By offering an API for common Solr functionality you no longer need to compose complex querystrings and parameters manually, greatly reducing development time and complexity. Take a look at the examples shown above for a first impression. To get a good view of the difference compared to other Solr clients or manual requests see Why Solarium?
Few months ago, we started a complete rewrite of the new version of Calenda powered by Lodel. The biggest part of the public side of Calenda—programaticaly speaking—is its search engine: this engine is used everywhere, not only on the result pages, but also on the front page and the event page.
Our search engine choice is Lucene/Solr, we already use it to index and provide faceted search on all the contents from Revues.org, Hypotheses.org and the actual Calenda. Solr is fast, powerful, easy to use and to maintain, and supported by a strong community. It also provides a very interesting functionnality: dynamic fields.
Après plus d'un an depuis la dernière version stable, Solr 1.4 est finalement disponible depuis hier en téléchargement.
Les améliorations sont nombreuses, tant au niveau de l'optimisation des performances que du point de vue fonctionnel. Au menu de cette version toute fraîche, on trouvera entre autre :
* Meilleure intégration aux SGBD grâce au gestionnaire d'import de données ;
* Possibilités d'indexation de documents externes (Word, OOo, PDF, HTML, etc.) grâce au projet Apache Tika ;
* Clustering dynamique de résultats de recherche avec Carrot2 ;
* Une tonne d'améliorations, de nouveaux greffons et de corrections de bugs ;
La liste des améliorations est vraiment très importante. Les intéressés auront tout intérêt à consulter le CHANGELOG complet.
Pour rappel, Lucene est une bibliothèque de recherche full-text écrite en Java et gérée par le projet Apache. Solr utilise Lucene pour proposer les fonctionnalités d'un moteur de recherche de qualité professionnelle (reche
# Simple query search
# Sorting – one can dynamically define new sort criterias
# Search results are rendered very much like Google search results are rendered. It is also possible to view all stored field values for every hit.
# Custom hit rendering – It is possible to show thumbnails (images) per hit and also customize a view for a hit based on html templates
# Faceting – one can dynamically define field and query facets via the UI. it is also possible to pre-configure these facets in the configuration file.
# Highlighting – you can dynamically configure highlighting. it can also be pre-configured in the configuration file
# Spellchecking – you can dynamically configure spell checking. Can also be done in the configuration file. Supports collation. It is also possible to send "build" and "reload" commands.
# Data import handler – if used, it is possible to send a "full-import" and "status" command ("delta-import" is not implemented yet, but it's easy to add)
# Console – For developme
The Apache Solr extension is an extremely fast, light-weight, feature-rich library that allows PHP developers to communicate easily and efficiently with Apache Solr server instances using an object-oriented API.
While many Lucene/Solr applications will never outgrow a single, well-configured machine, the fact is, more and more applications are pushing beyond the single machine limit due to either index size or query volume. In discussing Lucene and Solr best practices for performance and scaling, Mark Miller explains how to get the most out of a single machine, as well as how to scale out to harness multiple machines to handle large indexes, large query volume, or both.
The idea is to use the RDF data model and a triples store to populate the Solr schema index. We leverage the powerful and flexible data representation framework (RDF), in conjunction with the piece of software that lets you do whatever you want with that data (Virtuoso), to feed a carefully tailored Solr schema index to optimally perform three things: full-text search, aggregates and filtering. Also, we want to leverage the ontologies used to describe this data to be able to infer things vis-à-vis these indexed resources in Solr. This leverage enables us to use inference on full-text search, aggregates and filtering, in Solr! This is quite important since you will be able to perform full text searches, filtered by types that are inferred!
We're the commercial entity exclusively dedicated to Apache Lucene/Solr open source search technology. Our products and services can help you develop and deploy search solutions with confidence: professional training, SLA-based support subscriptions; best practices consulting; free certified distributions of Lucene and Solr; and value-add software.
Yonik Seeley recently implemented a new method for faceting which will be available in Solr 1.4 (yet to be released). It is optimized for faceting on multi-valued fields with large number of unique terms but relatively low number of terms per document. The new method has made a large improvement in performance for faceted search and has cut memory usage at the same time.