Add Powerful Full Text Search to Your Web App with Solr
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Powerful Full-Text Search with Solr
Yonik [email protected]
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– [email protected]– [email protected]