add powerful full text search to your web app with solr

Powerful Full-Text Search with Solr

Yonik Seeleyyonik@apache.org

Web 2.0 Expo, Berlin8 November 2007

download athttp://www.apache.org/~yonik

What is Lucene• High performance, scalable, full-text

search library• Focus: Indexing + Searching Documents

– “Document” is just a list of name+value pairs• No crawlers or document parsing• Flexible Text Analysis (tokenizers + token

filters)• 100% Java, no dependencies, no config

files

What is Solr• A full text search server based on Lucene• XML/HTTP, JSON Interfaces• Faceted Search (category counting)• Flexible data schema to define types and fields• Hit Highlighting• Configurable Advanced Caching• Index Replication• Extensible Open Architecture, Plugins• Web Administration Interface• Written in Java5, deployable as a WAR

admin update select

Standard request handler

Custom request handler

XML response writer

JSON response writer

XML Update Handler

CSV Update Handler

Lucene

Basic App

Documentsuper_name: Mr. Fantasticname: Reed Richardscategory: superheropowers: elasticity

Query Response(matching docs)

Query(powers:agility)

http://solr/update http://solr/select

Ser

vlet

Con

tain

er Solr

HTML

WebappIndexer

Indexing Data

HTTP POST to http://localhost:8983/solr/update

<add><doc><field name=“id”>05991</field><field name=“name”>Peter Parker</field><field name=“supername”>Spider-Man</field><field name=“category”>superhero</field><field name=“powers”>agility</field><field name=“powers”>spider-sense</field>

</doc></add>

Indexing CSV data

Iron Man, Tony Stark, superhero, powered armor | flightSandman, William Baker|Flint Marko, supervillain, sand transformWolverine,James Howlett|Logan, superhero, healing|adamantiumMagneto, Erik Lehnsherr, supervillain, magnetism|electricity

http://localhost:8983/solr/update/csv?fieldnames=supername,name,category,powers&separator=,&f.name.split=true&f.name.separator=|&f.powers.split=true&f.powers.separator=|

Data upload methodsURL=http://localhost:8983/solr/update/csv

• HTTP POST body (curl, HttpClient, etc)curl $URL -H 'Content-type:text/plain; charset=utf-8' --data-binary @info.csv

• Multi-part file upload (browsers)• Request parameter?stream.body=‘Cyclops, Scott Summers,…’

• Streaming from URL (must enable)?stream.url=file://data/info.csv

Indexing with SolrJ// Solr’s Java Client API… remote or embedded/local!SolrServer server = new

CommonsHttpSolrServer("http://localhost:8983/solr");

SolrInputDocument doc = new SolrInputDocument();doc.addField("supername","Daredevil");doc.addField("name","Matt Murdock");doc.addField(“category",“superhero");

server.add(doc);server.commit();

Deleting Documents• Delete by Id, most efficient<delete><id>05591</id><id>32552</id>

</delete>

• Delete by Query<delete><query>category:supervillain</query>

</delete>

Commit• <commit/> makes changes visible

– Triggers static cache warming in solrconfig.xml

– Triggers autowarming from existing caches• <optimize/> same as commit, merges all

index segments for faster searching_0.fnm_0.fdt_0.fdx_0.frq_0.tis_0.tii_0.prx_0.nrm

_0_1.del

_1.fnm_1.fdt_1.fdx[…]

Lucene Index Segments

Searchinghttp://localhost:8983/solr/select?q=powers:agility

&start=0&rows=2&fl=supername,category

<response><result numFound=“427" start="0"><doc> <str name=“supername">Spider-Man</str><str name=“category”>superhero</str>

</doc> <doc> <str name=“supername">Msytique</str><str name=“category”>supervillain</str>

</doc></result>

</response>

Response Format• Add &wt=json for JSON formatted response

{“result": {"numFound":427, "start":0,"docs": [

{“supername”:”Spider-Man”, “category”:”superhero”},{“supername”:” Msytique”, “category”:” supervillain”}

