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From Jean-Daniel Cryans <jdcry...@apache.org>
Subject Re: first and second run 2x query time difference
Date Sat, 16 Dec 2017 20:28:22 GMT
Hi Boris,

How exactly did HDFS and ZK go down? A Kudu restart is fairly IO-intensive
but I don't know how that can cause things like DataNodes to fail.

J-D

On Sat, Dec 16, 2017 at 11:45 AM, Boris Tyukin <boris@boristyukin.com>
wrote:

> well our admin had fun two days - it was the first time we restarted Kudu
> on our DEV cluster and it did not go well. He is still troubleshooting what
> happened but after Kudu restart zookeeper and HDFS went down after 3-4
> minutes. If we disable Kudu, all is well. No error in Kudu logs...I will
> have more details next week so not asking for help as I do not know all the
> details. What is obvious thought is that it has to do something with Kudu :)
>
> On Thu, Dec 14, 2017 at 9:40 AM, Boris Tyukin <boris@boristyukin.com>
> wrote:
>
>> thanks for your suggestions, J-D, I am sure you are right more often than
>> that! :))
>>
>> I will report back with our results. So far I am really impressed with
>> Kudu - we have been benchmarking ingest and egress throughput and our
>> typical queries runtime. The biggest pain so far is lack of support for
>> decimals
>>
>> On Wed, Dec 13, 2017 at 5:07 PM, Jean-Daniel Cryans <jdcryans@apache.org>
>> wrote:
>>
>>> On Wed, Dec 13, 2017 at 11:30 AM, Boris Tyukin <boris@boristyukin.com>
>>> wrote:
>>>
>>>> thanks J-D! we are going to try that and see how it impacts the
>>>> runtime.
>>>>
>>>> is there any way to load this metadata upfront? a lot of our queries
>>>> are adhoc in nature but they will be hitting the same tables with different
>>>> predicates and join patterns though.
>>>>
>>>
>>> You could use Impala to compute all the stats of all the tables after
>>> each Kudu restart. Actually, do try that, restart Kudu then compute stats
>>> and see how fast it scans.
>>>
>>>
>>>>
>>>> I am curious why this metadata does not survive restarts though. We are
>>>> going to run our benchmarks again and this time restart Kudu and Impala.
>>>>
>>>
>>> It's in the tserver memory, it can't survive a restart.
>>>
>>>
>>>>
>>>> I just ran another query first time which hits 2 large tables and these
>>>> tables have been scanned by the previous query and this time I do not see
>>>> any difference in query time before the first and second time - I guess
>>>> this confirms your statement about " first time ever scanning the
>>>> table since a Kudu restart" and collecting metadata.
>>>>
>>>
>>> Maybe, I've been known to be right once or twice a year :)
>>>
>>>
>>>>
>>>>
>>>> On Wed, Dec 13, 2017 at 11:18 AM, Jean-Daniel Cryans <
>>>> jdcryans@apache.org> wrote:
>>>>
>>>>> Hi Boris,
>>>>>
>>>>> Given that we don't have much data we can use here, I'll have to
>>>>> extrapolate. As an aside though, this is yet another example where we
need
>>>>> more Kudu-side metrics in the query profile.
>>>>>
>>>>> So, Kudu lazily loads a bunch of metadata and that can really affect
>>>>> scan times. If this was your first time ever scanning the table since
a
>>>>> Kudu restart, it's very possible that that's where that time was spent.
>>>>> There's also the page cache in the OS that might now be populated. You
>>>>> could do something like "sync; echo 3 > /proc/sys/vm/drop_caches"
on all
