Then try to do following 2 instead: 1) change your replicated region to partitioned region. (It will automatically split your putAll into 113 small putAlls). 2) change your max connection to 5000.
On Wed, Jun 26, 2019 at 12:15 PM aashish choudhary < aashish.choudha...@gmail.com> wrote: > So are you saying that we should put in batches of 1~10k. But that I tried > already atleast for 10k and it was failing with default readtimeout. > Additionally it takes forever to put all 600k records into that region in > batchmode. > > With best regards, > Ashish > > On Wed, Jun 26, 2019, 11:38 PM Xiaojian Zhou <gz...@pivotal.io> wrote: > >> You can increase max connection size from default 800 to 5000. We did >> that long time ago for customer. >> >> I noticed that your servers are using "replicated" region. In that case, >> then the singlehop will not take effect. That's fine. >> >> If putAll map is too big, then it will hit read timeout issue, because it >> will take longer time to process bigger map. >> 600k in one map is too big. According to my test, 1k to 10k is the >> comfortable size. Since increasing read timeout workaround your issue. I >> feel size too big is probably the real root cause. >> >> So my suggestions: >> 1) try to reduce your putAll map to 1k ~ 10K >> 2) If still not working, increase max connection size from 800 to 5000. >> >> Regards >> Gester Zhou >> >> >> >> On Wed, Jun 26, 2019 at 10:46 AM Charlie Black <cbl...@pivotal.io> wrote: >> >>> Try batches that are small as a starting point - say 100. >>> >>> On Wed, Jun 26, 2019 at 10:33 AM aashish choudhary < >>> aashish.choudha...@gmail.com> wrote: >>> >>>> Yes we see exceeded max-connections error on server side. >>>> >>>> So I was trying to see how the putAll API works in general and from a >>>> standard java client I was trying to simulate the behaviour that we see on >>>> our server. >>>> I tried to put 600k records using putAll on my local machine with 1 >>>> locator and 2 servers. Region type is replicate persistent and I could see >>>> that local clientCache API getting crashed with some "pool unexpected" >>>> error. We do see this error on our spark code as well. It then do a retry >>>> and gets failed. However surprisingly data gets inserted in the region even >>>> though clientCache java API was crashed. >>>> >>>> I tried to run it through in some batches but those also got failed and >>>> it's too slow. >>>> >>>> Only way I was able to make it work by is increasing readtimeout to 60 >>>> seconds. >>>> >>>> Can someone share some tips on putAll API? >>>> How to use it effectively? >>>> >>>> >>>> With best regards, >>>> Ashish >>>> >>>> On Wed, Jun 26, 2019, 6:20 AM Anilkumar Gingade <aging...@pivotal.io> >>>> wrote: >>>> >>>>> Ashish, >>>>> >>>>> Do you see "exceeded max-connections" error... >>>>> >>>>> Operation/Job getting completed second time indicates, the server >>>>> where the operation is executed first time may have issues, you may want >>>>> to >>>>> see the load on that server and if there are any memory issues. >>>>> >>>>> >>What is the recommended way to connect to geode using spark? >>>>> Its more of how the geode is used in this context; is the spark >>>>> processors are acting as geode's client or peer node. If its geode client, >>>>> then its more about tuning client connections based on how/what operations >>>>> are performed. >>>>> >>>>> Anil >>>>> >>>>> >>>>> >>>>> >>>>> On Tue, Jun 25, 2019 at 10:54 AM aashish choudhary < >>>>> aashish.choudha...