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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:
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)
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
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)
Add an index for each distance function you want to use.