All, I have a few questions related to boosting and whether my use case makes sense for Dismax vs. the standard parser.
I have created a gist of my field definitions and current query structure here: https://gist.github.com/joshdcollins/0e3f24dd23c3fc6ac8e3 With the given configuration I am attempting to: * Support partial and exact matches by indexing fields twice — once with ngram and once without * Boost exact matches higher than partial matches * Boost matches in the entity_name (and entity_name_exact) field higher than content and content_exact fields * Boost matches with an entity_type of ‘company’ and ‘insight’ higher than other result types 1) Does the field definition and query approach make sense given the above objectives? 2) I have an additional use case to support a query syntax where terms wrapped in single quotes must be exact matches. Example “hello ‘wor'” would NOT match a document containing hello and world. a) Using the dismax parser can you explicitly determine which terms will be checked against which fields? In this case I would search “hello” against my general fields and “wor" against the _exact fields. b) Does this level of structured query better lend itself to using the standard query parser? 3) Does anyone have any experience or resources troubleshooting the fast vector highlighter? It is working correctly in most cases, but some search terms (sized lower than the boundryScanner.maxScan) return no content in the highlighter results like: <lst name="highlighting"> <lst name="d-3318"/> <lst name="cn-29348"/> <lst name="cn-29952"/> <lst name="cn-30329"/> <lst name="cn-30338"/> <lst name="cn-29349"/> <lst name="cn-30426"/> <lst name="cn-17546"/> </lst> In some other cases the highlighter will highlight a term once in a results, but not in another occurrence. Appreciate any insight anyone can provide! jc
