Apache Solr 4.0 with RankingAlgorithm 1.4.2
Apache Solr** 4.0 with RankingAlgorithm 1.4.2 (build 2012-03-19) is now available for download. See downloads below ...
- **New**, NRT now works with both RankingAlgorithm and Lucene
- NRT does not close the searcher (no commits are needed), so can be fine grained resulting in thread1, thread2, thread3 returning new results
- See how the NRT implemenation is more granular/realtime compared to soft commit, NRT comparison with soft commit
- Very high insert/update performance, 70000 docs / sec
- Very high performance, <10 ms response time (50 million index)
- Scale to 1 billion documents or more
Apache Solr 3.5 with RankingAlgorithm 1.4.2
Apache Solr** with RankingAlgorithm enables Solr's search results to be comparable to Google Site Search and much better than Apache Lucene** for searches using the Perl index, see comparison searches. RankingAgorithm is a search library that uses a new scoring algorithm to rank results accurately and relevantly. RankingAlgorithm is very easy to use and uses the very popular Lucene index but scores and ranks on its own.
Solr with RankingAlgorithm also supports NRT and can update documents at about 5000 documents in 498 with concurrent searches without closing the Searchers or clearing the caches, etc., see
Near Real Time Search.
Multiple Algorithm are available SIMPLE, SIMPLE1, COMPLEX, COMPLEX1. SIMPLE* are very fast algorithms and can return queries in <50ms on a 10m wikipedia index (complete index).
It can also scale to 100m docs or maybe more. COMPLEX is a more complex algorithm so is a little
slower compared to the SIMPLE, but can also still return queries in < 100ms on a 10m wikipedia index (complete index).
COMPLEX is more accurate and should be able to give you the best rankings as compared to SIMPLE*.
RankingAlgorithm works in two modes, document mode and product mode:
In document mode, it ranks documents such as HTML, Wikipedia, Word/PDF docs relevantly while in Product mode, a term's occurrence is taken into account and scored accordingly. So titles starting with "wii console" are ranked first, and the others rank lower as the occurrence of "wii console" shifts in the title or gets reversed, see below:
- Wii Console and Wii Fit Plus with Balance Board Bundle (Nintendo Wii)
- Wii Console System with Wii Sports Resort Game with TWO MotionPlus Attachments
- Nintendo Wii Console w/ Bonus Wii Sports Resort Bundle, Black
- Pelican Accessories Wii Console Stand - Nintendo Wii
- Grafitti Skin for Nintendo Wii Console
- NEW AC Adapter Cable Cord Power Supply For NINTENDO WII Gaming Console
- Wii Remote Charging Console Stand
- Nintendo Wii Skin - System Console Skin and two Wii Remote Skins - Blue Vortex
- CET Domain 10301901 Console Stand Station for Nintendo Wii
The RankingAlgorithm has been integrated into Solr so that either Lucene or the RankingAlgorithm can be used to do the search. The RankingAlgorithm scoring or working does not break any of the existing functionality, so shrad, faceting, highlighting, etc. still work as before. RankingAlogirhtm only uses Lucene Apis to retrieve the terms from the index and uses its own ranking and scoring to rank the documents. The scoring is very friendly and easy to follow.
Get more information:
Give it a try Download Apache Solr with RankingAlgorithm
Try the Demos here,
Try Autocomplete using Solr with RankingAlgorithm, similar to Google/Yahoo/Bing's autocomplete (It is free),
Give it a try
Installing and Using Solr with RankingAlgorithm
Install Solr as before, no changes to the existing installation steps (see Solr docs
for installation). No changes to the way you query or use Solr. The change is when you
initiate a query, the search uses RankingAlgorithm instead of Lucene. You can still use
Lucene by adding "&lucene=true" to use Lucene as before. You can download Solr with RA from here and follow the steps as in the download docs either on the Solr website or from here.
