The document discusses the features and capabilities of Solr, an open source enterprise search platform built on Apache Lucene. It describes how Solr allows indexing and querying of documents through HTTP requests, provides caching and a web admin interface, and supports advanced search features like highlighting, spellchecking, and more-like-this queries. The document also covers how to scale Solr through techniques like optimizing a single server, splitting data by document type, and using a distributed sharding approach.

1. PRESENTATION Solr Enterprise Search Server by Armen Polischuk

2. Introduction Java Web Application (Http/XML)

3. Uses Apache Lucene as text search engine

4. Inverted Index Data Structure November, 30 2010

5. Common Usage November, 30 2010

6. Lucene Features November, 30 2010 A text-based inverted index persistent storage for efficient retrieval of

7. documents by indexed terms

8. A rich set of text analyzers to transform a string of text into a series of terms (words), which are the fundamental units indexed and searched

9. A query syntax with a parser and a variety of query types

10. Lookup to exotic fuzzy matches

11. A good scoring algorithm based on sound Information Retrieval (IR)

12. principles to produce the more likely candidates first, with flexible means

13. to affect the scoring

14. A highlighter feature to show words found in context A query spellchecker based on indexed content

15. Solr Features November, 30 2010 HTTP request processing for indexing and querying documents

16. Several caches for faster query responses

17. A web-based administrative interface

18. Configuration files for the schema and the server itself

19. The disjunction-max query handler

20. A more like this plugin to list documents that are similar to a chosen document

21. A distributed Solr server model

22. Indexing Data November, 30 2010 Solr's native XML

23. CSV, JSON

24. Direct Database and XML Import through Solr's DataImportHandler

25. Rich documents through Solr Cell (pdf, doc, xls, ppt)

26. Indexing XML Request November, 30 2010 <add allowDups = &quot;false&quot; > <doc boost = &quot;2.0&quot; > <field name = &quot;doc_id&quot; > 1 </field> <field name = &quot;type&quot; > PERSON </field> <field name = &quot;first_name&quot; boost = &quot;2.5&quot; > Armen </field> <field name = &quot;last_name&quot; > Polischuk </field> </doc> <doc> <field name = &quot;doc_id&quot; > 2 </field>

27. <field name = &quot;type&quot; > PERSON </field>

28. <field name = &quot;first_name&quot; > John </field>

29. <field name = &quot;last_name&quot; > Smith </field> </doc> </add> Adding documents: Deleting documents: <delete><id> doc_id:2 </id><id> doc_id:3 </id></delete>

30. Basic Searching November, 30 2010 Using Web Interface

31. Using http request/response

32. Using SolrJ client http://localhost:8983/solr/select?indent=on&version=2.2&q=*%3A*&start=0&rows=10&fl=*%2Cscore&qt=standard&wt=standard&explainOther=&hl.fl= Example:

33. Searching XML Response November, 30 2010 <response> <lst name = &quot;responseHeader&quot; > <int name = &quot;status&quot; > 0 </int> <int name = &quot;QTime&quot; > 392 </int> <lst name = &quot;params&quot; > <str name = &quot;explainOther&quot; /> <str name = &quot;fl&quot; > *,score </str> <str name = &quot;start&quot; > 0 </str> <str name = &quot;q&quot; > *:* </str> <str name = &quot;hl.fl&quot; /> </lst> </lst> <result name = &quot;response&quot; numFound = &quot;1002272&quot; start = &quot;0&quot; maxScore = &quot;1.0&quot; > <doc> <float name = &quot;score&quot; > 1.0 </float> <str name = &quot;id&quot; > PERSON:1 </str> <str name = &quot;first_name&quot; > Armen </str> <str name = &quot;last_name&quot; > Polischuk </str> </doc> </result> </response>

34. Features November, 30 2010 And, or, not: Java AND Developer NOT swing (Java OR Python) AND Developer Field qualifier: first_name:John AND last_name:Doe Phrase and term proximity “ Web Developer” “ Web Developer”~3 Wildcards Java* AND Developer Boosting Java^10 AND Web^5 AND Developer Filtering and sorting q=Java&fq=type%3APERSON&sort=score+asc

35. Advanced Features November, 30 2010 Highlighting

36. Query elevation

37. Spell checking aka “Did you mean...”

38. The more-like-this search

39. Scaling - approaches November, 30 2010 Optimizing a single Solr server JVM params

40. HTTP caching

41. Solr caching Split data by doc type Scale Wide

42. Shards

43. Scaling – whole picture November, 30 2010

44. Documentation November, 30 2010 http://wiki.apache.org/lucene-java/FrontPage http://wiki.apache.org/solr/FrontPage