This document provides a summary of the Solr search platform. It begins with introductions from the presenter and about Lucid Imagination. It then discusses what Solr is, how it works, who uses it, and its main features. The rest of the document dives deeper into topics like how Solr is configured, how to index and search data, and how to debug and customize Solr implementations. It promotes downloading and experimenting with Solr to learn more.

1. Introduction
to
Solr
NFJS - Boston, September 2011
Presented by Erik Hatcher
erik.hatcher@lucidimagination.com
Lucid Imagination
http://www.lucidimagination.com

2. About me...
• Co-author, "Lucene in Action" (and "Java
Development with Ant" / "Ant in Action"
once upon a time)
• "Apache guy" - Lucene/Solr committer;
member of Lucene PMC, member of
Apache Software Foundation
• Co-founder, evangelist, trainer, coder @
Lucid Imagination

3. About Lucid Imagination...
• Lucid Imagination provides commercial-grade
support, training, high-level consulting and value-
added software for Lucene and Solr.
• We make Lucene ‘enterprise-ready’ by offering:
• Free, certified, distributions and downloads.
• Support, training, and consulting.
• LucidWorks Enterprise, a commercial search
platform built on top of Solr.

4. Abstract
Apache Solr serves search requests at the enterprises and
the largest companies around the world. Built on top of the
top-notch Apache Lucene library, Solr makes indexing and
searching integration into your applications straightforward.
Solr provides faceted navigation, spell checking, highlighting,
clustering, grouping, and other search features. Solr also
scales query volume with replication and collection size
with distributed capabilities. Solr can index rich documents
such as PDF, Word, HTML, and other file types.

5. What is Solr?
• An open source search server
• Indexes content sources, processes query requests, returns
search results
• Uses Lucene as the "engine", but adds full enterprise search
server features and capabilities
• A web-based application that processes HTTP requests and
returns HTTP responses.
• Initially started in 2004 and developed by CNET as an in-house
project to add search capability for the company website.
• Donated to ASF in 2006.

6. Who uses Solr?
And many many many many more...!

7. Which Solr version?
• There’s more than one answer!
• The current, released, stable version is 3.3
(soon to be 3.4)
• The development release is referred to as “trunk”.
• This is where the new, less tested work goes on
• Also referred to as 4.0
• LucidWorks Enterprise is built on a trunk snapshot
+ additional features.

8. What is Lucene?
• An open source search library (not an application)
• 100% Java
• Continuously improved and tuned for more than 10
years
• Compact, portable index representation
• Programmable text analyzers, spell checking and
highlighting
• Not, itself, a crawler or a text extraction tool

9. Inverted Index
• Lucene stores input data in what is known as an
inverted index
• In an inverted index each indexed term points to a
list of documents that contain the term
• Similar to the index provided at the end of a book
• In this case "inverted" simply means the list of terms
point to documents
• It is much faster to find a term in an index, than to
scan all the documents

10. Inverted Index Example

11. Ingestion
• API / Solr XML, JSON, and javabin/SolrJ
• CSV
• Relational databases
• File system
• Web crawl (using Nutch, or others)
• Others - XML feeds (e.g. RSS/Atom), e-mail

12. Solr indexing options

13. Solr XML
POST to /update
<add>
<doc>
<field name="id">rawxml1</field>
<field name="content_type">text/xml</field>
<field name="category">index example</field>
<field name="title">Simple Example</field>
<field name="filename">addExample.xml</field>
<field name="text">A very simple example of
adding a document to the index.</field>
</doc>
</add>

14. Solr JSON
POST to /update/json
[
{"id" : "TestDoc1", "title" : "test1"},
{"id" : "TestDoc2", "title" : "another test"}
]

15. CSV indexing
• http://localhost:8983/solr/update/csv
• Files can be sent over HTTP:
• curl http://localhost:8983/solr/update/
csv --data-binary @data.csv -H 'Content-
type:text/plain; charset=utf-8’
• or streamed from the file system:
• curl http://localhost:8983/solr/update/
csv?stream.file=exampledocs/
data.csv&stream.contentType=text/
plain;charset=utf-8

