Solr is an open source text search index and tool that allows users to create customizable search solutions. It is highly configurable and allows search results to be tuned, unlike some other search products that do not allow configuration. The presenter is giving a talk on Solr because they took a course on it from LucidWorks and are presenting on behalf of FindWise, a search specialist company that uses various search engines including Solr. When building a Solr solution, the general approach involves designing the schema, prototyping to test indexing and searching, and integrating Solr with other systems for ingestion and presentation.

1. Solr

2. What is it?
• Text search index (engine)
• Open source
• Not a search product
• A tool that allows you to create a search
solution

3. What is it like?
• Google, Google Appliance.
• FAST
• Oracle Secure Enterprise Search
• etc.

4. Google Appliance:
• Sucks data in
• Can’t really configure
• Stuck with results
• Bonnet is locked

5. Solr:
• You need to feed data in
• Highly configurable
• Search results can be tuned
• There is no bonnet

6. Why am I doing a talk?
• Did a course
• LucidWorks content
• Presented by FindWise
• FindWise are a search specialist that use a
range of search engines

7. Caveats
• Course was in Solr 4.1.0, we use 3.6.1 for
APVMA
• Course focussed on search, not ingestion or
presentation
• Java API recommended for ingestion
• ‘Browse’ interface uses Velocity templates for
presentation, but probably isn’t good enough
for most projects.

8. Where does Solr fit?

9. Application Architecture

10. Apache Tika
• Data import handler
• Used to be part of Lucene
• XML
• PDF
• Word
• Excel
• etc.

11. Manifold CF
• Apache
• Connector framework
• Used to connect to content repositories (source)
• Sharepoint
• Documentum
• CMIS
• JDBC
• RSS

12. Hydra
• FindWise
• Although Solr supports validation (e.g.
‘required’), don’t use it for data cleanup.
• Validation failure inconvenient: whole job fails
• Feed in clean data.
• Use Hydra for cleanup.

13. Apache ZooKeeper
• Used for SolrCloud
• Clustering and sharding
• Solr 4.1.0 only
• Side project for Hadoop
• Used to manage Hadoop clusters

14. Inside

15. General Approach
• Design schema
• Prototyping
• Integration

16. Design Schema
• A data modelling exercise
• schema.xml
• Dynamic fields can be useful in the first pass:
<dynamicField name=“*" type="string"
indexed="true" />

17. Prototyping
• Get the data in (index)
• csv, XML, JSON
• post.jar
• URL to search and inspect raw results
• ‘browse’ interface allows developer to
understand how the search is working
• solrconfig.xml

18. Integration
• Not covered
• Content ingestion
• Presentation of results
• Up to you…

19. Demo