PostgreSQL as a Vector Database: Part 2, Using HNSW Index скачать в хорошем качестве

PostgreSQL as a Vector Database: Part 2, Using HNSW Index

In this episode, we continue to build a generative AI application that helps select Airbnb vacation homes for travelers heading to San Francisco. The application already utilizes PostgreSQL as a vector database for storing and querying embeddings of Airbnb listings. Our next step is to optimize the performance of the similarity search with the HNSW index. The HNSW (Hierarchical Navigable Small Worlds) index is among the top-performing vector indexing algorithms used in vector databases worldwide. In this video, you'll learn how to effectively implement it in PostgreSQL. 0:00 Introduction 0:28 Airbnb Recommendations Service, Quick Recap 1:43 Similarity Search and Full Table Scan 3:11 Creating an HNSW Index for Airbnb Listings 5:07 Index Build Time vs. Accuracy Trade-off 5:45 Testing the Index 6:07 Adjusting the Source Code to Enable the Index Scan 7:10 Comparing the Accuracy of Full Table and Index Scans 8:02 What's Next in the PostgreSQL as a Vector Database Series Resources: Airbnb recommendations service: https://github.com/YugabyteDB-Samples... First episode:    • PostgreSQL as a Vector Database: Part 1, G...   Curious to learn even more about databases? Follow me here: Medium:   / magda7817   Twitter:   / denismagda