16. Rich documents
• Solr uses Tika for extraction. Tika is a toolkit for detecting and
extracting metadata and structured text content from various
document formats using existing parser libraries.
• Tika identifies MIME types and then uses the appropriate parser
to extract text.
• The ExtractingRequestHandler uses Tika to identify types and
extract text, and then indexes the extracted text.
• The ExtractingRequestHandler is sometimes called "Solr Cell",
which stands for Content Extraction Library.
• File formats include MS Office, Adobe PDF, XML, HTML, MPEG
and many more.

17. Solr Cell parameters
• The literal parameter is very important.
• A way to add other fields not indexed using Tika to documents.
• &literal.id=12345
• &literal.category=sports
• Using curl to index a file on the file system:
• curl 'http://localhost:8983/solr/update/extract?
literal.id=doc1&commit=true' -F
myfile=@tutorial.html
• Streaming a file from the file system:
• curl "http://localhost:8983/solr/update/extract?
stream.file=/some/path/
news.doc&stream.contentType=application/
msword&literal.id=12345"

18. Streaming remote docs
• Streaming a file from a URL:
• curl http://localhost:8983/solr/
update/extract?
literal.id=123&stream.url=http://
www.solr.com/content/file.pdf -H
'Content-type:application/pdf’

19. DataImportHandler
• An "in-process" module that can be used to index data directly
from relational databases and other data sources
• Configuration driven
• A tool that can aggregate data from multiple database tables, or
even multiple data sources to be indexed as a single Solr
document
• Provides powerful and customizable data transformation tools
• Can do full import or delta import
• Pluggable to allow indexing of any type of data source

20. DIH Examples
• Rich documents
• Relational database
• E-mail

21. Other commands
• <commit/> and <optimize/>
• <delete>...</delete>
• <id>Q-36</id>
• <query>category:electronics</query>
• To update a document, simply add a
document with same unique key

22. Configuring Solr
• schema.xml
• defines field types, fields, and unique key
• solrconfig.xml
• Lucene settings
• request handler, component, and plugin
definitions and customizations

23. Searching Basics
• http://localhost:8983/solr/select?q=*:*
• q - main query
• rows - maximum number of "hits" to return
• start - zero-based hit starting point
• fl - comma-separated field list
• * for all stored fields, score for computed
Lucene score

24. Other Common Search
Parameters
• sort - specify sort criteria either by field(s)
or function(s) in ascending or descending
order
• fq - filter queries, multiple values supported
• wt - writer type - format of Solr response
• debugQuery - adds debugging info to
response

25. Filtering results
• Use fq to filter results in addition to main
query constraints
• fq results are independently cached in Solr's
filterCache
• filter queries do not contribute to ranking
scores
• Commonly used for filtering on facets

26. Typical Solr Request
• http://localhost:8983/solr/select
?q=ipod
&facet=on
&facet.field=cat
&fq=cat:electronics

27. Features
• Faceting • Distributed search
• Highlighting • Replication
• Spellchecking • Suggest
• More-like-this • Geospatial support
• Clustering • UIMA integration
• Grouping • Extensible

28. Integration
• It's just HTTP
• and CSV, JSON, XML, etc on the requests
and responses
• Any language or environment can work
with Solr easily
• Many libraries/layers exist on top

29. Ruby indexing example

30. SolrJ searching example
SolrServer solrServer = new CommonsHttpSolrServer(
"http://localhost:8983/solr");
SolrQuery query = new SolrQuery();
query.setQuery(userQuery);
query.setFacet(true);
query.setFacetMinCount(1);
query.addFacetField("category");
QueryResponse queryResponse = solrServer.query(query);

31. Devilish Details
• analysis: tokenization and token filtering
• query parsing
• relevancy tuning
• performance and scalability

