This blog post will analyze the impact of large stored fields on Apache Solr query performance.
The Apache Solr Birds of a Feather from ApacheCon NA 2022 in New Orleans taught us we can improve Solr in many ways… This is the TOP-10!
In this blog post we present the available learning to rank Apache Solr features with a focus on categorical features and how to manage them.
This blog is meant to explain how QueryResultCache and FilterCache are used during the basic query processing in Apache Solr 8.11.0. This blog does not explain how these caches are used during the execution of more advanced components like faceting. Solr caches are associated with a specific instance of an Index Searcher. By default, elements…
How the FeatureLogger works? When the Feature Vector Cache is used in Solr? Is the cache speeding up the rerank process?
Neural Search in Apache Solr has been contributed by Sease thanks to Alessandro Benedetti, Apache Lucene/Solr committer, and Elia Porciani.
How a learning to rank query works in Solr? How we can obtain the required features extraction time from the Solr qTime parameter?
How eDismax sow parameter works The sow(split on whitespace) is an eDismax query parser parameter [1] that regulates aspects of query time text analysis that impact how the user query is parsed and the internal Lucene query is built.It is particularly relevant in multi-term and multi-field search.If sow=true : first the user query text is…
Common errors and warnings in manipulating feature stores and models in Solr. Pay attention also to JVM Heap and Zookeeper.
How to list, upload, delete feature stores and models necessary in Solr for learning to rank.