Faceting
by Matt Mitchell, Kranti Parisa, Eric Pugh, David Smiley
Apache Solr Enterprise Search Server - Third Edition
- Apache Solr Enterprise Search ServerThird Edition
- Table of Contents
- Apache Solr Enterprise Search Server Third Edition
- Credits
- About the Authors
- About the Reviewers
- www.PacktPub.com
- Preface
- 1. Quick Starting Solr
- 2. Schema Design
- Is Solr schemaless?
- MusicBrainz.org
- One combined index or separate indices
- Schema design
- The schema.xml file
- Summary
- 3. Text Analysis
- 4. Indexing Data
- Communicating with Solr
- Solr's Update-XML format
- Commit, optimize, and rollback the transaction log
- Atomic updates and optimistic concurrency
- Sending CSV-formatted data to Solr
- The DataImportHandler framework
- Indexing documents with Solr Cell
- Update request processors
- Summary
- 5. Searching
- Your first search – a walk-through
- Solr's generic XML structured data representation
- Solr's XML response format
- Understanding request handlers
- Query parameters
- Query parsers and local-params
- Query syntax (the lucene query parser)
- The DisMax query parser – part 1
- Filtering
- Sorting
- Joining
- Spatial search
- Summary
- 6. Search Relevancy
- 7. Faceting
- 8. Search Components
- About components
- The highlight component
- The SpellCheck component
- Query complete/suggest
- The QueryElevation component
- The MoreLikeThis component
- The Stats component
- The Clustering component
- Collapsing and expanding
- The TermVector component
- Summary
- 9. Integrating Solr
- Working with the included examples
- Solritas – the integrated search UI
- SolrJ – Solr's Java client API
- Using JavaScript/AJAX with Solr
- Using XSLT to transform XML search results
- Accessing Solr from PHP applications
- Ruby on Rails integrations
- Nutch for crawling web pages
- Solr and Hadoop
- ManifoldCF – a connector framework
- Document-level security
- Summary
- 10. Scaling Solr
- Tuning complex systems is hard
- Use SolrMeter to test Solr performance
- Optimizing a single Solr server – scale up
- Configuring Solr for near real-time search
- Use SolrCloud to go big – scale wide
- Summary
- 11. Deployment
- A. Quick Reference
- Index
The following parameters are commonly used in facet queries, and are covered in Chapter 7, Faceting:
- Field specific parameter: (Works for highlighting too)
f.myfieldname.facet.mincount=1 - Field value faceting:
facet=on,facet.field=myfieldname,facet.sort=count (count, index),facet.limit=100,facet.offset=0,facet.mincount=0,facet.missing=off,facet.prefix,facet.method(enum,fc, orfcs) - Range faceting:
facet=on,facet.range=myfieldname,facet.range.start,facet.range.end,facet.range.gap(for example,+1DAY),facet.range.hardend=off,facet.range.other=off,facet.range.include=lower(lowerupper,edge,outer, orall) - Facet queries:
facet=on, facet.query - Facet pivots:
facet.pivot=field1,field2,field3 - Facet keys:
facet.field={!key=Type}r_type - Filter exclusion:
fq={!tag=r_type}r_type:Album&facet.field={!ex=r_type}r_type
-
No Comment
..................Content has been hidden....................
You can't read the all page of ebook, please click here login for view all page.