Learn about the Elasticsearch sparse vector query, how it works, and how to effectively use it.

Introduction

Sparse vector queries with inference

Sparse vector queries with precomputed query vectors

Query optimization with token pruning

What's next?

Sparse vector queries take advantage of Elasticsearch’s powerful inference API, allowing easy built-in setup for Elastic-hosted models such as ELSER and E5, as well as the flexibility to host other models.

What are sparse vector queries in Elasticsearch?

Elasticsearch sparse vector query

Introducing the sparse vector query: Searching sparse vectors with inference or precomputed query vectors

Introducing the general availability of query rules

How do query rules work?

New query rule features

What does this look like?

These are simple examples, what about some more complex examples?

Troubleshooting query rules

Elasticsearch query rules are now generally available

This blog offers practical strategies for tuning search relevance that can be complementary to semantic search.

Lexical search toolbox for relevance tuning

Challenges with semantic search

Benefits of hybrid search

What does a hybrid search look like in Elasticsearch?

Combining result sets

Tuning for relevance

Applying tools for search relevance tuning

Query rules

Synonyms

Wrapping up

Watch the Haystack talk

Search relevance tuning: Tuning semantic search relevance

Search relevance tuning: Balancing keyword and semantic search

Learn about token pruning and how it boosts the performance of text expansion queries by making them more efficient without sacrificing recall.

The strategy behind token pruning

Speed it up by removing tokens

Performance improvements with token pruning

Relevance impact of token pruning

How to use: Pruning configuration

Improving text expansion performance using token pruning

Looking back at Elastic's vector search innovations in Elasticsearch and Lucene

Elasticsearch 7.x

Elasticsearch 8.0

Elasticsearch 8.2

Elasticsearch 8.3

Elasticsearch 8.4

Elasticsearch 8.5

Elasticsearch 8.6

Elasticsearch 8.7

Elasticsearch 8.8

Elasticsearch 8.9

Elasticsearch 8.10

Elasticsearch 8.11

Elasticsearch 8.12

Elasticsearch 8.13

Elasticsearch 8.14

Elasticsearch 8.15

... and beyond!

Vector search improvements in Elasticsearch and Lucene

Looking back: A timeline of vector search innovations

Author

Kathleen DeRusso

Articles

Introducing the sparse vector query: Searching sparse vectors with inference or precomputed query vectors

Elasticsearch query rules are now generally available

Search relevance tuning: Balancing keyword and semantic search

Improving text expansion performance using token pruning

Looking back: A timeline of vector search innovations