diff --git a/apps/www/_blog/2023-07-13-pgvector-performance.mdx b/apps/www/_blog/2023-07-13-pgvector-performance.mdx index 7dc6cd3ea05..1e11e056e95 100644 --- a/apps/www/_blog/2023-07-13-pgvector-performance.mdx +++ b/apps/www/_blog/2023-07-13-pgvector-performance.mdx @@ -198,11 +198,11 @@ Another way to improve performance without throwing more compute would be to inc We ran a test to measure the impact of list size: we uploaded 90,000 vectors from Wikipedia dataset and then queried 10,000 vectors from the same dataset. The documentation recommends to use `lists` constant of `number of vectors / 1000`. In this case, it would be 90. -But as our experiment shows, we can improve select queries speed if we make more lists (i.e. with more lists in the index we need to get less index data to get the same precision). E.g. for a precision of 95%, we need to take +But as our experiment shows, we can improve `select` speed if we increase lists (i.e. with more lists in the index we need to get less index data to get the same precision). So for 95% precision, we can take any of: -- 3% of index data for 270 lists, -- 6% - for 90 lists, -- and 13% - for 30 lists. +- 3% of index data = 270 lists +- 6% of index data = 90 lists +- 13% of index data = 30 lists