See examples below:
Searching in document mode (default):
http://localhost:8773/solr/select/?q=california gold rush&fl=score
Searching in product mode:
http://localhost:8773/solr/select/?q=wii console&fl=score&scoring=product
Searching using Lucene library:
http://localhost:8773/solr/select/?q=california gold rush&fl=score&lucene=true
Search components
Autocomplete using Solr with RankingAlgorithm, similar to Google/Yahoo/Bing's autocomplete (It is free),
Give it a try
Demos
Give it a try (Downloads)
- Download Apache Solr with RankingAlgorithm (Free)
Bundle:
- Solr 4.0 (NRT support) with RankingAlgorithm 1.4.3 (bundle 160MB)
[very high update perf(70000 docs / sec), very high performance, <10 ms response times (50 million index), scale upto 1 billion docs; supports NRT with both RankingAlgorithm and Lucene. Improved performance over 1.4 (Early Access Release from build 2012-03-19), more info SolrJ NRT Testcode]
[md5sum:5df04b5abf9a2e734fb1b9f8bfa0af96], 2012/05/14 (4.0.20120129.7)
- Solr 4.0 (NRT support) with RankingAlgorithm 1.4.1 (bundle 160MB)
[very high update perf(70000 docs / sec), very high performance, <10 ms response times (50 million index), scale upto 1 billion docs; supports NRT with both RankingAlgorithm and Lucene. (Early Access Release from build 2012-03-19), more info SolrJ NRT Testcode]
[md5sum:fc808b4fecd39416e3b3570f1ea35f3f], 2012/03/29 (4.0.20120129.3)
- Solr 3.5 (NRT support) with RankingAlgorithm 1.4.2 (bundle 118MB)
[very high update perf(5000 docs in 450 ms), 50-100% improved performance over 1.4, <50 ms response times (10 million wikipedia index), scale upto 100m docs, more info SolrJ NRT Testcode]
[md5sum:334ab7fc30e3910e0976a45bb22cb8fc], 2012/04/18 (3.5.20111211.8)
- Solr 3.5 (NRT support) with RankingAlgorithm 1.4.1 (bundle 118MB)
[very high update perf(5000 docs in 450 ms), 50-100% improved performance over 1.3, <50 ms response times (10 million wikipedia index), scale upto 100m docs, more info SolrJ NRT Testcode]
[md5sum:0f1560bd7402e9c4708168a96466af99], 2012/02/26 (3.5.20111211.7)
- Solr 3.5 (NRT support) with RankingAlgorithm 1.3 (bundle 118MB)
[very high update perf(5000 docs in 450 ms), 50-100% improved performance over 1.2, <50 ms response times (10 million wikipedia index), scale upto 100m docs, more info SolrJ NRT Testcode]
[md5sum:d230eb7cea83c471dd46446e255aa5ee], 2011/12/25 (3.5.20111211.5)
- Solr 3.4 (NRT support) with RankingAlgorithm 1.3 (bundle 110MB)
[very high update perf(10000 docs/sec), 50-100% improved performance over 1.2, <50 ms response times (10 million wikipedia index), scale upto 100m docs, more info SolrJ NRT Testcode]
[md5sum:5bf96814ff1ddffe255804e49b447baf], 2011/11/25 (3.4.20111125.1)
- Solr 3.3 (NRT support) with RankingAlgorithm 1.2 (bundle 110MB)
[very high update perf(10000 docs/sec), <100 ms response times (10 million wikipedia index), scale upto 100m docs, more info SolrJ NRT Testcode]
[md5sum:6515d2da2071d0f6c76b5e44acfce63d], 2011/08/23 (3.3.20110823.1)
- Solr 3.2 (NRT support) with RankingAlgorithm 1.1 (bundle 110MB)
[high update perf, 5000 docs/sec] [md5sum:be03b95be21c788186b7bdc34fe38f67]
- Download Apache Solr 1.4.1 with RankingAlgorithm 1.1 (apache solr + rankingalgorithm bundle)
[md5sum:2c4b264c92ff9d32285048a4c780cf27]
(see installation steps)
War file:
- Solr 4.0 (NRT support) with RankingAlgorithm 1.4.3 (war file 33MB)
[very high update perf(70000 docs / sec), very high performance, <10 ms response times (50 million index), scale upto 1 billion docs; NRT supports both RankingAlgorithm and Lucene (Early Access Release from build 2012-03-19), more info SolrJ NRT Testcode]
