Bernd,
But why do you have so many deletes? Is it expected?
When you run DIHs concurrently, do you shard intput data by uniqueKey?

On Wed, Jul 27, 2016 at 6:20 PM, Bernd Fehling <
bernd.fehl...@uni-bielefeld.de> wrote:

> If there is a problem in single index then it might also be in CloudSolr.
> As far as I could figure out from INFOSTREAM, documents are added to
> segments
> and terms are "collected". Duplicate term are "deleted" (or whatever).
> These deletes (or whatever) are not concurrent.
> I have a lines like:
> BD 0 [Wed Jul 27 13:28:48 GMT+01:00 2016; Thread-27879]: applyDeletes:
> infos=...
> BD 0 [Wed Jul 27 13:31:48 GMT+01:00 2016; Thread-27879]: applyDeletes took
> 180028 msec
> ...
> BD 0 [Wed Jul 27 13:42:03 GMT+01:00 2016; Thread-27890]: applyDeletes:
> infos=...
> BD 0 [Wed Jul 27 14:38:55 GMT+01:00 2016; Thread-27890]: applyDeletes took
> 3411845 msec
>
> 3411545 msec are about 56 minutes where the system is doing what???
> At least not indexing because only one JAVA process and no I/O at all!
>
> How can SolrJ help me now with this problem?
>
> Best
> Bernd
>
>
> Am 27.07.2016 um 16:41 schrieb Erick Erickson:
> > Well, at least it'll be easier to debug in my experience. Simple example.
> > At some point you'll call CloudSolrClient.add(doc list). Comment just
> that
> > out and you'll be able to isolate whether the issue is querying the be or
> > sending to Solr.
> >
> > Then CloudSolrClient (assuming SolrCloud) has efficiencies in terms of
> > routing...
> >
> > Best
> > Erick
> >
> > On Jul 27, 2016 7:24 AM, "Bernd Fehling" <bernd.fehl...@uni-bielefeld.de
> >
> > wrote:
> >
> >> So writing some SolrJ doing the same job as the DIH script
> >> and using that concurrent will solve my problem?
> >> I'm not using Tika.
> >>
> >> I don't think that DIH is my problem, even if it is not the best
> solution
> >> right now.
> >> Nevertheless, you are right SolrJ has higher performance, but what
> >> if I have the same problems with SolrJ like with DIH?
> >>
> >> If it runs with DIH it should run with SolrJ with additional performance
> >> boost.
> >>
> >> Bernd
> >>
> >>
> >> On 27.07.2016 at 16:03, Erick Erickson:
> >>> I'd actually recommend you move to a SolrJ solution
> >>> or similar. Currently, you're putting a load on the Solr
> >>> servers (especially if you're also using Tika) in addition
> >>> to all indexing etc.
> >>>
> >>> Here's a sample:
> >>> https://lucidworks.com/blog/2012/02/14/indexing-with-solrj/
> >>>
> >>> Dodging the question I know, but DIH sometimes isn't
> >>> the best solution.
> >>>
> >>> Best,
> >>> Erick
> >>>
> >>> On Wed, Jul 27, 2016 at 6:59 AM, Bernd Fehling
> >>> <bernd.fehl...@uni-bielefeld.de> wrote:
> >>>> After enhancing the server with SSDs I'm trying to speed up indexing.
> >>>>
> >>>> The server has 16 CPUs and more than 100G RAM.
> >>>> JAVA (1.8.0_92) has 24G.
> >>>> SOLR is 4.10.4.
> >>>> Plain XML data to load is 218G with about 96M records.
> >>>> This will result in a single index of 299G.
> >>>>
> >>>> I tried with 4, 8, 12 and 16 concurrent DIHs.
> >>>> 16 and 12 was to much because for 16 CPUs and my test continued with 8
> >> concurrent DIHs.
> >>>> Then i was trying different <indexConfig> and <updateHandler> settings
> >> but now I'm stuck.
> >>>> I can't figure out what is the best setting for bulk indexing.
> >>>> What I see is that the indexing is "falling asleep" after some time of
> >> indexing.
> >>>> It is only producing del-files, like _11_1.del, _w_2.del, _h_3.del,...
> >>>>
> >>>> <indexConfig>
> >>>>     <maxIndexingThreads>8</maxIndexingThreads>
> >>>>     <ramBufferSizeMB>1024</ramBufferSizeMB>
> >>>>     <maxBufferedDocs>-1</maxBufferedDocs>
> >>>>     <mergePolicy class="org.apache.lucene.index.TieredMergePolicy">
> >>>>       <int name="maxMergeAtOnce">8</int>
> >>>>       <int name="segmentsPerTier">100</int>
> >>>>       <int name="maxMergedSegmentMB">512</int>
> >>>>     </mergePolicy>
> >>>>     <mergeFactor>8</mergeFactor>
> >>>>     <mergeScheduler
> >> class="org.apache.lucene.index.ConcurrentMergeScheduler"/>
> >>>>     <lockType>${solr.lock.type:native}</lockType>
> >>>>     ...
> >>>> </indexConfig>
> >>>>
> >>>> <updateHandler class="solr.DirectUpdateHandler2">
> >>>>      ### no autocommit at all
> >>>>      <autoSoftCommit>
> >>>>        <maxTime>${solr.autoSoftCommit.maxTime:-1}</maxTime>
> >>>>      </autoSoftCommit>
> >>>> </updateHandler>
> >>>>
> >>>>
> >>>>
> >>
> command=full-import&optimize=false&clean=false&commit=false&waitSearcher=false
> >>>> After indexing finishes there is a final optimize.
> >>>>
> >>>> My idea is, if 8 DIHs use 8 CPUs then I have 8 CPUs left for merging
> >>>> (maxIndexingThreads/maxMergeAtOnce/mergeFactor).
> >>>> It should do no commit, no optimize.
> >>>> ramBufferSizeMB is high because I have plenty of RAM and I want make
> >> use the speed of RAM.
> >>>> segmentsPerTier is high to reduce merging.
> >>>>
> >>>> But somewhere is a misconfiguration because indexing gets stalled.
> >>>>
> >>>> Any idea what's going wrong?
> >>>>
> >>>>
> >>>> Bernd
> >>>>
> >>
> >
>
> --
> *************************************************************
> Bernd Fehling                    Bielefeld University Library
> Dipl.-Inform. (FH)                LibTec - Library Technology
> Universitätsstr. 25                  and Knowledge Management
> 33615 Bielefeld
> Tel. +49 521 106-4060       bernd.fehling(at)uni-bielefeld.de
>
> BASE - Bielefeld Academic Search Engine - www.base-search.net
> *************************************************************
>



-- 
Sincerely yours
Mikhail Khludnev

Reply via email to