@gmail.com> wrote: >>>>> >>>>>> We could also see below on server side logs as well. >>>>>> >>>>>> Rejected connection from Server connection from >>>>>> >> [client host address=x.yx.x.x; client port=abc] because incoming >>>>>> >> request was rejected by pool possibly due to thread exhaustion >>>>>> >> >>>>>> >>>>>> >>>>>> On Tue, Jun 25, 2019, 7:27 AM aashish choudhary < >>>>>> aashish.choudha...@gmail.com> wrote: >>>>>> >>>>>>> As I mentioned earlier threads count could go to 4000 and we have >>>>>>> seen readtimeout crossing default 10 seconds. We tried to increase read >>>>>>> timeout to 30 seconds but that didn't work either. Record count is not >>>>>>> more >>>>>>> than 600k. >>>>>>> >>>>>>> Job gets successful in second attempt without changing anything >>>>>>> which is bit weird. >>>>>>> >>>>>>> With best regards, >>>>>>> Ashish >>>>>>> >>>>>>> On Tue, Jun 25, 2019, 12:23 AM Anilkumar Gingade < >>>>>>> aging...@pivotal.io> wrote: >>>>>>> >>>>>>>> Hi Ashish, >>>>>>>> >>>>>>>> How many threads at a time executing putAll jobs in a single client >>>>>>>> (spark job?)... >>>>>>>> Do you see read timeout exception in client logs...If so, can you >>>>>>>> try increasing the read timeout value. Or reducing the putAll size. >>>>>>>> >>>>>>>> In case of PutAll for partitioned region; the putAll (entries) size >>>>>>>> is broken down and sent to respective servers based on its data >>>>>>>> affinity; >>>>>>>> the reason its working with partitioned region. >>>>>>>> >>>>>>>> You can find more detail on how client-server connection works at: >>>>>>>> >>>>>>>> https://geode.apache.org/docs/guide/14/topologies_and_comm/topology_concepts/how_the_pool_manages_connections.html >>>>>>>> <https://urldefense.proofpoint.com/v2/url?u=https-3A__geode.apache.org_docs_guide_14_topologies-5Fand-5Fcomm_topology-5Fconcepts_how-5Fthe-5Fpool-5Fmanages-5Fconnections.html&d=DwMFaQ&c=lnl9vOaLMzsy2niBC8-h_K-7QJuNJEsFrzdndhuJ3Sw&r=ytCZi8EyFn1QZDXaow7uOQ&m=cbnDKYT-WgN1H8tBKVimepu_Xn39dIjrxPUI5pUqafk&s=uDG5oxsM1CRDlWx2F-_QTqM8dJjygXiejHPkDxa7EFc&e=> >>>>>>>> >>>>>>>> -Anil. >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>> On Mon, Jun 24, 2019 at 10:04 AM aashish choudhary < >>>>>>>> aashish.choudha...@gmail.com> wrote: >>>>>>>> >>>>>>>>> Hi, >>>>>>>>> >>>>>>>>> We have been experiencing issues while connect to geode using >>>>>>>>> putAll API with spark. Issue is specific to one particular spark job >>>>>>>>> which >>>>>>>>> tries to load data to a replicated region. Exception we see in the >>>>>>>>> server >>>>>>>>> side is that default limit of 800 gets maxed out and on client side >>>>>>>>> we see >>>>>>>>> retry attempt to each server but gets failed even though when we re >>>>>>>>> ran the >>>>>>>>> same job it gets completed without any issue. >>>>>>>>> >>>>>>>>> In the code problem I could see is that we are connecting to geode >>>>>>>>> using client cache in forEachPartition which I think could be the >>>>>>>>> issue. So >>>>>>>>> for each partition we are making a connection to geode. In stats file >>>>>>>>> we >>>>>>>>> could see that connections getting timeout and there is thread burst >>>>>>>>> also >>>>>>>>> sometimes >4000. >>>>>>>>> >>>>>>>>> What is the recommended way to connect to geode using spark? >>>>>>>>> >>>>>>>>> But this one specific job which gets failed most of the times and >>>>>>>>> is a replicated region. Also when we change the type of region to >>>>>>>>> partitioned then job gets completed. We have enabled disk persistence >>>>>>>>> for >>>>>>>>> both type of regions. >>>>>>>>> >>>>>>>>> Thoughts? >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> With best regards, >>>>>>>>> Ashish >>>>>>>>> >>>>>>>> >>> >>> -- >>> Charlie Black | cbl...@pivotal.io >>> >>
