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  • Elasticsearch聚合分析

    预先设置

    在进行聚合分析的是皇后首先把文本的field的fielddata属性设置为true

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

     计算每个tag下的商品数量

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

     结果

    {
      "took": 11,
      "timed_out": false,
      "_shards": {
        "total": 5,
        "successful": 5,
        "failed": 0
      },
      "hits": {
        "total": 3,
        "max_score": 1,
        "hits": [
      ......
      "aggregations": {
        "group_by_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
            }
          ]
        }
      }
    }
    

     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": 22,
      "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" }
                    }
                }
            }
        }
    }
    

     结果

    {
      "took": 26,
      "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"
                  }
                }
              }
            }
          }
        }
      }
    }
    
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  • 原文地址:https://www.cnblogs.com/fmgao-technology/p/10410329.html
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