elasticsearchHow can I use vector search in Elasticsearch?
Vector search in Elasticsearch is a powerful tool for finding documents that are similar to a given vector of values. It can be used to find similar items in a dataset, such as similar products in an e-commerce store. To use vector search in Elasticsearch, you need to create a vector field in your document mapping and store the vector values in that field.
Here is an example of how to create a vector field and store a vector of values in it:
PUT my_index
{
"mappings": {
"properties": {
"vector_field": {
"type": "dense_vector",
"dims": 3
}
}
}
}
PUT my_index/_doc/1
{
"vector_field": [1.0, 2.0, 3.0]
}
Once the vector field has been created and the vector values stored in it, you can use the query_string
query to search for documents that are similar to a given vector. The following example searches the my_index
index for documents that are similar to the vector [1.0, 2.0, 3.0]
:
GET my_index/_search
{
"query": {
"query_string": {
"query": "vector_field: [1.0, 2.0, 3.0]"
}
}
}
If the query is successful, the output will be a list of documents that are similar to the given vector.
Parts of the example code:
PUT my_index
: Creates an index calledmy_index
type": "dense_vector"
: Sets the type of the vector field todense_vector
dims": 3
: Sets the number of dimensions in the vector field to 3PUT my_index/_doc/1
: Creates a document in themy_index
indexvector_field": [1.0, 2.0, 3.0]
: Stores a vector of values in thevector_field
fieldGET my_index/_search
: Searches themy_index
index for documentsquery_string
: Uses thequery_string
query to search for documents that are similar to a given vector
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