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

3. Uses Apache Lucene as text search engine

4. Inverted Index Data Structure November, 30 2010

5. Common Usage November, 30 2010

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

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

23. CSV, JSON

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

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

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

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

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>

36. Query elevation

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

38. The more-like-this search

40. HTTP caching

42. Shards

43. Scaling – whole picture November, 30 2010