]}

• Also Python, Ruby, PHP, SerializedPHP, XSLT

Scoring• Query results are sorted by score descending• VSM – Vector Space Model• tf – term frequency: numer of matching terms in field• lengthNorm – number of tokens in field• idf – inverse document frequency• coord – coordination factor, number of matching

terms• document boost• query clause boost

http://lucene.apache.org/java/docs/scoring.html

Explainhttp://solr/select?q=super fast&indent=on&debugQuery=on

<lst name="debug"><lst name="explain"><str name="id=Flash,internal_docid=6">

0.16389132 = (MATCH) product of:0.32778263 = (MATCH) sum of:0.32778263 = (MATCH) weight(text:fast in 6), product of:0.5012072 = queryWeight(text:fast), product of:2.466337 = idf(docFreq=5)0.20321926 = queryNorm

0.65398633 = (MATCH) fieldWeight(text:fast in 6), product of:1.4142135 = tf(termFreq(text:fast)=2)2.466337 = idf(docFreq=5)0.1875 = fieldNorm(field=fast, doc=6)

0.5 = coord(1/2)</str><str name="id=Superman,internal_docid=7">

0.1365761 = (MATCH) product of:

Lucene Query Syntax1. justice league

• Equiv: justice OR league• QueryParser default operator is “OR”/optional

2. +justice +league –name:aquaman• Equiv: justice AND league NOT name:aquaman

3. “justice league” –name:aquaman4. title:spiderman^10 description:spiderman5. description:“spiderman movie”~100

Lucene Query Examples21. releaseDate:[2000 TO 2007]2. Wildcard searches: sup?r, su*r, super*3. spider~

• Fuzzy search: Levenshtein distance• Optional minimum similarity: spider~0.7

4. *:*5. (Superman AND “Lex Luthor”) OR

(+Batman +Joker)

DisMax Query Syntax• Good for handling raw user queries

– Balanced quotes for phrase query– ‘+’ for required, ‘-’ for prohibited– Separates query terms from query structure

http://solr/select?qt=dismax&q=super man // the user query&qf=title^3 subject^2 body // field to query&pf=title^2,body // fields to do phrase queries&ps=100 // slop for those phrase q’s&tie=.1 // multi-field match reward&mm=2 // # of terms that should match &bf=popularity // boost function

DisMax Query Form• The expanded Lucene Query:

+( DisjunctionMaxQuery( title:super^3 | subject:super^2 | body:super)DisjunctionMaxQuery( title:man^3 | subject:man^2 | body:man)

)DisjunctionMaxQuery(title:”super man”~100^2

body:”super man”~100)FunctionQuery(popularity)

• Tip: set up your own request handler with default parameters to avoid clients having to specify them

Function Query

• Allows adding function of field value to score– Boost recently added or popular documents

• Current parser only supports function notation• Example: log(sum(popularity,1))• sum, product, div, log, sqrt, abs, pow• scale(x, target_min, target_max)

– calculates min & max of x across all docs• map(x, min, max, target)

– useful for dealing with defaults

Boosted Query

• Score is multiplied instead of added– New local params <!...> syntax added

&q=<!boost b=sqrt(popularity)>super man

• Parameter dereferencing in local params&q=<!boost b=$boost v=$userq>&boost=sqrt(popularity)&userq=super man

Analysis & Search Relevancy

LexCorp BFG-9000

LexCorp BFG-9000

BFG 9000Lex Corp

LexCorp

bfg 9000lex corp

lexcorp

WhitespaceTokenizer

WordDelimiterFilter catenateWords=1

LowercaseFilter

Lex corp bfg9000

Lex bfg9000

bfg 9000Lex corp

bfg 9000lex corp

WhitespaceTokenizer

WordDelimiterFilter catenateWords=0

LowercaseFilter

Query Analysis

A Match!

