From 5146c7cc575f46a31e548543cbd5c4dda461a6d3 Mon Sep 17 00:00:00 2001 From: Andrew Kane Date: Thu, 20 Apr 2023 12:32:49 -0700 Subject: [PATCH] Added guidance for probes to readme [skip ci] --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 59ec97d..a4386bc 100644 --- a/README.md +++ b/README.md @@ -160,8 +160,8 @@ You can add an index to use approximate nearest neighbor search, which trades so Three keys to achieving good recall are: 1. Create the index *after* the table has some data -2. Choose an appropriate number of lists (a good place to start is `rows / 1000` for up to 1M rows and `sqrt(rows)` for over 1M rows) -3. When querying, specify an appropriate number of [probes](#query-options) (higher is better for recall, lower is better for speed) +2. Choose an appropriate number of lists - a good place to start is `rows / 1000` for up to 1M rows and `sqrt(rows)` for over 1M rows +3. When querying, specify an appropriate number of [probes](#query-options) (higher is better for recall, lower is better for speed) - a good place to start is `lists / 10` for up to 1M rows and `sqrt(lists)` for over 1M rows Add an index for each distance function you want to use.