>>>>> the machines and run the query 2 times again, without restarting Kudu,
to
>>>>> understand the effect of the page cache itself. There's currently now
way
>>>>> to purge the cached metadata in Kudu though.
>>>>>
>>>>> Hope this helps a bit,
>>>>>
>>>>> J-D
>>>>>
>>>>> On Wed, Dec 13, 2017 at 8:07 AM, Boris Tyukin <boris@boristyukin.com>
>>>>> wrote:
>>>>>
>>>>>> Hi guys,
>>>>>>
>>>>>> I am doing some benchmarks with Kudu and Impala/Parquet and hope
to
>>>>>> share it soon but there is one thing that bugs me. This is perhaps
Impala
>>>>>> question but since I am using Kudu with Impala I am going to try
and ask
>>>>>> anyway.
>>>>>>
>>>>>> One of my queries takes 120 seconds to run the very first time. It
>>>>>> joins one large 5B row table with a bunch of smaller tables and then
stores
>>>>>> result in Impala/parquet (not Kudu).
>>>>>>
>>>>>> Now if I run it second and third time, it only takes 60 seconds.
Can
>>>>>> someone explain why? Is there any settings to decrease this gap?
>>>>>>
>>>>>> I've compared query profiles in CM and the only thing that was very
>>>>>> different is scan against Kudu table (the large one):
>>>>>>
>>>>>> ***************************
>>>>>> first time:
>>>>>> ***************************
>>>>>> KUDU_SCAN_NODE (id=0) (47.68s)
>>>>>> <https://lkmaorabd103.multihosp.net:7183/cmf/impala/queryDetails?queryId=5143f7165be82819%3Ae00a103500000000&serviceName=impala#>
>>>>>>
>>>>>>
>>>>>>
>>>>>>    - BytesRead: *0 B*
>>>>>>    - InactiveTotalTime: *0ns*
>>>>>>    - KuduRemoteScanTokens: *0*
>>>>>>    - NumScannerThreadsStarted: *20*
>>>>>>    - PeakMemoryUsage: *35.8 MiB*
>>>>>>    - RowsRead: *693,502,241*
>>>>>>    - RowsReturned: *693,502,241*
>>>>>>    - RowsReturnedRate: *14643448 per second*
>>>>>>    - ScanRangesComplete: *20*
>>>>>>    - ScannerThreadsInvoluntaryContextSwitches: *1,341*
>>>>>>    - ScannerThreadsTotalWallClockTime: *36.2m*
>>>>>>       - MaterializeTupleTime(*): *47.57s*
>>>>>>       - ScannerThreadsSysTime: *31.42s*
>>>>>>       - ScannerThreadsUserTime: *1.7m*
>>>>>>    - ScannerThreadsVoluntaryContextSwitches: *96,855*
>>>>>>    - TotalKuduScanRoundTrips: *52,308*
>>>>>>    - TotalReadThroughput: *0 B/s*
>>>>>>    - TotalTime: *47.68s*
>>>>>>
>>>>>>
>>>>>> ***************************
>>>>>> second time:
>>>>>> ***************************
>>>>>> KUDU_SCAN_NODE (id=0) (4.28s)
>>>>>> <https://lkmaorabd103.multihosp.net:7183/cmf/impala/queryDetails?queryId=53497a308f860837%3A243772e000000000&serviceName=impala#>
>>>>>>
>>>>>>
>>>>>>
>>>>>>    - BytesRead: *0 B*
>>>>>>    - InactiveTotalTime: *0ns*
>>>>>>    - KuduRemoteScanTokens: *0*
>>>>>>    - NumScannerThreadsStarted: *20*
>>>>>>    - PeakMemoryUsage: *37.9 MiB*
>>>>>>    - RowsRead: *693,502,241*
>>>>>>    - RowsReturned: *693,502,241*
>>>>>>    - RowsReturnedRate: *173481534 per second*
>>>>>>    - ScanRangesComplete: *20*
>>>>>>    - ScannerThreadsInvoluntaryContextSwitches: *1,451*
>>>>>>    - ScannerThreadsTotalWallClockTime: *19.5m*
>>>>>>       - MaterializeTupleTime(*): *4.20s*
>>>>>>       - ScannerThreadsSysTime: *38.22s*
>>>>>>       - ScannerThreadsUserTime: *1.7m*
>>>>>>    - ScannerThreadsVoluntaryContextSwitches: *480,870*
>>>>>>    - TotalKuduScanRoundTrips: *52,142*
>>>>>>    - TotalReadThroughput: *0 B/s*
>>>>>>    - TotalTime: *4.28s*
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>
>>>>
>>>
>>
>

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