Document Indexing Analysis

corp

Configuring Relevancy<fieldType name="text" class="solr.TextField"><analyzer><tokenizer class="solr.WhitespaceTokenizerFactory"/><filter class="solr.LowerCaseFilterFactory"/><filter class="solr.SynonymFilterFactory"

synonyms="synonyms.txt“/><filter class="solr.StopFilterFactory“

words=“stopwords.txt”/><filter class="solr.EnglishPorterFilterFactory"

protected="protwords.txt"/></analyzer>

</fieldType>

Field Definitions• Field Attributes: name, type, indexed, stored,

multiValued, omitNorms, termVectors

<field name="id“ type="string" indexed="true" stored="true"/><field name="sku“ type="textTight” indexed="true" stored="true"/><field name="name“ type="text“ indexed="true" stored="true"/><field name=“inStock“ type=“boolean“ indexed="true“ stored=“false"/><field name=“price“ type=“sfloat“ indexed="true“ stored=“false"/><field name="category“ type="text_ws“ indexed="true" stored="true“

multiValued="true"/>

• Dynamic Fields

<dynamicField name="*_i" type="sint“ indexed="true" stored="true"/><dynamicField name="*_s" type="string“ indexed="true" stored="true"/><dynamicField name="*_t" type="text“ indexed="true" stored="true"/>

copyField• Copies one field to another at index time• Usecase #1: Analyze same field different ways

– copy into a field with a different analyzer– boost exact-case, exact-punctuation matches– language translations, thesaurus, soundex

<field name=“title” type=“text”/><field name=“title_exact” type=“text_exact”

stored=“false”/><copyField source=“title” dest=“title_exact”/>

• Usecase #2: Index multiple fields into single searchable field

Facet Queryhttp://solr/select?q=foo&wt=json&indent=on&facet=true&facet.field=cat&facet.query=price:[0 TO 100]&facet.query=manu:IBM

{"response":{"numFound":26,"start":0,"docs":[…]},“facet_counts":{

"facet_queries":{ "price:[0 TO 100]":6,“manu:IBM":2},

"facet_fields":{ "cat":[ "electronics",14, "memory",3,

"card",2, "connector",2]}}}

Filters• Filters are restrictions in addition to the query• Use in faceting to narrow the results• Filters are cached separately for speed

1. User queries for memory, query sent to solr is&q=memory&fq=inStock:true&facet=true&…

2. User selects 1GB memory size&q=memory&fq=inStock:true&fq=size:1GB&…

3. User selects DDR2 memory type&q=memory&fq=inStock:true&fq=size:1GB

&fq=type:DDR2&…

Highlightinghttp://solr/select?q=lcd&wt=json&indent=on&hl=true&hl.fl=features

{"response":{"numFound":5,"start":0,"docs":[ {"id":"3007WFP", “price”:899.95}, …]

"highlighting":{"3007WFP":{ "features":["30\" TFT active matrix <em>LCD</em>, 2560 x 1600”

"VA902B":{ "features":["19\" TFT active matrix <em>LCD</em>, 8ms response time, 1280 x 1024 native resolution"]}}}

MoreLikeThis• Selects documents that are “similar” to the

documents matching the main query.&q=id:6H500F0

&mlt=true&mlt.fl=name,cat,features"moreLikeThis":{

"6H500F0":{"numFound":5,"start":0,"docs”: [

{"name":"Apple 60 GB iPod with Video Playback Black", "price":399.0,

"inStock":true, "popularity":10, […]}, […]

][…]

High Availability

Load Balancer

Appservers

Solr Searchers

Solr Master

DBUpdaterupdates

updatesadmin queries

Index Replication

admin terminal

HTTP search requests

Dynamic HTML Generation

Resources• WWW

– http://lucene.apache.org/solr– http://lucene.apache.org/solr/tutorial.html– http://wiki.apache.org/solr/

• Mailing Lists– solr-user-subscribe@lucene.apache.org– solr-dev-subscribe@lucene.apache.org