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| There are already a bunch of hybrid search in haystack past conferences: | |
| EU 2023: (Mastering Hybrid Search: Blending Classic Ranking Functions with Vector Search for Superior Search Relevance)[https://haystackconf.com/eu2023/talk-10/] | |
| EU 2023: (Reciprocal Rank Fusion (RRF) or How to Stop Worrying about Boosting)[https://haystackconf.com/eu2023/talk-2/] | |
| US 2024: (All Vector Search is Hybrid Search)[https://haystackconf.com/us2024/talk-1/] | |
| US 2024: (Better Semantic Search with Hybrid (Sparse-Dense) Search) | |
| # Doing hybrid search on your real-time data in pure SQL with CrateDB's index-all strategy. | |
| Points to highlight: | |
| - Hybrid search (convex/rrf) in pure SQL. | |
| - Do the whole thing is live data (constantly ingesting new things) | |
| - Showcase the index-all strategy | |
| Description | |
| ----------- | |
| There are many ways of doing Hybrid search, but what if I told you that you could do it with high resilience, | |
| with pure SQL, fast queries without giving up flexibility and scalability. | |
| CrateDB is a powerful distribute SQL database based on Apache Lucene, we can implement Hybrid search using | |
| either convex or RRF as reranking methods in pure SQL, directly in your live data with fast ad-hoc queries | |
| thanks to its index-all by default strategy. | |
| In this talk we will: | |
| * Have a quick overview of CrateDB and some of its interesting capabilities. | |
| * Look at how we index every column by default. | |
| * Show how to implement Hybrid search using only SQL. | |
| * Show the demo where we apply Hybrid search in our real time data (constantly ingesting new rows) project. | |
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