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![Feature comparison ESP – Solr (differences)
Feature ESP Solr
Lemmatization Can be licensed Can be licensed
for many from 3rd party
languages
Query syntax and(a:foo, b:bar) a:foo OR b:bar
i:range(0, 100) I:[0 TO 100]
d:range(2000-01- d:[2000-01-
01T00:00:00, 01T00:00:00Z TO
2010-03- NOW]
03T12:00:00)
Query params query= q=
offset= start=
hits= rows=
spell=1 spellcheck=true
What fields to return view=viewname fl=title,price,body...
cominvent as](https://image.slidesharecdn.com/migratingfast-solr-100305142819-phpapp01/85/Migrating-Fast-to-Solr-23-320.jpg)
![Push Feeding example
– Feed XML using HTTP POST:
• curl http://localhost:8080/solr/update?commit=true
-H "Content-Type: text/xml"
--data-binary @mydoc.xml
– Ruby example:
• >gem sources -a http://gemcutter.org
>sudo gem install rsolr
require 'rsolr'
solr = RSolr.connect :url=>'http://localhost:8080'
documents = [{:id=>1, :price=>1.00},
{:id=>2, :price=>10.50}]
solr.add documents
solr.commit
cominvent as](https://image.slidesharecdn.com/migratingfast-solr-100305142819-phpapp01/85/Migrating-Fast-to-Solr-29-320.jpg)
![Querying examples
– http://localhost:8080/solr/select?q=car&fl=id,title
– Ruby
• res=solr.select :q=>'roses', :fq=>['red','white']
res['response']['docs'].each do |doc|
puts doc['title']
end
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Migrating Fast to Solr
This document discusses migrating from Microsoft FAST to Apache Solr. It provides an overview of the migration process and key steps to consider, such as mapping the FAST index profile to the Solr schema, migrating content by feeding it into Solr, and options for migrating document processing and the search middleware. It also addresses operational concerns and provides additional resources for learning more about Solr.
More Related Content
Migrating Fast to Solr
- 1. cominvent as Enterprise Search Specialists Migrating FAST to Solr by Jan Høydahl cominvent as
- 2.
- 3. Consulting – Cominvent delivers independent search consulting – Focus on Apache Lucene/Solr & Microsoft FAST ESP – We know both the proprietary and Open Source worlds, their benefits and disadvantages. We help you choose. We help you maximize your chosen engine, and we help you migrate as your requirements change. cominvent as
- 4. Training – Cominvent AS delivers training public and on-site – Certified Solr Training Partner for Lucid Imagination – Certified FAST ESP Training Partner – Read more: http://www.cominvent.com/training/ cominvent as Photo: fluidpowerzone.com
- 5. Commercial Support – When community & mailing list support is not enough.. – Paid support agreement for Apache Solr/Lucene – In cooperation with Lucid Imagination – Read more: http://www.cominvent.com/support/ cominvent as
- 6. Jan Høydahl –experience ● IT architect, 15 years with search, telecom, mobile ● Helped build FAST's Global Services as first engineer ● Founder of Cominvent AS ● Search consultant 10 years ● Certified Solr instructor cominvent as
- 7. Recommendations «His skills on Fast ESP is in-depth, thorough, and probably amongst the best you can get. Jan is working independently, but also well in teams. Whether it is technical or business work, Jan does not fall behind. His excellent skills to see things from the holistic perspective is great.» -Knut Stenmark, DPM AS cominvent as
- 8. Sample consulting projects World wide news agency Chief architect of FAST ESP search solution, migrating from Autonomy IDOL. Real-time news, alerting etc. Major Swedish newspaper Architect for new Topic Page solution, letting editors define topics based on keywords and regex rules. Norwegian Yellow Pages actor Architect for migrating traditional DB backed catalog search to modern one- search box solution. Classifieds and real estate online broker Advise on migrating from DB to search. Architect for FAST ESP solution with Norwegian linguistics, search middleware and relevance tuning. Leading news surveillance company Helped implement and tune real-time search using FAST ESP and real-time alerting using FAST RTA. cominvent as
- 9. Sample Solr Trainingreferences Library organization – Danish national library – Global library org, organization serving all serving hundreds of Danish libraries libraries world wide – Migrating from in-house – Helping them migrate search to Apache Solr for from FAST to Solr all their search – First step is Classroom – Delivered Solr training Training in March 2010 course in 2010 cominvent as
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- 11. About Apache Solr – Open Source enterprise search server – Built on the popular Apache Lucene library – 100% Java, runs on all platforms and env. – Supports billions of documents, high scalability and advanced features like faceting, highlighting, document format conversions, GEO search etc – Indexes most languages including CJK – Platform not language aware, but each field can be configured to language specific tokenization, stemming, stop word processing etc – Very active developer and user communities – Apache 2.0 license – commercially friendly – Rapid growth in companies providing support etc cominvent as
