In this tutorial, we will discuss how to optimize PostgreSQL’s pgvector with IVFFlat indexing. We’ll cover the following topics: IVFFlat stands fo

Understanding PostgreSQL pgvector Indexing with IVFFlat

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2023-04-02 00:00:02

In this tutorial, we will discuss how to optimize PostgreSQL’s pgvector with IVFFlat indexing. We’ll cover the following topics:

IVFFlat stands for Inverted File with Flat Compression. It’s an approximate nearest neighbor (ANN) search method that aims to improve search performance by dividing the vector space into a fixed number of clusters. The algorithm works by assigning each vector in the dataset to its closest cluster center, and then building an inverted file that maps cluster centers to the vectors they contain.

When searching for the nearest neighbors of a query vector, IVFFlat first identifies the closest cluster center(s) and then searches within the associated inverted list(s) for the nearest neighbors. This allows the algorithm to avoid searching the entire dataset, resulting in faster query times.

Adding an index enables approximate nearest neighbor search (since there’s not an efficient way to index exact search with high dimensional data). Two very important things to keep in mind to avoid bad results / poor recall are:

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