| IntroductionWhy do we need an abstraction layer for full-text indexing?Developers often must implement search methods for their database, but unfortunately so far it has been easier to roll your own simple search than to deploy an existing project such as Lucene. Merquery provides an abstraction layer for popular text indexing engines and makes it easy for anyone to attach them to their database. Using MerqueryYou can enable Lucene indexing of a database table like so (assuming the library is in contrib.search): from contrib.search.backends import LuceneIndexerclass Person(models.Model): first_name = models.CharField(maxlength=30) last_name = models.CharField(maxlength=30) biography = models.TextField()indexer = LuceneIndexer('/tmp/person-index', Person, {'first': 'Person.first_name', 'last': 'Person.last_name'}, text_fields=['Person.biography'] )indexer.update()indexer.search("brian -last:beck", order_by='last_name')Current StatusMerquery is in a working state but needs some polish. XapianIndexer? and LuceneIndexer? currently works fine and is about 90% complete. HypeIndexer? are not yet fully functional, this are about 50% complete. Note: You should see the ticket #2707 if you want use XapianIndexer?. More info from the author in this blog post. |