[md5sum:0dcd07958ade0430c574b40cd144ebfd], 2012/05/14 (4.0.20120129.7)
- Solr 4.0 (NRT support) with RankingAlgorithm 1.4.1 (war file 33MB)
[very high update perf(70000 docs / sec), very high performance, <10 ms response times (50 million index), scale upto 1 billion docs; NRT now supports both RankingAlgorithm and Lucene (Early Access Release from build 2012-03-19), more info SolrJ NRT Testcode]
[md5sum:099179c0ad0c53d72ca3f4153e837ae3], 2012/03/29 (4.0.20120129.3)
- Solr 4.0 (NRT support) with RankingAlgorithm 1.4.1 (war file 33MB)
[very high update perf(5000 docs in 450 ms), New, NRT now supports both RankingAlgorithm and Lucene. Improved performance over 1.4 (Early Access Release from build 2012-03-19), more info SolrJ NRT Testcode]
[md5sum:099179c0ad0c53d72ca3f4153e837ae3], 2012/03/29 (4.0.20120129.3)
- Solr 3.5 (NRT support) with RankingAlgorithm 1.4.2 (war file 6.64MB)
[very high update perf(5000 docs in 450 ms), 50-100% improved performance over 1.4, <50 ms response times (10 million wikipedia index), scale upto 100m docs, more info SolrJ NRT Testcode]
[md5sum:f527237639d8faa7cfa58bd77e14dd59], 2012/04/18 (3.5.20111211.8)
- Chunk download (1 MB each, last chunk maybe less than 1 MB):
On Unix/Linux/Cygwin/Mac: cat chunk01 chunk02 ... > get_orig_file_back.zip
On Windows: copy /B chunk01+chunk02 ... get_orig_file_back.zip
unzip get_orig_file_back.zip
Chunk 00
Chunk 01
Chunk 02
Chunk 03
Chunk 04
Chunk 05
Chunk 06
- Solr 3.5 (NRT support) with RankingAlgorithm 1.4.1 (war file 6.64MB)
[very high update perf(5000 docs in 450 ms), 50-100% improved performance over 1.3, <50 ms response times (10 million wikipedia index), scale upto 100m docs, more info SolrJ NRT Testcode]
[md5sum:33eb04ca580dcf793dc1355f65758f4b], 2012/02/26 (3.5.20111211.7)
- Chunk download (1 MB each, last chunk maybe less than 1 MB):
On Unix/Linux/Cygwin/Mac: cat chunk01 chunk02 ... > get_orig_file_back.zip
On Windows: copy /B chunk01+chunk02 ... get_orig_file_back.zip
unzip get_orig_file_back.zip
Chunk 00
Chunk 01
Chunk 02
Chunk 03
Chunk 04
Chunk 05
Chunk 06
- Solr 3.5 (NRT support) with RankingAlgorithm 1.3 (war file 6.64MB)
[very high update perf(5000 docs in 450 ms), 50-100% improved performance over 1.2, <50 ms response times (10 million wikipedia index), scale upto 100m docs, more info SolrJ NRT Testcode]
[md5sum:4c15c02382a00f42142539e02cc6b996], 2011/12/25 (3.5.20111211.5)
- Solr 3.4 (NRT support) with RankingAlgorithm 1.3 (war file 7MB)
[very high update perf(10000 docs/sec), 50-100% improved performance over 1.2, <50 ms response times (10 million wikipedia index), scale upto 100m docs, more info SolrJ NRT Testcode]
[md5sum:f5d572625774ae9a44a18c18bfc47898], 2011/10/11 (3.4.20111125.1)
- Solr 3.3 (NRT support) with RankingAlgorithm 1.2 (war file 7MB)
[very high update perf(10000 docs/sec), <100 ms response times (10 million wikipedia index), scale upto 100m docs, more info SolrJ NRT Testcode]
[md5sum:12e5462a0e3def665904e5a8914e435a], 2011/08/23 (3.3.20110823.1)
- Solr 3.2 (NRT support) with RankingAlgorithm 1.1 (war file 7MB)
[high update perf, 5000 docs/sec] [md5sum:85d0979a820912c34fa4ee70f642fc1d]
- Download Apache Solr 1.4.1 with RankingAlgorithm 1.1 (just the war file)
[md5sum:fec749de1fabc58bfe4863a7e8502ee8]
(see installation steps)
- Download RankingAlgorithm Library (Free):
- ver 1.4.1, works with Lucene 4.x [md5sum:b463a16e86ba9be94c35b563c837f774], 2012/03/22 (1.4.1.20120322.1)
- ver 1.4.1, works with Lucene 3.x [md5sum:93954336e081f97c8d60f9aabb99bead], 2012/03/05 (1.4.1.20120305.1)
- ver 1.3, works with Lucene 3.x [md5sum:c3b04c45771c3df557e2d0e1236a3bf3], 2011/11/25 (1.3.20111125.1)
