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From "Meier, Caleb" <Caleb.Me...@parsons.com>
Subject RE: fluo accumulo table tablet servers not keeping up with application
Date Tue, 31 Oct 2017 18:22:08 GMT
Hey Keith,

Just following up on your last message.  After looking at the worker ScanTask logs, it seems
like the workers are conducting scans as frequently as the min sleep time permits.  That is,
if the min sleep time is set to 10s, a ScanTask is being executed every 10s.  In addition,
running the Fluo wait command indicates that the number of outstanding notifications steadily
increases or is held constant (depending on the number of workers).  Based on your comments
below, it seems like the workers should be scanning at a lower rate given that the notification
work queue is constantly increasing in size.  Another thing that we tried was reducing the
number of workers and increasing the min sleep time.  This lowered the scan burden on the
tablet server, but unsurprisingly our processing rate plummeted.  We also tried lowering the
ingest rate for a fixed number of workers (lowering the notification rate for each worker
thread).  While it took longer for the TabletServer to become saturated, it still became overwhelmed.
 

In general, for the queries that we are benchmarking, our notification:data ratio is about
7:1 (i.e. each piece of ingested data generates about 7 notifications on the way to being
entirely processed).  I think that this is our primary culprit, but I think that our application
specific scans are also part of the problem (I'm still in the process of trying to determine
what portion of the scans that we are seeing is specific to our observers and what portion
is specific to notification discovery - any suggestions here would be appreciated).  One reason
that I think notification discovery is the culprit is that we implemented an in memory cache
for the metadata, and that didn't seem to affect the scan rate too much (metadata seeks constitute
about 30% of our seeks/scans). 

Going forward, we're going to shard our data and look into ways to cut down on scans.  Any
other suggestions about how to improve performance would be appreciated.

Thanks,
Caleb

Caleb A. Meier, Ph.D.
Senior Software Engineer ♦ Analyst
Parsons Corporation
1911 N. Fort Myer Drive, Suite 800 ♦ Arlington, VA 22209
Office:  (703)797-3066
Caleb.Meier@Parsons.com ♦ www.parsons.com

-----Original Message-----
From: Keith Turner [mailto:keith@deenlo.com] 
Sent: Friday, October 27, 2017 12:17 PM
To: fluo-dev <dev@fluo.apache.org>
Subject: Re: fluo accumulo table tablet servers not keeping up with application

On Fri, Oct 27, 2017 at 11:03 AM, Meier, Caleb <Caleb.Meier@parsons.com> wrote:
> Hey Keith,
>
> Our benchmark consists of a single query that is a join of two statement patterns (essentially
patterns that incoming data matches, where a unit of data is a statement).  We are ingesting
50 pairs of statements a minute (100 total), where each statement in the pair matches one
of the statement patterns.  Because the data is being ingested at a constant rate, the statement
pattern Observers and Join Observers are constantly working.  One thing that is worth mentioning
is that we changed the property fluo.implScanTask.maxSleep from 5 min to 10 seconds.  Based
on the constant ingest rate, your comments below, and our low maxSleep, it seems like the
workers would constantly be scanning for new notifications.
>
>> Once a worker scans all tablets and finds a list of notifications, it does not scan
again until half of those notifications are processed.
>
> How does the maxSleep property work in conjunction with this?  If the max sleep time
elapses before a worker processes half of the notifications, will it scan?

I don't think it will scan again until the # of queued notifications is cut in half.  I looked
in 1.0.0 and 1.1.0 and I think while loops linked below should hold off on the scan until
the queue halves.

