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From Josh Elser <els...@apache.org>
Subject Re: maximize usage of cluster resources during ingestion
Date Wed, 12 Jul 2017 15:16:52 GMT
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#_native_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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