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Merge branch 'annoy-2' of github.com:Vector-Similarity-Search-for-ClickHouse/ClickHouse into annoy-2

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docs/en/engines/table-engines/mergetree-family/annindexes.md
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# Approximate Nearest Neighbor Search Indexes [experimental] {#table_engines-ANNIndex}
The main task that indexes is to quickly find nearest neighbors for multidimensional data. An example of such a problem can be finding similar pictures (texts) for a given picture (text). That problem can be reduced to finding the nearest [embeddings](https://cloud.google.com/architecture/overview-extracting-and-serving-feature-embeddings-for-machine-learning). They can be created from data using [UDF](../../../sql-reference/functions/index.md#executable-user-defined-functions).
The main task that indexes achieve is to quickly find nearest neighbors for multidimensional data. An example of such a problem can be finding similar pictures (texts) for a given picture (text). That problem can be reduced to finding the nearest [embeddings](https://cloud.google.com/architecture/overview-extracting-and-serving-feature-embeddings-for-machine-learning). They can be created from data using [UDF](../../../sql-reference/functions/index.md#executable-user-defined-functions).
The next query finds the closest neighbors in N-dimensional space using the L2 (Euclidean) distance:
``` sql
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ORDER BY L2Distance(Column, Point)
LIMIT N
SETTING ann_index_select_query_params=`k_search=100`
```
```