https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_apache_fluo_blob_rel_fluo-2D1.0.0-2Dincubating_modules_core_src_main_java_org_apache_fluo_core_worker_finder_hash_ScanTask.java-23L85&d=DwIFaQ&c=Nwf-pp4xtYRe0sCRVM8_LWH54joYF7EKmrYIdfxIq10&r=vuVdzYC2kksVZR5STiFwDpzJ7CrMHCgeo_4WXTD0qo8&m=btY_WNg1O7SuwcHi1m2ksRp3ggzrI7nJlnC2B5cHgaU&s=BRyQS2DPBtEfUvHT-JKBXPWABrSyihP6yaJcfE1BJFQ&e=
https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_apache_fluo_blob_rel_fluo-2D1.1.0-2Dincubating_modules_core_src_main_java_org_apache_fluo_core_worker_finder_hash_ScanTask.java-23L88&d=DwIFaQ&c=Nwf-pp4xtYRe0sCRVM8_LWH54joYF7EKmrYIdfxIq10&r=vuVdzYC2kksVZR5STiFwDpzJ7CrMHCgeo_4WXTD0qo8&m=btY_WNg1O7SuwcHi1m2ksRp3ggzrI7nJlnC2B5cHgaU&s=ZxURCZE5k65I008z7o4UQGsm6o0mBtJnwV_N6Y668oM&e=

Were you able to find the ScanTask debug messages in the worker logs?
Below are the log messages int the code to give a sense of what to look for.

https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_apache_fluo_blob_rel_fluo-2D1.0.0-2Dincubating_modules_core_src_main_java_org_apache_fluo_core_worker_finder_hash_ScanTask.java-23L130&d=DwIFaQ&c=Nwf-pp4xtYRe0sCRVM8_LWH54joYF7EKmrYIdfxIq10&r=vuVdzYC2kksVZR5STiFwDpzJ7CrMHCgeo_4WXTD0qo8&m=btY_WNg1O7SuwcHi1m2ksRp3ggzrI7nJlnC2B5cHgaU&s=C141kYyjygBL3kWZyUObU1-nu4ZjvMnu7xp_QbIGkCA&e=
https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_apache_fluo_blob_rel_fluo-2D1.1.0-2Dincubating_modules_core_src_main_java_org_apache_fluo_core_worker_finder_hash_ScanTask.java-23L146&d=DwIFaQ&c=Nwf-pp4xtYRe0sCRVM8_LWH54joYF7EKmrYIdfxIq10&r=vuVdzYC2kksVZR5STiFwDpzJ7CrMHCgeo_4WXTD0qo8&m=btY_WNg1O7SuwcHi1m2ksRp3ggzrI7nJlnC2B5cHgaU&s=4Qy1-LbMEpJ7NZLqngU8ZOEOBv6nB0nXM8mjkWdpEL4&e=

IIRC I think if notifications were found in a tablet during the last scan, then it will always
scan it during the next scan loop.  As notifications are not found in a tablet then that tablets
next scan time doubles up to fluo.implScanTask.maxSleep.

So its possible that all notifications found are being processed quickly and then the workers
are scanning for more.  The debug messages would show this.

There is also a minSleep time.  This property determines the minimum amount of time it will
sleep between scan loops, seems to default to 5 secs.  Could try increasing this.

Looking at the props, it seems they prop names for min and max sleep changed between 1.0.0
and 1.1.0.


