[[search-aggregations-metrics-min-aggregation]]
=== Min aggregation
++++
<titleabbrev>Min</titleabbrev>
++++

A `single-value` metrics aggregation that keeps track and returns the minimum
value among numeric values extracted from the aggregated documents.

NOTE: The `min` and `max` aggregation operate on the `double` representation of
the data. As a consequence, the result may be approximate when running on longs
whose absolute value is greater than +2^53+.

Computing the min price value across all documents:

[source,console]
--------------------------------------------------
POST /sales/_search?size=0
{
  "aggs": {
    "min_price": { "min": { "field": "price" } }
  }
}
--------------------------------------------------
// TEST[setup:sales]

Response:

[source,console-result]
--------------------------------------------------
{
  ...

  "aggregations": {
    "min_price": {
      "value": 10.0
    }
  }
}
--------------------------------------------------
// TESTRESPONSE[s/\.\.\./"took": $body.took,"timed_out": false,"_shards": $body._shards,"hits": $body.hits,/]

As can be seen, the name of the aggregation (`min_price` above) also serves as
the key by which the aggregation result can be retrieved from the returned
response.

==== Script

If you need to get the `min` of something more complex than a single field,
run the aggregation on a <<runtime,runtime field>>.

[source,console]
----
POST /sales/_search
{
  "size": 0,
  "runtime_mappings": {
    "price.adjusted": {
      "type": "double",
      "script": """
        double price = doc['price'].value;
        if (doc['promoted'].value) {
          price *= 0.8;
        }
        emit(price);
      """
    }
  },
  "aggs": {
    "min_price": {
      "min": { "field": "price.adjusted" }
    }
  }
}
----
// TEST[setup:sales]
// TEST[s/_search/_search?filter_path=aggregations/]

////
[source,console-result]
--------------------------------------------------
{
  "aggregations": {
      "min_price": {
          "value": 8.0
      }
  }
}
--------------------------------------------------
////

==== Missing value

The `missing` parameter defines how documents that are missing a value should
be treated. By default they will be ignored but it is also possible to treat
them as if they had a value.

[source,console]
--------------------------------------------------
POST /sales/_search
{
  "aggs": {
    "grade_min": {
      "min": {
        "field": "grade",
        "missing": 10 <1>
      }
    }
  }
}
--------------------------------------------------
// TEST[setup:sales]

<1> Documents without a value in the `grade` field will fall into the same
bucket as documents that have the value `10`.

[[search-aggregations-metrics-min-aggregation-histogram-fields]]
==== Histogram fields

When `min` is computed on <<histogram,histogram fields>>, the result of the aggregation is the minimum
of all elements in the `values` array. Note, that the `counts` array of the histogram is ignored.

For example, for the following index that stores pre-aggregated histograms with latency metrics for different networks:

[source,console]
--------------------------------------------------
PUT metrics_index/_doc/1
{
  "network.name" : "net-1",
  "latency_histo" : {
      "values" : [0.1, 0.2, 0.3, 0.4, 0.5], <1>
      "counts" : [3, 7, 23, 12, 6] <2>
   }
}

PUT metrics_index/_doc/2
{
  "network.name" : "net-2",
  "latency_histo" : {
      "values" :  [0.1, 0.2, 0.3, 0.4, 0.5], <1>
      "counts" : [8, 17, 8, 7, 6] <2>
   }
}

POST /metrics_index/_search?size=0
{
  "aggs" : {
    "min_latency" : { "min" : { "field" : "latency_histo" } }
  }
}
--------------------------------------------------

The `min` aggregation will return the minimum value of all histogram fields:

[source,console-result]
--------------------------------------------------
{
  ...
  "aggregations": {
    "min_latency": {
      "value": 0.1
    }
  }
}
--------------------------------------------------
// TESTRESPONSE[skip:test not setup]