> Massimiliano
> >>
> >>
> >>
> >> From: Jonathan Wonders <_jwonders88@gmail.com_ <mailto:
> >> jwonders88@gmail.com>>
> >> To: _user@accumulo.apache.org_ <mailto:user@accumulo.apache.org>
> >> Date: 06/07/2017 04:01
> >> Subject: Re: maximize usage of cluster resources during ingestion
> >> ------------------------------------------------------------------------
> >>
> >>
> >>
> >> Hi Massimilian,
> >>
> >> Are you seeing held commits during the ingest pauses?  Just based on
> >> having looked at many similar graphs in the past, this might be one of the
> >> major culprits.  A tablet server has a memory region with a bounded size
> >> (tserver.memory.maps.max) where it buffers data that has not yet been
> >> written to RFiles (through the process of minor compaction). The region is
> >> segmented by tablet and each tablet can have a buffer that is undergoing
> >> ingest as well as a buffer that is undergoing minor compaction. A memory
> >> manager decides when to initiate minor compactions for the tablet buffers
> >> and the default implementation tries to keep the memory region 80-90% full
> >> while preferring to compact the largest tablet buffers. Creating larger
> >> RFiles during minor compaction should lead to less major compactions.
> >> During a minor compaction, the tablet buffer still "consumes" memory within
> >> the in memory map and high ingest rates can lead to exhausing the remaining
> >> capacity.  The default memory manage uses an adaptive strategy to predict
> >> the expected memory usage and makes compaction decisions that should
> >> maintain some free memory.  Batch writers can be bursty and a bit
> >> unpredictable which could throw off these estimates.  Also, depending on
> >> the ingest profile, sometimes an in-memory tablet buffer will consume a
> >> large percentage of the total buffer.  This leads to long minor compactions
> >> when the buffer size is large which can allow ingest enough time to exhaust
> >> the buffer before that memory can be reclaimed. When a tablet server has to
> >> block ingest, it can affect client ingest rates to other tablet servers due
> >> to the way that batch writers work.  This can lead to other tablet servers
> >> underestimating future ingest rates which can further exacerbate the
> >> problem.
> >>
> >> There are some configuration changes that could reduce the severity of
> >> held commits, although they might reduce peak ingest rates.  Reducing the
> >> in memory map size can reduce the maximum pause time due to held commits.
> >> Adding additional tablets should help avoid the problem of a single tablet
> >> buffer consuming a large percentage of the memory region.  It might be
> >> better to aim for ~20 tablets per server if your problem allows for it.  It
> >> is also possible to replace the memory manager with a custom one.  I've
> >> tried this in the past and have seen stability improvements by making the
> >> memory thresholds less aggressive (50-75% full).  This did reduce peak
> >> ingest rate in some cases, but that was a reasonable tradeoff.
> >>
> >> Based on your current configuration, if a tablet server is serving 4
> >> tablets and has a 32GB buffer, your first minor compactions will be at
> >> least 8GB and they will probably grow larger over time until the tablets
> >> naturally split.  Consider how long it would take to write this RFile
> >> compared to your peak ingest rate.  As others have suggested, make sure to
> >> use the native maps.  Based on your current JVM heap size, using the Java
> >> in-memory map would probably lead to OOME or very bad GC performance.
> >>
> >> Accumulo can trace minor compaction durations so you can get a feel for
> >> max pause times or measure the effect of configuration changes.
> >>
> >> Cheers,
> >> --Jonathan
> >>
> >> On Wed, Jul 5, 2017 at 7:16 PM, Dave Marion <_dlmarion@comcast.net_
> >> <mailto:dlmarion@comcast.net>> wrote:
> >>
> >> Based on what Cyrille said, I would look at garbage collection,
> >> specifically I would look at how much of your newly allocated objects spill
> >> into the old generation before they are flushed to disk. Additionally, I
> >> would turn off the debug log or log to SSD’s if you have them. Another
> >> thought, seeing that you have 256GB RAM / node, is to run multiple tablet
> >> servers per node. Do you have 10 threads on your Batch Writers? What about
> >> the Batch Writer latency, is it too low such that you are not filling the
> >> buffer?
> >>
> >> *From:* Massimilian Mattetti [mailto:_MASSIMIL@il.ibm.com_ <mailto:
> >> MASSIMIL@il.ibm.com>] *
> >> Sent:* Wednesday, July 05, 2017 8:37 AM*
> >> To:* _user@accumulo.apache.org_ <mailto:user@accumulo.apache.org>*
> >> Subject:* maximize usage of cluster resources during ingestion
> >>
> >> Hi all,
> >>
> >> I have an Accumulo 1.8.1 cluster made by 12 bare metal servers. Each
> >> server has 256GB of Ram and 2 x 10 cores CPU. 2 machines are used as
> >> masters (running HDFS NameNodes, Accumulo Master and Monitor). The other 10
> >> machines has 12 Disks of 1 TB (11 used by HDFS DataNode process) and are
> >> running Accumulo TServer processes. All the machines are connected via a
> >> 10Gb network and 3 of them are running ZooKeeper. I have run some heavy
> >> ingestion test on this cluster but I have never been able to reach more
> >> than *20% *CPU usage on each Tablet Server. I am running an ingestion
> >> process (using batch writers) on each data node. The table is pre-split in
> >> order to have 4 tablets per tablet server. Monitoring the network I have
> >> seen that data is received/sent from each node with a peak rate of about
> >> 120MB/s / 100MB/s while the aggregated disk write throughput on each tablet
> >> servers is around 120MB/s.
> >>
> >> The table configuration I am playing with are:
> >> "table.file.replication": "2",
> >> "table.compaction.minor.logs.threshold": "10",
> >> "table.durability": "flush",
> >> "table.file.max": "30",
> >> "table.compaction.major.ratio": "9",
> >> "table.split.threshold": "1G"
> >>
> >> while the tablet server configuration is:
> >> "tserver.wal.blocksize": "2G",
> >> "tserver.walog.max.size": "8G",
> >> "tserver.memory.maps.max": "32G",
> >> "tserver.compaction.minor.concurrent.max": "50",
> >> "tserver.compaction.major.concurrent.max": "8",
> >> "tserver.total.mutation.queue.max": "50M",
> >> "tserver.wal.replication": "2",
> >> "tserver.compaction.major.thread.files.open.max": "15"
> >>
> >> the tablet server heap has been set to 32GB
> >>
> >>  From Monitor UI
> >>
> >>
> >> As you can see I have a lot of valleys in which the ingestion rate
> >> reaches 0.
> >> What would be a good procedure to identify the bottleneck which causes
> >> the 0 ingestion rate periods?
> >> Thanks.
> >>
> >> Best Regards,
> >> Max
> >>
> >>
> >>
> >>
> >>
> >>
> >>

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