Seeley Yonik - Solr Performance Key Innovations

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Solr Performance & Key Innovations Yonik Seeley, Lucid Imagination yonik@lucidimagination.com, May 26 2011


Solr 3.1 Highlights §  Numeric range facets (similar to date faceting). §  New spatial search, including spatial filtering, boosting and sorting capabilities. §  Example Velocity driven search UI at http://localhost:8983/solr/browse §  A new faster termvector-based highlighter. §  Extended dismax (edismax) query parser with support for fielded queries, enhanced relevancy, and full lucene syntax support. §  Distributed search support for the Spell check and Terms components. 3


Solr 3.1 Highlights (continued) §  Suggester, a fast trie-based autocomplete component. §  Sort results by any function query. §  JSON document indexing. §  CSV response format §  Apache UIMA integration for metadata extraction. §  Tons of optimizations, bugfixes, and new analysis capabilities via Apache Lucene 3.1.

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What’s not in 3.1? §  Result Grouping (AKA Field Collapsing) §  Pivot Faceting §  SolrCloud §  Pseudo-fields §  Pseudo-join §  Relevancy function queries §  Per-segment faceting §  *Tons* of new Lucene performance/efficiency goodness 5


Recent Lucene Performance §  TieredMergePolicy – the new default •  •  •  •

Much better for incremental indexing / NRT Ignores segment order when selecting best merge Takes deletes into account Does not over-merge (no cascading merges)

§  Finite State Transducer (FST) based terms index

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DocumentWriterPerThread (DWPT) §  Flushing new segment is now concurrent w/ indexing §  Use multiple indexing threads/ connections §  When max mem is hit, biggest DWPT is concurrently flushed

Indexing thread Index Writer

DWPT in-memory

DWPT

DWPT

Flush segment to disk _1_0.tiv _1_0.prx _1_0.frq …

_2_0.tiv _2_0.prx _2_0.frq …

_3_0.tiv _3_0.prx _3_0.frq … 7


Solr Cloud http://.../solr/collection1?distrib=true

Load-balanced sub-request

shard1 (replica1) replica2

shard2 (replica1) replica2

replica3

replica3 ZK node

ZK node

/collections /collection1 configName=myconf /shards /shard1 server1:8983/solr server2:8983/solr /shard2 server3:8983/solr ZK server4:8983/solr

node

/livenodes server1:8983/solr server2:8983/solr server2:8983/solr

ZK node

/configs /myconf solrconfig.xml schema.xml

ZooKeeper quorum

ZK node

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Solr Cloud: Getting Started http://wiki.apache.org/solr/SolrCloud java -­‐Dbootstrap_confdir=./solr/conf -­‐Dcollection.configName=myconf -­‐DzkRun -­‐jar start.jar

Upload /solr/conf to ZK and call it “myconf”

Run an internal ZK server

http://localhost:8983/solr/collection1/admin/zookeeper.jsp


Distributed Requests l  Explicitly

specify node addresses to load-balance across

shards=localhost:8983/solr|localhost:8900/solr, localhost:7574/solr|localhost:7500/solr l  l

A list of equivalent nodes are separated by “|” Different phases of the same distributed request use the same node

l  Specify

logical shard ids to search across

shards=NY_shard,NJ_shard l  Query

across all shards in the collection

http://localhost:8983/solr/collection1/select?distrib=true l  public CloudSolrServer(String zkHost) l

SolrJ Java client that load-balances across all nodes in cluster


Extended Dismax Parser l  Superset

of dismax l  Designed to directly handle user queries w/o exceptions &defType=edismax&q=foo&qf=body l  Fixes

edge cases where dismax could still throw exceptions

OR AND NOT -­‐ l  Full l  l

lucene syntax support

Tries lucene syntax first Smart escaping is done if syntax errors

l  Optionally

supports treating and / or as AND/OR in lucene

syntax l  Fielded queries (e.g. myfield:foo) even in degraded mode l

uf parameter controls what field names may be directly specified in q


Extended Dismax Parser (continued) parameter for multiplicative boost-by-function l  Pure negative query clauses l  boost

Example: solr OR (-­‐solr) l  Enhanced

term proximity boosting

pf2=myfield – results in term bigrams in sloppy phrase queries myfield: aa bb cc -­‐> myfield: aa bb myfield: bb cc

l

l  Enhanced

stopword handling

stopwords omitted in main query, but added in optional proximity boosting part Example: q=solr is awesome & qf=myfield & pf2=myfield -­‐> +myfield:(solr awesome) (myfield: solr is myfield: is awesome ) l  Currently controlled by the absence of StopWordFilter in index analyzer, and presence in query analyzer l


