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 >> >> > >> >> >> > >> > >> > >
