平均聚合 #

avg 指标是一个单值指标，它返回某个字段的平均值。

参数说明 #

avg 聚合采用以下参数。

参考样例 #

以下示例请求计算示例数据中 taxful_total_price 字段的平均值：

GET sample_data_ecommerce/_search
{
  "size": 0,
  "aggs": {
    "avg_taxful_total_price": {
      "avg": {
        "field": "taxful_total_price"
      }
    }
  }
}

返回内容 #

返回内容包含 taxful_total_price 的平均值：

{
  "took": 85,
  "timed_out": false,
  "_shards": {
    "total": 1,
    "successful": 1,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": {
      "value": 4675,
      "relation": "eq"
    },
    "max_score": null,
    "hits": []
  },
  "aggregations": {
    "avg_taxful_total_price": {
      "value": 75.05542864304813
    }
  }
}

可以使用聚合名称 avg_taxful_total_price 作为从聚合获取结果的键名。

缺失值处理 #

通过提取以下文档来准备示例索引。请注意，第二个文档缺少 gpa 值：

POST _bulk
{ "create": { "_index": "students", "_id": "1" } }
{ "name": "John Doe", "gpa": 3.89, "grad_year": 2022}
{ "create": { "_index": "students", "_id": "2" } }
{ "name": "Jonathan Powers", "grad_year": 2025 }
{ "create": { "_index": "students", "_id": "3" } }
{ "name": "Jane Doe", "gpa": 3.52, "grad_year": 2024 }

示例：替换缺失值 #

取平均值，将缺失的 GPA 字段替换为 0 ：

GET students/_search
{
  "size": 0,
  "aggs": {
    "avg_gpa": {
      "avg": {
        "field": "gpa",
        "missing": 0
      }
    }
  }
}

返回内容如下。可以与下一个忽略了缺失值的示例做个比较：

{
  "took": 12,
  "timed_out": false,
  "_shards": {
    "total": 1,
    "successful": 1,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": {
      "value": 3,
      "relation": "eq"
    },
    "max_score": null,
    "hits": []
  },
  "aggregations": {
    "avg_gpa": {
      "value": 2.4700000286102295
    }
  }
}

示例：忽略缺失值 #

取平均值但不分配 missing 参数：

GET students/_search
{
  "size": 0,
  "aggs": {
    "avg_gpa": {
      "avg": {
        "field": "gpa"
      }
    }
  }
}

聚合器计算平均值，省略包含缺失字段值的文档（默认行为）：

{
  "took": 255,
  "timed_out": false,
  "_shards": {
    "total": 1,
    "successful": 1,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": {
      "value": 3,
      "relation": "eq"
    },
    "max_score": null,
    "hits": []
  },
  "aggregations": {
    "avg_gpa": {
      "value": 3.7050000429153442
    }
  }
}