Faceting Performance Improvements l  For

facet.method=enum, speed up initial population of the filterCache (i.e. first time facet): from 30% to 32x improvement l  Optimized facet.method=fc for multi-valued fields and large facet.limit – up to 3x faster l  Optimized deep facet paging – up to 10x faster with really large facet.offsets l  Less memory consumed by field cache entries l  Per-segment faceting with facet.method=fcs l  l

Only faster when re-opening index frequently (many times a second) Only works for single-valued fields


Pivot Faceting l  Other l

names that could have made sense:

Grid Faceting, Cross-Product Faceting, Matrix Faceting

l  Syntax:

facet.pivot=field1,field2,field3,…

facet.pivot=cat,inStock #docs #docs w/ inStock:true

#docs w/ instock:false

cat:electronics

14

10

4

cat:memory

3

3

0

cat:connector

2

0

2

cat:graphics card

2

0

2

cat:hard drive

2

2

0


Pivot Faceting http://...&facet=true&facet.pivot=cat,popularity "facet_counts":{ (continued) "facet_pivot":{ "cat,popularity":[{ { "field":"cat", "field":"popularity", 14 docs w/ "value":"electronics", "value":"1", cat==electronics "count":14, "count":2}]}, "pivot":[{ { "field":"popularity", "field":"cat", 5 docs w/ "value":"6", "value":"memory", cat==electronics && popularity==6 "count":5}, "count":3, { "pivot":[]}, "field":"popularity", "value":"7", […] "count":4},


Range Faceting §ď‚§â€Ż Like Date faceting, but more generic

http://...&facet=true &facet.range=price &facet.range.start=0 &facet.range.end=500 &facet.range.gap=50

"facet_counts":{ "facet_ranges":{ "price":{ "counts":{ "0.0":5, "50.0":2, "100.0":0, "150.0":2, "200.0":0, "250.0":1, "300.0":2, "350.0":2, "400.0":0, "450.0":1}, "gap":50.0, "start":0.0, "end":500.0}}}}


Spatial Search Step1: Index some locations! <field name= name >The Alpine Shop</field> <field name= store >44.013617,-73.168264</field>

Step2: Decide where you are &pt=44.0153371,-73.16734 &d=1 &sfield=store

Step3: Profit! Spatial Filter: &fq={!geofilt} Bounding Box: &fq={!bbox} Distance Function: &sort=geodist() asc Returning the distance: &fl=geodist() Pseudo-fields!

Note: You can now sort by any arbitrary function query!


Pseudo-Fields Returns other info along with document stored fields §  Function queries fl=name,location,geodist(),add(myfield,10)

§  Fieldname globs fl=id,attr_*

§  Multiple “fl” (field list) values

&fl=id,attr_*&fl=geodist()&fl=termfreq(text,’solr’)

§  Aliasing fl=id,location:loc,_dist_:geodist()

§  Future: inlined highlighting, “explain”, sort-values, group-value

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Result Grouping / Field Collapsing l  Goal

Limit the number of results per category l  category normally defined by unique values in a field l

l  Uses

Web Search – collapse by web site l  Email threads – collapse by thread id l  Ecommerce/retail l  Show the top 5 items for each store category (music, movies, etc) l


Field Collapsing by Site


Result Grouping by Category Field Collapse on Product Type


Group by Field http://...&fl=id,name&q=ipod&group=true&group.field=manu_exact "grouped":{ "manu_exact":{ "matches":3, "groups":[{ "groupValue":"Belkin", "doclist":{"numFound":2,"start":0,"docs":[ { "id":"IW-02", "name":"iPod & iPod Mini USB 2.0 Cable"}] }}, { "groupValue":"Apple Computer Inc.", "doclist":{"numFound":1,"start":0,"docs":[ {


Group by Query http://...&group=true&group.query=price:[0 TO 99.99] &group.query=price:[100 TO *]&group.limit=5 "grouped":{ "price:[0 TO 99.99]":{ "matches":3, "doclist":{"numFound":2,"start":0,"docs":[ { "id":"IW-02", "name":"iPod & iPod Mini USB 2.0 Cable"}, { "id":"F8V7067-APL-KIT", "name":"Belkin Mobile Power Cord for iPod"}] }}, "price:[100 TO *]":{ "matches":3, "doclist":{"numFound":1,"start":0,"docs":[


