简单实例:聚合分析

分组聚合:计算每个tag下的商品数量

GET /ecommerce/product/_search
{
  "aggs": {
    "group_by_tags": {
      "terms": { "field": "tags" }
    }
  }
}

可以使用size参数设置为0 可以不显示检索到的文档

GET /ecommerce/product/_search
{
  "size": 0,
  "aggs": {
    "group_by_tags": {
      "terms": { "field": "tags" }
    }
  }
}

如果报以下错误 , 将文本field的fielddata属性设置为true,再次操作即可

{
  "error": {
    "root_cause": [
      {
        "type": "illegal_argument_exception",
        "reason": "Fielddata is disabled on text fields by default. Set fielddata=true on [tags] in order to load fielddata in memory by uninverting the inverted index. Note that this can however use significant memory."
      }
    ],
    "type": "search_phase_execution_exception",
    "reason": "all shards failed",
    "phase": "query",
    "grouped": true,
    "failed_shards": [
      {
        "shard": 0,
        "index": "ecommerce",
        "node": "7bJsCFK-QlalolMWGqOoxA",
        "reason": {
          "type": "illegal_argument_exception",
          "reason": "Fielddata is disabled on text fields by default. Set fielddata=true on [tags] in order to load fielddata in memory by uninverting the inverted index. Note that this can however use significant memory."
        }
      }
    ],
    "caused_by": {
      "type": "illegal_argument_exception",
      "reason": "Fielddata is disabled on text fields by default. Set fielddata=true on [tags] in order to load fielddata in memory by uninverting the inverted index. Note that this can however use significant memory."
    }
  },
  "status": 400
}

具体操作

PUT /ecommerce/_mapping/product
{
  "properties": {
    "tags": {
      "type": "text",
      "fielddata": true
    }
  }
}

返回结果如下:

{
  "took": 28,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 3,
    "max_score": 0,
    "hits": []
  },
  "aggregations": {
    "all_tags": {
      "doc_count_error_upper_bound": 0,
      "sum_other_doc_count": 0,
      "buckets": [
        {
          "key": "fangzhu",
          "doc_count": 2
        },
        {
          "key": "meibai",
          "doc_count": 1
        },
        {
          "key": "qingxin",
          "doc_count": 1
        }
      ]
    }
  }
}

对名称中包含yagao的商品，计算每个tag下的商品数量

GET /ecommerce/product/_search
{
  "size": 0,
  "query": {
    "match": {
      "name": "yagao"
    }
  },
  "aggs": {
    "all_tags": {
      "terms": {
        "field": "tags"
      }
    }
  }
}

先分组，再算每组的平均值，计算每个tag下的商品的平均价格

GET /ecommerce/product/_search
{
    "size": 0,
    "aggs" : {
        "group_by_tags" : {
            "terms" : { "field" : "tags" },
            "aggs" : {
                "avg_price" : {
                    "avg" : { "field" : "price" }
                }
            }
        }
    }
}

结果:

{
  "took": 49,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 3,
    "max_score": 0,
    "hits": []
  },
  "aggregations": {
    "group_by_tags": {
      "doc_count_error_upper_bound": 0,
      "sum_other_doc_count": 0,
      "buckets": [
        {
          "key": "fangzhu",
          "doc_count": 2,
          "avg_price": {
            "value": 27.5
          }
        },
        {
          "key": "meibai",
          "doc_count": 1,
          "avg_price": {
            "value": 30
          }
        },
        {
          "key": "qingxin",
          "doc_count": 1,
          "avg_price": {
            "value": 40
          }
        }
      ]
    }
  }
}

计算每个tag下的商品的平均价格，并且按照平均价格降序排序

GET /ecommerce/product/_search
{
    "size": 0,
    "aggs" : {
        "all_tags" : {
            "terms" : { "field" : "tags", "order": { "avg_price": "desc" } },
            "aggs" : {
                "avg_price" : {
                    "avg" : { "field" : "price" }
                }
            }
        }
    }
}

返回结果:

{
  "took": 41,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 3,
    "max_score": 0,
    "hits": []
  },
  "aggregations": {
    "all_tags": {
      "doc_count_error_upper_bound": 0,
      "sum_other_doc_count": 0,
      "buckets": [
        {
          "key": "qingxin",
          "doc_count": 1,
          "avg_price": {
            "value": 40
          }
        },
        {
          "key": "meibai",
          "doc_count": 1,
          "avg_price": {
            "value": 30
          }
        },
        {
          "key": "fangzhu",
          "doc_count": 2,
          "avg_price": {
            "value": 27.5
          }
        }
      ]
    }
  }
}

按照指定的价格范围区间进行分组，然后在每组内再按照tag进行分组，最后再计算每组的平均价格

GET /ecommerce/product/_search
{
  "size": 0,
  "aggs": {
    "group_by_price": {
      "range": {
        "field": "price",
        "ranges": [
          {
            "from": 0,
            "to": 20
          },
          {
            "from": 20,
            "to": 40
          },
          {
            "from": 40,
            "to": 50
          }
        ]
      },
      "aggs": {
        "group_by_tags": {
          "terms": {
            "field": "tags"
          },
          "aggs": {
            "average_price": {
              "avg": {
                "field": "price"
              }
            }
          }
        }
      }
    }
  }
}

返回结果:

{
  "took": 46,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 3,
    "max_score": 0,
    "hits": []
  },
  "aggregations": {
    "group_by_price": {
      "buckets": [
        {
          "key": "0.0-20.0",
          "from": 0,
          "to": 20,
          "doc_count": 0,
          "group_by_tags": {
            "doc_count_error_upper_bound": 0,
            "sum_other_doc_count": 0,
            "buckets": []
          }
        },
        {
          "key": "20.0-40.0",
          "from": 20,
          "to": 40,
          "doc_count": 2,
          "group_by_tags": {
            "doc_count_error_upper_bound": 0,
            "sum_other_doc_count": 0,
            "buckets": [
              {
                "key": "fangzhu",
                "doc_count": 2,
                "average_price": {
                  "value": 27.5
                }
              },
              {
                "key": "meibai",
                "doc_count": 1,
                "average_price": {
                  "value": 30
                }
              }
            ]
          }
        },
        {
          "key": "40.0-50.0",
          "from": 40,
          "to": 50,
          "doc_count": 1,
          "group_by_tags": {
            "doc_count_error_upper_bound": 0,
            "sum_other_doc_count": 0,
            "buckets": [
              {
                "key": "qingxin",
                "doc_count": 1,
                "average_price": {
                  "value": 40
                }
              }
            ]
          }
        }
      ]
    }
  }
}