
Impact of Large Stored Fields on Apache Solr Query Performance
This blog post analyzes and discovers the impact of large stored fields on Apache Solr query performance.

This blog post analyzes and discovers 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 post explores the internals of Apache Solr queryResultCache and filterCache through practical code examples.

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?

This blog post explores the Apache Solr multi-field search limitations with a focus on the sow(split on whitespace) parameter.

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.
We are Sease, an Information Retrieval Company based in London, focused on providing R&D project guidance and implementation, Search consulting services, Training, and Search solutions using open source software like Apache Lucene/Solr, Elasticsearch, OpenSearch and Vespa.
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