>
> Caleb A. Meier, Ph.D.
> Senior Software Engineer ♦ Analyst
> Parsons Corporation
> 1911 N. Fort Myer Drive, Suite 800 ♦ Arlington, VA 22209
> Office:  (703)797-3066
> Caleb.Meier@Parsons.com ♦ www.parsons.com
>
> -----Original Message-----
> From: Keith Turner [mailto:keith@deenlo.com]
> Sent: Thursday, October 26, 2017 6:20 PM
> To: fluo-dev <dev@fluo.apache.org>
> Subject: Re: fluo accumulo table tablet servers not keeping up with 
> application
>
> On Thu, Oct 26, 2017 at 5:47 PM, Meier, Caleb <Caleb.Meier@parsons.com> wrote:
>> Hey Keith,
>>
>> We'll rerun the benchmarks tomorrow and track the outstanding notifications.  We'll
also see if compacting at some point during ingest helps with the scan rate.  Have you observed
such high scan rates for such a small amount of data in any of your benchmarking?  What would
account for the huge disparity in results read vs. results returned?  It seems like our scans
are extremely inefficient for some reason.  Our tablet servers are becoming overwhelmed even
before data gets flushed to disk.
>
> Oh I never saw you attachment, may not be able to attach stuff on mailing list.
>
> Its possible that what you are seeing is the workers scanning for notifications.  If
you look in the workers logs do you see messages about scanning for notifications?  If so
what do they look like?
>
> In 1.0.0 each worker scans all tablets in random order.  When it scans it has an iterator
that uses hash+mod to select a subset of notifications.  The iterator also suppresses deleted
notifications.
> So the selection and suppression by that iterator could explain the read vs returned.
 It does exponential back off on tablets where it does not find data.  Once a worker scans
all tablets and finds a list of notifications, it does not scan again until half of those
notifications are processed.
>
> In the beginning, would you have a lot of notifications?  If so I would expect a lot
of scanning and then it should slow down once the workers get a list of notifications to process.
>
> In 1.1.0 the workers divide up the tablets (so workers no longer scan
> all tablets, groups of workers share groups of tablets).   If the
> table is splits after the workers start, it may take them a bit to execute the distributed
algorithm that divys tablets among workers.
>
> Anyway the debug messages about scanning for notifications in the workers should provide
some insight into this.
>
> If its not notification scanning, then it could be that the application is scanning over
a lots of data that was deleted or something like that.
>
>>
>> Caleb A. Meier, Ph.D.
>> Senior Software Engineer ♦ Analyst
>> Parsons Corporation
>> 1911 N. Fort Myer Drive, Suite 800 ♦ Arlington, VA 22209
>> Office:  (703)797-3066
>> Caleb.Meier@Parsons.com ♦ www.parsons.com
>>
>> -----Original Message-----
>> From: Keith Turner [mailto:keith@deenlo.com]
>> Sent: Thursday, October 26, 2017 5:36 PM
>> To: fluo-dev <dev@fluo.apache.org>
>> Subject: Re: fluo accumulo table tablet servers not keeping up with 
>> application
>>
>> On Thu, Oct 26, 2017 at 2:50 PM, Meier, Caleb <Caleb.Meier@parsons.com> wrote:
>>> Hey Keith,
>>>
>>> Thanks for the reply.  Regarding our benchmark, I've attached some screenshots
of our Accumulo UI that were taken while the benchmark was running.  Basically, our ingest
rate is pretty low (about 150 entries/s, but our scan rate is off the charts - approaching
6 million entries/s!).  Also, notice the disparity between reads and returned in the Scan
chart.  That disparity would suggest that we're possibly doing full table scans somewhere,
which is strange given that all of our scans are RowColumn constrained.  Perhaps we are building
our Scanner incorrectly.   In an effort to maximize the number of TabletServers, we split
the Fluo table into 5MB tablets.  Also, the data is not well balanced -- the tablet servers
do take turns being maxed out while others are idle.  We're considering possible sharding
strategies.
>>>
>>> Given that our TabletServers are getting saturated so quickly for such a low
ingest rate, it seems like we definitely need to cut down on the number of scans as a first
line of attack to see what that buys us.  Then we'll look into tuning Accumulo and Fluo. 
Does this seem like a reasonable approach to you?  Does the scan rate of our application strike
you as extremely high?  When you look at the Rya Observers, can you pay attention to how we
are building our scans to make sure that we're not inadvertently doing full table scans? 
Also, what exactly do you mean by "are the 6 lookups in the transaction done sequentially"?
>>
>> Regarding the scan rate there are few things I Am curious about.
>>
>> Fluo workers scan for notifications in addition to the scanning done 
>> by your apps.  I made some changes in 1.1.0 to reduce the amount of 
>> scanning needed to find notifications, but this should not make much 
