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From "Steve Rowe (JIRA)" <>
Subject [jira] [Commented] (SOLR-8542) Integrate Learning to Rank into Solr
Date Tue, 08 Mar 2016 01:52:40 GMT


Steve Rowe commented on SOLR-8542:

Just read through the comments on the issue, but haven't looked at any code yet.

I think you're asking about using managed resources or solrconfig.xml plugins as configuration
locations.  I think that relatively short config stuff fits naturally in solrconfig.xml, and
managed resource infrastructure is set up to enable modifications to structured data in resources
via API (is that enabled here?  probably not, just whole-resource CRUD, I'm guessing).  So
I'd guess solrconfig.xml is a better fit here.

Note that new usages of solrconfig.xml config should consider how they can be addressed via
the Config API.

One other consideration you didn't mention: shouldn't the Solr blob store be considered for
storage/versioning/sharing of models?  (Skimming here makes me think that they are stored
in Zk as files with per-collection config.)

> Integrate Learning to Rank into Solr
> ------------------------------------
>                 Key: SOLR-8542
>                 URL:
>             Project: Solr
>          Issue Type: New Feature
>            Reporter: Joshua Pantony
>            Assignee: Christine Poerschke
>            Priority: Minor
>         Attachments:,, SOLR-8542-branch_5x.patch, SOLR-8542-trunk.patch
> This is a ticket to integrate learning to rank machine learning models into Solr. Solr
Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for
use in training a machine learned model. You can then deploy that model to Solr and use it
to rerank your top X search results. This concept was previously presented by the authors
at Lucene/Solr Revolution 2015 (
> The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, David Grohmann
and Diego Ceccarelli.
> Any chance this could make it into a 5x release? We've also attached documentation as
a github MD file, but are happy to convert to a desired format.
> h3. Test the plugin with solr/example/techproducts in 6 steps
> Solr provides some simple example of indices. In order to test the plugin with 
> the techproducts example please follow these steps
> h4. 1. compile solr and the examples 
> cd solr
> ant dist
> ant example
> h4. 2. run the example
> ./bin/solr -e techproducts 
> h4. 3. stop it and install the plugin:
> ./bin/solr stop
> mkdir example/techproducts/solr/techproducts/lib
> cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar example/techproducts/solr/techproducts/lib/
> cp contrib/ltr/example/solrconfig.xml example/techproducts/solr/techproducts/conf/
> h4. 4. run the example again
> ./bin/solr -e techproducts
> h4. 5. index some features and a model
> curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore'  --data-binary "@./contrib/ltr/example/techproducts-features.json"
 -H 'Content-type:application/json'
> curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore'  --data-binary "@./contrib/ltr/example/techproducts-model.json"
 -H 'Content-type:application/json'
> h4. 6. have fun !
> *access to the default feature store*
> http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ 
> *access to the model store*
> http://localhost:8983/solr/techproducts/schema/mstore
> *perform a query using the model, and retrieve the features*
> http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true

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