- 12. Solr-user community growth Solr-user growth 1600 1400 1200 1000 Messages 800 Column B 600 400 200 0 2006 Mar 2006 Jul 2006 Nov 2007 Mar 2007 Jul 2007 Nov 2008 Mar 2008 Jul 2008 Nov 2009 Apr 2009 Aug 2009 Dec 2006 Jan 2006 May 2006 Sep 2007 Jan 2007 May 2007 Sep 2008 Jan 2008 May 2008 Sep 2009 Feb 2009 Jun 2009 Oct 2010 Feb cominvent as Month
- 13. Lucene/Solr deployments – More: http://wiki.apache.org/solr/PublicServers cominvent as Thanks to Lucid Imagination for logo collection
- 14. Solr in media& newspapers – News search. Also exposes API – Danish news search – Swedish news search – Swedish news search – Faceted search through classifieds – Eastern european classifieds cominvent as
- 15. Sample FAST-Solr switchers – Human Rights search • hurisearch.org (blog) – FINN katalog (former Sesam) • katalog.finn.no (announce) – Mocality – African business search • mocality.co.ke (linkedin) – International library search • Large multi-lingual index – Norwegian media house cominvent as • Multiple newspapers
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- 18. Migration objectives – Possible objectives include: • Lower maintenance cost • Deeper in-house competency • Less dependent on external consultants • Ownership and visibility of source code • Shorter time to market for new features • Bugs fixed faster – or even fix ourselves • Larger community, mailing lists that work! • More choice in external consultants • Contribute back to Open Source • Lower HW footprint cominvent as
- 19. Migration steps – Knowledge gathering & Training – Review current features & arch • Want to keep all features? Add new? – Migration areas: • Index profile • Content • Feeding • Document Processing • Querying • Search middleware? • Admin & Operational – What to do in Application space vs Search space? cominvent as
- 20. Feature comparison ESP– Solr (similarities) Feature ESP Solr Full-text, boolean, range search, Yes Yes sorting, sub-second, facets, did-you- mean, synonyms, faceting Scaling for QPS Add rows Add rows Scaling for document volume Add columns Add shards Synonyms Index/query side Index/query side GEO search Yes Yes (1.5) Boolean query language Yes (FQL) Yes (Lucene or (e)DisMax) APIs HTTP, Java, .NET, HTTP, Java, .NET, C++, PHP Ruby, Python, PHP, Perl, JS cominvent as
- 21. Feature comparison ESP– Solr (differences) Feature ESP Solr Admin server Yes No (coming 1.5) Processes Many (C++, Java, One WAR in Java Python) app-server, 100% Java Navigators / Facets Index-time Query-time Did-you-mean Dictionary based Dictionary or index based Feeding API only HTTP POST or API Document processing Pipeline (py) Simple pipeline (Java, JS, Groovy, Jython, JRuby..) Multi field querying Composite fields DisMax handler cominvent as
- 22. Feature comparison ESP– Solr (differences) Feature ESP Solr Relevancy tuning Rank profiles, term Dynamic function boosting queries and boost functions XRANK XRANK operator Function Queries Freshness boost Freshness in rank Function Queries profile Boost GEO distance Rank profile and Function Queries special Major schema or software updates Cold update, use Stage new content stage environment into new Solr core Pluggability Docprocs, clients Everything :) Request Handlers, Query Parsers, Docprocs, Rank, Spell, tokenizer++ cominvent as
- 23. Feature comparison ESP– Solr (differences) Feature ESP Solr Lemmatization Can be licensed Can be licensed for many from 3rd party languages Query syntax and(a:foo, b:bar) a:foo OR b:bar i:range(0, 100) I:[0 TO 100] d:range(2000-01- d:[2000-01- 01T00:00:00, 01T00:00:00Z TO 2010-03- NOW] 03T12:00:00) Query params query= q= offset= start= hits= rows= spell=1 spellcheck=true What fields to return view=viewname fl=title,price,body... cominvent as
- 24. Your FAST system- overview Your web-app Search middleware? cominvent as Graphics diagram: www.microsoft.com
- 25. Migrating index profile – ESP index profile -> Solr schema.xml – Setup field types, use defaults or create your own – Setup the static fields. ESP: – Solr equivalent: – No need for generic*, use dynamic fields: cominvent as
- 26. Migrating index profile – Composite fields? • Solr can use <copyField> to copy multiple fields into one, e.g. as we did to map many attributes into one field • However, to achieve ranking with different boost of each field, Solr does not need composite field. Use DisMax query handler instead. Very powerful! – No need to edit schema to add new fields. Using dynamic fields, it is easy to e.g. Introduce a color facet for cars or a Mpixels facet for digital cameras cominvent as
