elasticsearchHow can I use Elasticsearch KNN to find similar documents?

K Nearest Neighbors (KNN) is a machine learning algorithm used for finding similar documents in an Elasticsearch index. It works by computing the similarity between documents using a distance metric such as Euclidean or cosine distance. The algorithm then returns the K nearest neighbors to a given document.

Example code

GET /my_index/_search
{
  "query": {
    "knn": {
      "my_field": {
        "vector": [1,2,3],
        "k": 10
      }
    }
  }
}

This example code searches the index my_index for documents similar to the given vector [1,2,3], and returns the 10 nearest neighbors.

The code consists of several parts:

1. The GET command which specifies the index to search.
2. The query section, which contains the knn query with the my_field field containing the vector to search, and the k parameter specifying the number of nearest neighbors to return.

For more information on using KNN in Elasticsearch, please refer to the Elasticsearch KNN documentation.

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