32. SolrMeter
http://code.google.com/p/solrmeter/

33. e.g. data.gov

34. Data.gov CSV catalog
URL,Title,Agency,Subagency,Category,Date Released,Date Updated,Time
Period,Frequency,Description,Data.gov Data Category Type,Specialized Data Category
Designation,Keywords,Citation,Agency Program Page,Agency Data Series Page,Unit of
Analysis,Granularity,Geographic Coverage,Collection Mode,Data Collection
Instrument,Data Dictionary/Variable List,Applicable Agency Information Quality
Guideline Designation,Data Quality Certification,Privacy and Confidentiality,Technical
Documentation,Additional Metadata,FGDC Compliance (Geospatial Only),Statistical
Methodology,Sampling,Estimation,Weighting,Disclosure Avoidance,Questionnaire
Design,Series Breaks,Non-response Adjustment,Seasonal Adjustment,Statistical
Characteristics,Feeds Access Point,Feeds File Size,XML Access Point,XML File Size,CSV/
TXT Access Point,CSV/TXT File Size,XLS Access Point,XLS File Size,KML/KMZ Access
Point,KML File Size,ESRI Access Point,ESRI File Size,Map Access Point,Data Extraction
Access Point,Widget Access Point
"http://www.data.gov/details/4","Next Generation Radar (NEXRAD) Locations","Department of Commerce","National Oceanic
and Atmospheric Administration","Geography and Environment","1991","Irregular as needed","1991 to present","Between 4
and 10 minutes","This geospatial rendering of weather radar sites gives access to an historical archive of Terminal
Doppler Weather Radar data and is used primarily for research purposes. The archived data includes base data and
derived products of the National Weather Service (NWS) Weather Surveillance Radar 88 Doppler (WSR-88D) next generation
(NEXRAD) weather radar. Weather radar detects the three meteorological base data quantities: reflectivity, mean radial
velocity, and spectrum width. From these quantities, computer processing generates numerous meteorological analysis
products for forecasts, archiving and dissemination. There are 159 operational NEXRAD radar systems deployed
throughout the United States and at selected overseas locations. At the Radar Operations Center (ROC) in Norman OK,
personnel from the NWS, Air Force, Navy, and FAA use this distributed weather radar system to collect the data needed
to warn of impending severe weather and possible flash floods; support air traffic safety and assist in the management
of air traffic flow control; facilitate resource protection at military bases; and optimize the management of water,
agriculture, forest, and snow removal. This data set is jointly owned by the National Oceanic and Atmospheric
Administration, Federal Aviation Administration, and Department of Defense.","Raw Data Catalog",...

36. Debugging
http://localhost:8983/solr/data.gov?q=searching&debugQuery=true

37. Custom pages
• Document detail page
• Multiple query intersection comparison
with Venn visualization

38. Document detail
http://localhost:8983/solr/data.gov/document
?id=http%3A%2F%2Fwww.data.gov%2Fdetails%2F61

39. Query intersection
• Just showing off.... how easy it is to do
something with a bit of visual impact
• Compare three independent queries,
intersecting them in a Venn diagram
visualization

41. What now?
• Download Solr
• "install" it (unzip it)
• Start Solr: java -jar start.jar
• Ingest your data
• Iterate on schema & config
• Ship It!

42. UI / prototyping
• Solritas - aka VelocityResponseWriter
• Blacklight - projectblacklight.org

43. Blacklight @ UVa

44. Blacklight @ Stanford

45. For more information...
• http://www.lucidimagination.com
• LucidFind
• search Lucene ecosystem: mailing lists, wikis, JIRA, etc
• http://search.lucidimagination.com
• Getting started with LucidWorks Enterprise:
• http://www.lucidimagination.com/products/
lucidworks-search-platform/enterprise
• http://lucene.apache.org/solr - wiki, e-mail lists

46. LucidFind
http://www.lucidimagination.com/search/?q=user+interface

47. Thank You!