- 27. DisMax query example – This Solr query can replace use of composite-field • qt=dismax • q=oslo • qf=title^0.7 highpriorityfields^1.5 mediumpriorityfields^0.6 lowpriorityfields^0.2 recallfields^0.0 body^0.0 • bf=recip(rord(creationDate),1,1000,1000) cominvent as
- 28. Migrating content – If using FAST ContentAPI to push programatically • Use Solr's clients (Java, .NET, Ruby, Python, PHP...) – If feeding FastXML using FileTraverser • Feed as Solr XML using HTTP POST or a POST client – If you feed custom XML with XMLMapper • Have a look at DIH's import and mapping features cominvent as
- 29. Push Feeding example – Feed XML using HTTP POST: • curl http://localhost:8080/solr/update?commit=true -H "Content-Type: text/xml" --data-binary @mydoc.xml – Ruby example: • >gem sources -a http://gemcutter.org >sudo gem install rsolr require 'rsolr' solr = RSolr.connect :url=>'http://localhost:8080' documents = [{:id=>1, :price=>1.00}, {:id=>2, :price=>10.50}] solr.add documents solr.commit cominvent as
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- 31. Querying examples – http://localhost:8080/solr/select?q=car&fl=id,title – Ruby • res=solr.select :q=>'roses', :fq=>['red','white'] res['response']['docs'].each do |doc| puts doc['title'] end cominvent as
- 32. Migrating document processing – Solr lacks a sophisticated pipeline with entity extraction etc. Alternatives: • Do extraction in Application space (Ruby) • Write own stage in Solr pipeline for simple cases • Integrate to do more advanced stuff – Matchers/extractors • LingPipe NamedEntityExtractor inside of OpenPipeline – Synonyms: • Use Solr's synonym handling index/query side – Custom stages: • Write a Solr UpdateProcessor (in Java, Jython etc) – Got a LOT of custom FAST docproc stages? • Have a look at SESAT's PY ProcServer for Solr (GPL) cominvent as
- 33. Migrating linguistics (lemmatization) – Solr ships with Stemming instead of Lemmatization – Stemming has limitations • Biler, bilen, bilene -> bil BUT • Bøker, bøkene -> bøk; boka, bok -> bok – Kstem better. Free with LucidWorks for Solr – If you need singular/plural handling only • Free dictionaries? Check lucene-hunspell – Lemmatization can be licensed from 3rd party such as Basistech, who also has language identification & entity extraction – Language identification also from Sematext cominvent as
- 34. Basistech Rosette forLucene – High-end linguistics capabilities for 19 languages – Language Identification – Segmentation and tokenization – Lemmatization – Noun decompounding – Part-of-speech tagging – Entity extraction – Easily integrated with Lucene/Solr – More: http://www.basistech.com/lucene/ cominvent as
- 35. Migrating search middleware – Using FAST Unity? • Consider migrating middleware logic such as external source querying and federation to SESAT (AGPL) – Using Comperio Front? • Must migrate custom query and resp formats • Consider SESAT as well for migrating flow logic – Or is plain Solr enough? • Solr has built-in support for shards • A shard query will query multiple shards and merge the results into one • Add custom processing as Query Components in Solr • Check contrib & patches! cominvent as
- 36. Migrating Web Crawler – Solr has no built-in web crawler • Instead you can choose from several integrations – The Apache Nutch crawler • Proven with hundreds of millions of pages • http://www.lucidimagination.com/blog/2009/03/09/nutch-solr/ – Apache Droids • Still an incubator, but aims at becoming a full crawler • http://incubator.apache.org/droids/ – Heritix + Solr (example in Solr1.4 book) – OpenPipeline has a (very) simple crawler – Lucene Connectors Framework • Preparing crawler support cominvent as
- 37. Migrating Connectors – Solr handles these sources internally through DIH: • Database, RSS, Web-services, Local filesystem – Additionally throgh Lucene Connectors Framework: • • EMC Documentum, FileNet, JDBC, LiveLink, Patriarch (Memex), Meridio, SharePoint, RSS • New connectors should be written for LCF – Another option: Open Pipeline, supporting: • • Sharepoint, IMAP, Documentum, Vignette, Filesystem cominvent as
- 38. Operations – Solr has no admin-server (coming in 1.5) – Possible to run multiple Tomcat on same server – Multiple cores in same Tomcat – easier migration – No built-in query reports, use 3rd party tools – No built-in monitoring, have a look at Nagios? cominvent as
- 39. More info – Solr WIKI: http://wiki.apache.org/solr/ – Deployments: http://wiki.apache.org/solr/PublicServers – Reference Guide: http://tinyurl.com/ygj3q9j – Solr Book: http://tinyurl.com/solrbook – Solr training: http://www.solrtraining.com/ cominvent as
- 40. Thank You www.cominvent.com jh@cominvent.com www.twitter.com/cominvent This presentation licensed under CC-by-sa license cominvent as You must attribute Cominvent with name and link