yep it is really weird since Kudu does not use neither one. I'll get with him on Monday to gather more details
On Sat, Dec 16, 2017 at 3:28 PM, Jean-Daniel Cryans <[email protected]> wrote: > 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 <[email protected]> > 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 <[email protected]> >> 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 <[email protected] >>> > wrote: >>> >>>> On Wed, Dec 13, 2017 at 11:30 AM, Boris Tyukin <[email protected]> >>>> 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 < >>>>> [email protected]> 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 <[email protected]> >>>>>> 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* >>>>>>> >>>>>>> >>>>>>> >>>>>>> >>>>>>> >>>>>> >>>>> >>>> >>> >> >
