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Improved indexing docs [skip ci]

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Andrew Kane
2023-04-10 21:12:25 -07:00
parent 67fc791d95
commit 00148dfa1f
1 changed files with 2 additions and 8 deletions
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README.md
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@@ -156,14 +156,8 @@ You can add an index to use approximate nearest neighbor search, which trades so
Three keys to achieving good recall are: Three keys to achieving good recall are:
1. Create the index *after* the table has some data 1. Create the index *after* the table has some data
2. Choose an appropriate number of lists (lower is better for recall, higher 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:
- `rows / 1000` for up to 1M rows
- `sqrt(rows)` for over 1M rows
3. Choose an appropriate [number of probes](#query-options) when querying
Add an index for each distance function you want to use. Add an index for each distance function you want to use.