- ver 1.2, works with Lucene 3.x [md5sum:4ef61cbef033a567f434d7008ae808fe], 2011/08/21
- ver 1.1, works with Lucene 3.x [md5sum:119e6f17466d245fe857e9c427ba88dd]
- ver 1.0, works with Lucene 3.x [md5sum:8896655a465b4ee2b447bdacc7ad404e]
- Download RankingAlgorithm exposed as Lucene API Library (Free)
Steps:
Lucene 4.0
1. Download Lucene core 4.x.0 above
2. Download RankingAlgorithm 1.4.1 for Lucene 4.x above
3. Replace lucene-core-4.x.0.jar with lucene-ra-core-4.x.0.jar
3a. unzip lucene-core-4.x.0.zip
3b. mv lucene-core-4.x.0.jar lucene-core-4.x.0.jar_backup
3c. cp lucene-ra-core-4.x.0.jar lucene-core-4.x.0.jar
3c1. cp lucene-modules-4x.jar lucene-modules-4x.jar
4. Add lucene-core-4.x.0.jar, lucene-modules-4x.jar and rankingalgorithm40_1.4.1.jar to the classpath
5. Run your previous Lucene examples, applications with no changes but using the RankingAlgorithm for searches instead of Lucene library.
Lucene 3.0
1. Download Lucene core 3.x.0 above
2. Download RankingAlgorithm 1.3 for Lucene 3.x above
3. Replace lucene-core-3.x.0.jar with lucene-ra-core-3.x.0.jar
3a. unzip lucene-core-3.x.0.zip
3b. mv lucene-core-3.x.0.jar lucene-core-3.x.0.jar_backup
3c. cp lucene-ra-core-3.x.0.jar lucene-core-3.x.0.jar
4. Add RankingAlgorithm to the classpath
5. Run your previous Lucene examples, applications with no changes but using the RankingAlgorithm for searches instead of Lucene library.
Note:
a. To use product mode, start your app with -Dmode=product, default is document mode. To use document mode, use -Dmode=document
b. To specify the scan depth in product mode, use -Dscan=fast, -Dscan=medium, -Dscan=full
c. To specify AND/AND_OR/OR, specify -DAND_OR=and, -DAND_OR=or, -DAND_OR=and_or
d. To switch to lucene, start with -Dlucene=true
- Download Autocomplete using Solr with RankingAlgorithm (similar to Google/Yahoo/Bing's autocomplete)(Free)
Features
1. Search very accurate and relevant. Comparable to Google site search and much better than Lucene, see comparison.
2. Three algorithms, SIMPLE, SIMPLE1 and COMPLEX.
3. Two modes, Document and Product mode. Product mode enables very accurate product/retail/short twitter text searches. Document mode enables relevant search, can be used for product searches too.
4. By default AND/OR combinations.
5. Very easy scoring with a relevancy score.
6. Very easy to use.
7. Score boosting, supports Document, Field, Query & Query term boosts.
8. Uses the very popular Lucene index. No changes to your code or index.
9. NRT search
10. Query a 10m wikipedia index in <50 ms, scale upto 100m docs
11. Supports +- boolean queries, entire Lucene Query Syntax
Documentation
Discussions
RankingAlgorithm
** Solr and Lucene are trademarks of Apache Software Foundation
The NRT implementation differs from soft commit as below:
- Does not close the SolrIndexSearcher object. SolrIndexSearcher is a heavy object, holds caches, searches could be in progress, ref-counted, etc.
- The implementation passes the IndexReader as a parameter to each search ( suits the methodology of de-coupling the reader and searcher, and not maintaining any directory related information).
- Since the IndexReader is passed as a parameter, the search can be very granular, allowing query1, query2, query3 to
return updated results in a high frequency update scenario.
As the searcher is not closed, the cache structures are not destroyed. The user can disable the queryResultsCache,
etc. as needed for now. The dynamic IndexReader allows fine granular realtime
search which may not be possible with soft commit.
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