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From Cyrille Savelief <>
Subject Re: maximize usage of cluster resources during ingestion
Date Thu, 06 Jul 2017 08:47:37 GMT
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 <> 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",
>  "": "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 <>
> To:
> 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 <**
> <>> 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:**
> <>]
> *Sent:* Wednesday, July 05, 2017 8:37 AM
> *To:* ** <>
> *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",
> "": "50M",
> "tserver.wal.replication": "2",
> "": "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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