>> of a difference on a small amount of nodes.  Details about this are 
>> in
>> 1.1.0 release notes.  I am not sure what the best way is to determine how much of
the scanning you are seeing is app vs notification finding.  Can you run the fluo wait command
to see how many outstanding notifications there are?
>>
>> Transactions leave a paper trail behind and compactions clean this up (Fluo has a
garbage collection iterator).  This is why I asked what effect compacting the table had. 
Compactions will also clean up deleted notifications.
>>
>>
>>>
>>> Thanks,
>>> Caleb
>>>
>>> Caleb A. Meier, Ph.D.
>>> Senior Software Engineer ♦ Analyst
>>> Parsons Corporation
>>> 1911 N. Fort Myer Drive, Suite 800 ♦ Arlington, VA 22209
>>> Office:  (703)797-3066
>>> Caleb.Meier@Parsons.com ♦ www.parsons.com
>>>
>>> -----Original Message-----
>>> From: Keith Turner [mailto:keith@deenlo.com]
>>> Sent: Thursday, October 26, 2017 1:39 PM
>>> To: fluo-dev <dev@fluo.apache.org>
>>> Subject: Re: fluo accumulo table tablet servers not keeping up with 
>>> application
>>>
>>> Caleb
>>>
>>> What if any tuning have you done?  The following tune-able Accumulo parameters
impact performance.
>>>
>>>  * Write ahead log sync settings (this can have huge performance
>>> implications)
>>>  * Files per tablet
>>>  * Tablet server cache sizes
>>>  * Accumulo data block sizes
>>>  * Tablet server client thread pool size
>>>
>>> For Fluo the following tune-able parameters are important.
>>>
>>>  * Commit memory (this determines how many transactions are held in 
>>> memory while committing)
>>>  * Threads running transactions
>>>
>>> What does the load (CPU and memory) on the cluster look like?  I'm curious how
even it is?  For example is one tserver at 100% cpu while others are idle, this could be caused
by uneven data access patterns.
>>>
>>> Would it be possible for me to see or run the benchmark?  I am going to take
a look at the Rya observers, let me know if there is anything in particular I should look
at.
>>>
>>> Are the 6 lookups in the transaction done sequentially?
>>>
>>> Keith
>>>
>>> On Thu, Oct 26, 2017 at 11:34 AM, Meier, Caleb <Caleb.Meier@parsons.com>
wrote:
>>>> Hello Fluo Devs,
>>>>
>>>> We have implemented an incremental query evaluation service for Apache Rya
that leverages Apache Fluo.  We’ve been doing some benchmarking and we’ve found that the
Accumulo Tablet servers for the Fluo table are falling behind pretty quickly for our application.
 We’ve tried splitting the Accumulo Table so that we have more Tablet Servers, but that
doesn’t really buy us too much.  Our application is fairly scan intensive—we have a metadata
framework in place that allows us to pass query results through the query tree, and each observer
needs to look up metadata to determine which observer to route its data to after processing.
 To give you some indication of our scan rates, our Join Observer does about 6 lookups, builds
a scanner to do one RowColumn restricted scan, and then does many writes.  So an obvious way
to alleviate the burden on the TableServer is to cut down on the number of scans.
>>>>
>>>> One approach that we are considering is to import all of our metadata into
memory.  Essentially, each Observer would need access to an in memory metadata cache.  We’re
considering using the Observer context, but this cache needs to be mutable because a user
needs to be able to register new queries.  Is it possible to update the context, or would
we need to restart the application to do that?  I guess other options would be to create a
static cache for each Observer that stores the metadata, or to store it in Zookeeper.  Have
any of you devs ever had create a solution to share state between Observers that doesn’t
rely on the Fluo table?
>>>>
>>>> In addition to cutting down on the scan rate, are there any other approaches
that you would consider?  I assume that the problem lies primarily with how we’ve implemented
our application, but I’m also wondering if there is anything we can do from a configuration
point of view to reduce the burden on the Tablet servers.  Would reducing the number of workers/worker
threads to cut down on the number of times a single observation is processed be helpful? 
It seems like this approach would cut out some redundant scans as well, but it might be more
of a second order optimization. In general, any insight that you might have on this problem
would be greatly appreciated.
>>>>
>>>> Sincerely,
>>>> Caleb Meier
>>>>
>>>> Caleb A. Meier, Ph.D.
>>>> Senior Software Engineer ♦ Analyst
>>>> Parsons Corporation
>>>> 1911 N. Fort Myer Drive, Suite 800 ♦ Arlington, VA 22209
>>>> Office:  (703)797-3066
>>>> Caleb.Meier@Parsons.com<mailto:Caleb.Meier@Parsons.com> ♦ 
>>>> www.parsons.com<https://webportal.parsons.com/,DanaInfo=www.parsons.
>>>> c
>>>> om+>
>>>>
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