Grouping Params parameter

meaning

group.field=<field>

Like facet.field – group by unique field values

group.query=<query>

Like facet.query – top docs that also match

default

group.function=<function Group by unique values produced by the query> function query group.limit=<n>

How many docs per group

1

group.sort=<sort spec>

How to sort documents within a group

Same as sort

rows=<n>

How many groups to return

10

sort=<sort spec>

How to sort the groups relative to each other (based on top doc)

group.format=<format>

grouped/simple – if simple, a single flat list is used and rows units are “docs”

group.main=true/false

If true, the first field grouping command is false used as main result set

grouped


Pseudo-Join id: blog1 name: Solr ‘n Stuff owner: Yonik Seeley Started: 2007-10-26

id: post1 blog_id: blog1 author: Yonik Seeley title: Solr relevancy function queries body: Lucene’s default ranking […]

id: blog2 name: lifehacker owner: Gawker Media started: 2005-1-31

id: post2 blog_id: blog1 author: Yonik Seeley title: Solr result grouping body: Result Grouping, also called […]

Restrict to blogs mentioning netflix fq={!join from=blog_id to=id}body:netflix

id: post3 blog_id: blog2 author: Whitson Gordon title: How to Install Netflix on Almost Any Android Device

-  Finds all documents matching “netflix” -  Maps to different docs by following blog_id to id 25


Pseudo-Join Examples §  Only show posts from blogs started after 2010 q=foo&fq={!join from=id to=blog_id}started:[2010 TO *]

§  If any post in a blog mentions “obama”, then search all posts in that blog for “bomb” (self-join) q=bomb&fq={!join from=blog_id to=blog_id}obama

§  If any blog post mentions “obama”, then search all websites with the same blog owner for “bomb” q=bomb&fq={!join from=owner to=website_owner}{!join from=blog_id to=id}obama 26


Cross-Core Join id: doc1 security: managers title: doc for managers only body: ‌

id: mary security_groups: managers, employees

id: doc1 security: managers, employees title: doc for everyone body: ‌

id: john security_groups: employees

sec1

collection1 Single Solr Server

http://localhost:8983/solr/collection1/select?q=foo&fq={!join fromIndex=sec1 from=security_groups to=security}user:john 27


Pseudo-Join vs Grouping Pseudo-Join

Result Grouping / Field Collapsing

O(n_terms_in_join_fields)

O(n_docs_in_result)

Single or multi-valued fields

Single-valued fields only

Filters only (no info currently passed from the “from” docs to the “to” docs).

Can order docs within a group and groups by top doc within that group using normal sort criteria.

Chainable (one join can be the input to another)

Not currently chainable – can only group one field deep

Affects which documents match a request, so naturally affects facet numbers (e.g. you can search posts and get numbers of blogs)

Grouping does not currently affect the set of documents matching the query, so faceting is unaffected.

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Auto-Suggest l  Many l

Can be slow for a large corpus

l  New l  l  l

people previously used terms component

auto-suggest builds off SpellCheck component

TST implementation: compact memory based trie FST implementation: slower to build, but smaller & faster lookup Based on a field in the main index, or on a dictionary file

http://localhost:8983/solr/suggest?wt=json&indent=true&q=ult

"spellcheck":{ "suggestions":[ "ult",{ "numFound":1, "startOffset":0, "endOffset":3, "suggestion":["ultrasharp"]}, "collation","ultrasharp"]}}

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Index with JSON $ URL=http://localhost:8983/solr/update/json $ curl $URL -­‐H 'Content-­‐type:application/json' -­‐d ’ [ { "id" : "978-­‐0641723445", "cat" : ["book","hardcover"], "title" : "The Lightning Thief", "author" : "Rick Riordan", "series_t" : "Percy Jackson and the Olympians", "sequence_i" : 1, "genre_s" : "fantasy", "inStock" : true, "price" : 12.50, "pages_i" : 384 } ]'


Query Results in CSV http://localhost:8983/solr/select?q=ipod&fl=name,price,cat,popularity&wt=csv name,price,cat,popularity iPod & iPod Mini USB 2.0 Cable,11.5,"electronics,connector",1 Belkin Mobile Power Cord for iPod w/ Dock,19.95,"electronics,connector",1 Apple 60 GB iPod with Video Playback Black,399.0,"electronics,music",10 Can handle multi-valued fields (see cat field in example) l  Completely compatible with the CSV update handler (can round-trip) l  Results are streamed – good for dumping entire parts of the index l


http://localhost:8983/solr/browse


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