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Elastic Docs ›Elasticsearch Guide [8.15] ›Aggregations ›Metrics aggregations

Max aggregation

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Max aggregation

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

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 max price value across all documents

resp = client.search(
    index="sales",
    size="0",
    aggs={
        "max_price": {
            "max": {
                "field": "price"
            }
        }
    },
)
print(resp)
response = client.search(
  index: 'sales',
  size: 0,
  body: {
    aggregations: {
      max_price: {
        max: {
          field: 'price'
        }
      }
    }
  }
)
puts response
const response = await client.search({
  index: "sales",
  size: 0,
  aggs: {
    max_price: {
      max: {
        field: "price",
      },
    },
  },
});
console.log(response);
POST /sales/_search?size=0
{
  "aggs": {
    "max_price": { "max": { "field": "price" } }
  }
}

Response:

{
  ...
  "aggregations": {
      "max_price": {
          "value": 200.0
      }
  }
}

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

Script

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If you need to get the max of something more complex than a single field, run an aggregation on a runtime field.

resp = client.search(
    index="sales",
    size=0,
    runtime_mappings={
        "price.adjusted": {
            "type": "double",
            "script": "\n        double price = doc['price'].value;\n        if (doc['promoted'].value) {\n          price *= 0.8;\n        }\n        emit(price);\n      "
        }
    },
    aggs={
        "max_price": {
            "max": {
                "field": "price.adjusted"
            }
        }
    },
)
print(resp)
response = client.search(
  index: 'sales',
  body: {
    size: 0,
    runtime_mappings: {
      'price.adjusted' => {
        type: 'double',
        script: "\n        double price = doc['price'].value;\n        if (doc['promoted'].value) {\n          price *= 0.8;\n        }\n        emit(price);\n      "
      }
    },
    aggregations: {
      max_price: {
        max: {
          field: 'price.adjusted'
        }
      }
    }
  }
)
puts response
const response = await client.search({
  index: "sales",
  size: 0,
  runtime_mappings: {
    "price.adjusted": {
      type: "double",
      script:
        "\n        double price = doc['price'].value;\n        if (doc['promoted'].value) {\n          price *= 0.8;\n        }\n        emit(price);\n      ",
    },
  },
  aggs: {
    max_price: {
      max: {
        field: "price.adjusted",
      },
    },
  },
});
console.log(response);
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": {
    "max_price": {
      "max": { "field": "price.adjusted" }
    }
  }
}

Missing value

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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.

resp = client.search(
    index="sales",
    aggs={
        "grade_max": {
            "max": {
                "field": "grade",
                "missing": 10
            }
        }
    },
)
print(resp)
response = client.search(
  index: 'sales',
  body: {
    aggregations: {
      grade_max: {
        max: {
          field: 'grade',
          missing: 10
        }
      }
    }
  }
)
puts response
const response = await client.search({
  index: "sales",
  aggs: {
    grade_max: {
      max: {
        field: "grade",
        missing: 10,
      },
    },
  },
});
console.log(response);
POST /sales/_search
{
  "aggs" : {
      "grade_max" : {
          "max" : {
              "field" : "grade",
              "missing": 10       
          }
      }
  }
}

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

Histogram fields

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When max is computed on histogram fields, the result of the aggregation is the maximum 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:

resp = client.indices.create(
    index="metrics_index",
    mappings={
        "properties": {
            "latency_histo": {
                "type": "histogram"
            }
        }
    },
)
print(resp)

resp1 = client.index(
    index="metrics_index",
    id="1",
    refresh=True,
    document={
        "network.name": "net-1",
        "latency_histo": {
            "values": [
                0.1,
                0.2,
                0.3,
                0.4,
                0.5
            ],
            "counts": [
                3,
                7,
                23,
                12,
                6
            ]
        }
    },
)
print(resp1)

resp2 = client.index(
    index="metrics_index",
    id="2",
    refresh=True,
    document={
        "network.name": "net-2",
        "latency_histo": {
            "values": [
                0.1,
                0.2,
                0.3,
                0.4,
                0.5
            ],
            "counts": [
                8,
                17,
                8,
                7,
                6
            ]
        }
    },
)
print(resp2)

resp3 = client.search(
    index="metrics_index",
    size="0",
    filter_path="aggregations",
    aggs={
        "max_latency": {
            "max": {
                "field": "latency_histo"
            }
        }
    },
)
print(resp3)
response = client.indices.create(
  index: 'metrics_index',
  body: {
    mappings: {
      properties: {
        latency_histo: {
          type: 'histogram'
        }
      }
    }
  }
)
puts response

response = client.index(
  index: 'metrics_index',
  id: 1,
  refresh: true,
  body: {
    'network.name' => 'net-1',
    latency_histo: {
      values: [
        0.1,
        0.2,
        0.3,
        0.4,
        0.5
      ],
      counts: [
        3,
        7,
        23,
        12,
        6
      ]
    }
  }
)
puts response

response = client.index(
  index: 'metrics_index',
  id: 2,
  refresh: true,
  body: {
    'network.name' => 'net-2',
    latency_histo: {
      values: [
        0.1,
        0.2,
        0.3,
        0.4,
        0.5
      ],
      counts: [
        8,
        17,
        8,
        7,
        6
      ]
    }
  }
)
puts response

response = client.search(
  index: 'metrics_index',
  size: 0,
  filter_path: 'aggregations',
  body: {
    aggregations: {
      max_latency: {
        max: {
          field: 'latency_histo'
        }
      }
    }
  }
)
puts response
const response = await client.indices.create({
  index: "metrics_index",
  mappings: {
    properties: {
      latency_histo: {
        type: "histogram",
      },
    },
  },
});
console.log(response);

const response1 = await client.index({
  index: "metrics_index",
  id: 1,
  refresh: "true",
  document: {
    "network.name": "net-1",
    latency_histo: {
      values: [0.1, 0.2, 0.3, 0.4, 0.5],
      counts: [3, 7, 23, 12, 6],
    },
  },
});
console.log(response1);

const response2 = await client.index({
  index: "metrics_index",
  id: 2,
  refresh: "true",
  document: {
    "network.name": "net-2",
    latency_histo: {
      values: [0.1, 0.2, 0.3, 0.4, 0.5],
      counts: [8, 17, 8, 7, 6],
    },
  },
});
console.log(response2);

const response3 = await client.search({
  index: "metrics_index",
  size: 0,
  filter_path: "aggregations",
  aggs: {
    max_latency: {
      max: {
        field: "latency_histo",
      },
    },
  },
});
console.log(response3);
PUT metrics_index
{
  "mappings": {
    "properties": {
      "latency_histo": { "type": "histogram" }
    }
  }
}

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

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

POST /metrics_index/_search?size=0&filter_path=aggregations
{
  "aggs" : {
    "max_latency" : { "max" : { "field" : "latency_histo" } }
  }
}

The max aggregation will return the maximum value of all histogram fields:

{
  "aggregations": {
    "max_latency": {
      "value": 0.5
    }
  }
}
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