Try shards.info=true, but pinging the shard directly is the most certain.
Best, Erick On Mon, Mar 14, 2016 at 9:48 AM, Anil <anilk...@gmail.com> wrote: > HI Erik, > > we have used document routing to balance the shards load and for > expand/collapse. it is mainly used for main_collection which holds one to > many relationship records. In file_collection, it is only for load > distribution. > > 25GB for entire solr service. each machine will act as shard for some > collections. > > we have not stress tested our servers at least for solr service. i have > read the the link you have shared, i will do something on it. thanks for > sharing. > > i have checked other collections, where index size is max 90GB and 5 M as > max number of documents. but for the particular file_collection_2014 , i > see total index size across replicas is 147 GB. > > Can we get any hints if we run the query with debugQuery=true ? what is > the effective way of load distribution ? Please advice. > > Regards, > Anil > > On 14 March 2016 at 20:32, Erick Erickson <erickerick...@gmail.com> wrote: > >> bq: The slowness is happening for file_collection. though it has 3 shards, >> documents are available in 2 shards. shard1 - 150M docs and shard2 has 330M >> docs , shard3 is empty. >> >> Well, this collection terribly balanced. Putting 330M docs on a single >> shard is >> pushing the limits, the only time I've seen that many docs on a shard, >> particularly >> with 25G of ram, they were very small records. My guess is that you will >> find >> the queries you send to that shard substantially slower than the 150M >> shard, >> although 150M could also be pushing your limits. You can measure this >> by sending the query to the specific core (something like >> >> solr/files_shard1_replica1/query?(your queryhere)&distrib=false >> >> My bet is that your QTime will be significantly different with the two >> shards. >> >> It also sounds like you're using implicit routing where you control where >> the >> files go, it's easy to have unbalanced shards in that case, why did you >> decide >> to do it this way? There are valid reasons, but... >> >> In short, my guess is that you've simply overloaded your shard with >> 330M docs. It's >> not at all clear that even 150 will give you satisfactory performance, >> have you stress >> tested your servers? Here's the long form of sizing: >> >> >> https://lucidworks.com/blog/2012/07/23/sizing-hardware-in-the-abstract-why-we-dont-have-a-definitive-answer/ >> >> Best, >> Erick >> >> On Mon, Mar 14, 2016 at 7:05 AM, Susheel Kumar <susheel2...@gmail.com> >> wrote: >> > For each of the solr machines/shards you have. Thanks. >> > >> > On Mon, Mar 14, 2016 at 10:04 AM, Susheel Kumar <susheel2...@gmail.com> >> > wrote: >> > >> >> Hello Anil, >> >> >> >> Can you go to Solr Admin Panel -> Dashboard and share all 4 memory >> >> parameters under System / share the snapshot. ? >> >> >> >> Thanks, >> >> Susheel >> >> >> >> On Mon, Mar 14, 2016 at 5:36 AM, Anil <anilk...@gmail.com> wrote: >> >> >> >>> HI Toke and Jack, >> >>> >> >>> Please find the details below. >> >>> >> >>> * How large are your 3 shards in bytes? (total index across replicas) >> >>> -- *146G. i am using CDH (cloudera), not sure how to check >> the >> >>> index size of each collection on each shard* >> >>> * What storage system do you use (local SSD, local spinning drives, >> remote >> >>> storage...)? *Local (hdfs) spinning drives* >> >>> * How much physical memory does your system have? *we have 15 data >> nodes. >> >>> multiple services installed on each data node (252 GB RAM for each data >> >>> node). 25 gb RAM allocated for solr service.* >> >>> * How much memory is free for disk cache? *i could not find.* >> >>> * How many concurrent queries do you issue? *very less. i dont see any >> >>> concurrent queries to this file_collection for now.* >> >>> * Do you update while you search? *Yes.. its very less.