docs/reference/query-languages/esql/_snippets/commands/layout/mmr.md
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The MMR command reduces the result set from a set of input rows by applying a diversification strategy to the return rows.
MMR [query_vector] ON field LIMIT limit [WITH { "lambda": lambda_value }]
field
: (required) The name of the field that will use its values for the diversification process.
The field must be a dense_vector type.
limit
: (required) The maximum number of rows to return after diversification.
query_vector
: (optional) The query vector to use as part of the diversification algorithm for comparison.
Must have the same number of dimensions as the vector field you are searching against.
Must be one of:
- An array of floats
- A hex-encoded byte vector (one byte per dimension; for bit, one byte per 8 dimensions)
- A base64-encoded vector string. Base64 supports float and bfloat16 (big-endian), byte, and bit encodings depending on the target field type.
- A function or expression that returns a dense_vector
lambda_value
: (Required if WITH is used) A value between 0.0 and 1.0 that controls how similarity is calculated during diversification.
Higher values weight the similarity to the query_vector more heavily, lower values weight the diversity more heavily.
Use the MMR command to return a limited, but diverse, set of row results.
This is useful when you want to maximize diversity by preventing similar documents from dominating the top results returned from a search.
The command uses MMR (Maximum Marginal Relevance) diversification to discard results that are too similar to each other.
Similarity is determined based on the field parameter and the optionally provided query_vector.
:::{note} The ordering of results returned from the input rows is preserved. :::
:::{important}
You must limit the number of input rows before the MMR command.
For example, you can use the LIMIT command to restrict the input.
:::
:::{include} ../examples/mmr.csv-spec/simpleMMR.md :::
:::{include} ../examples/mmr.csv-spec/simpleMMRWithQueryVector.md :::
:::{include} ../examples/mmr.csv-spec/simpleMMRWithTextEmbedding.md :::