* >> >>> * What does a full query (rows, faceting, grouping, highlighting, >> >>> everything) look like? *for the file_collection, rows - 100, >> highlights = >> >>> false, no facets, expand = false.* >> >>> * How many documents does a typical query match (hitcount)? *it varies >> >>> with >> >>> each file. i have sort on int field to order commands in the query.* >> >>> >> >>> we have two sets of collections on solr cluster ( 17 data nodes) >> >>> >> >>> 1. main_collection - collection created per year. each collection uses >> 8 >> >>> shards 2 replicas ex: main_collection_2016, main_collection_2015 etc >> >>> >> >>> 2. file_collection (where files having commands are indexed) - >> collection >> >>> created per 2 years. it uses 3 shards and 2 replicas. ex : >> >>> file_collection_2014, file_collection_2016 >> >>> >> >>> The slowness is happening for file_collection. though it has 3 shards, >> >>> documents are available in 2 shards. shard1 - 150M docs and shard2 has >> >>> 330M >> >>> docs , shard3 is empty. >> >>> >> >>> main_collection is looks good. >> >>> >> >>> please let me know if you need any additional details. >> >>> >> >>> Regards, >> >>> Anil >> >>> >> >>> >> >>> On 13 March 2016 at 21:48, Anil <anilk...@gmail.com> wrote: >> >>> >> >>> > Thanks Toke and Jack. >> >>> > >> >>> > Jack, >> >>> > >> >>> > Yes. it is 480 million :) >> >>> > >> >>> > I will share the additional details soon. thanks. >> >>> > >> >>> > >> >>> > Regards, >> >>> > Anil >> >>> > >> >>> > >> >>> > >> >>> > >> >>> > >> >>> > On 13 March 2016 at 21:06, Jack Krupansky <jack.krupan...@gmail.com> >> >>> > wrote: >> >>> > >> >>> >> (We should have a wiki/doc page for the "usual list of suspects" >> when >> >>> >> queries are/appear slow, rather than need to repeat the same >> mantra(s) >> >>> for >> >>> >> every inquiry on this topic.) >> >>> >> >> >>> >> >> >>> >> -- Jack Krupansky >> >>> >> >> >>> >> On Sun, Mar 13, 2016 at 11:29 AM, Toke Eskildsen < >> >>> t...@statsbiblioteket.dk> >> >>> >> wrote: >> >>> >> >> >>> >> > Anil <anilk...@gmail.com> wrote: >> >>> >> > > i have indexed a data (commands from files) with 10 fields and >> 3 of >> >>> >> them >> >>> >> > is >> >>> >> > > text fields. collection is created with 3 shards and 2 >> replicas. I >> >>> >> have >> >>> >> > > used document routing as well. >> >>> >> > >> >>> >> > > Currently collection holds 47,80,01,405 records. >> >>> >> > >> >>> >> > ...480 million, right? Funny digit grouping in India. >> >>> >> > >> >>> >> > > text search against text field taking around 5 sec. solr is >> query >> >>> just >> >>> >> > and >> >>> >> > > of two terms with fl as 7 fields >> >>> >> > >> >>> >> > > fileId:"file unique id" AND command_text:(system login) >> >>> >> > >> >>> >> > While not an impressive response time, it might just be that your >> >>> >> hardware >> >>> >> > is not enough to handle that amount of documents. The usual >> culprit >> >>> is >> >>> >> IO >> >>> >> > speed, so chances are you have a system with spinning drives and >> not >> >>> >> enough >> >>> >> > RAM: Switch to SSD and/or add more RAM. >> >>> >> > >> >>> >> > To give better advice, we need more information. >> >>> >> > >> >>> >> > * How large are your 3 shards in bytes? >> >>> >> > * What storage system do you use (local SSD, local spinning >> drives, >> >>> >> remote >> >>> >> > storage...)? >> >>> >> > * How much physical memory does your system have? >> >>> >> > * How much memory is free for disk cache? >> >>> >> > * How many concurrent queries do you issue? >> >>> >> > * Do you update while you search? >> >>> >> > * What does a full query (rows, faceting, grouping, highlighting, >> >>> >> > everything) look like? >> >>> >> > * How many documents does a typical query match (hitcount)? >> >>> >> > >> >>> >> > - Toke Eskildsen >> >>> >> > >> >>> >> >> >>> > >> >>> > >> >>> >> >> >> >> >>
