Elasticsearch 7.x 【03】

主要內容：

聚合分析、嵌套聚合，下鑽分析的簡單操作

1、聚合分析

需求1：計算每個tag下的商品數量

執行語句：

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

執行後會報錯 

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. Alternatively use a keyword field instead

在ElasticSearch中默認fielddata默認是false的，因爲開啓Text的fielddata後對內存的佔用很高 

對tags字段開啓fielddata

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

注意：

索引地址不要寫錯，否則執行PUT操作會下面報錯，比如地址寫爲 [PUT ecommerce/_mapping]

{
  "error": {
    "root_cause": [
      {
        "type": "action_request_validation_exception",
        "reason": "Validation Failed: 1: mapping type is missing;"
      }
    ],
    "type": "action_request_validation_exception",
    "reason": "Validation Failed: 1: mapping type is missing;"
  },
  "status": 400
}

可以正常執行了，doc_count字段就是不同tag的document 數量

{
  "took" : 339,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 6,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
         ·········省略···········
    ]
  },
  "aggregations" : {
    "group_by_tags" : {
      "doc_count_error_upper_bound" : 0,
      "sum_other_doc_count" : 0,
      "buckets" : [
        {
          "key" : "fangzhu",
          "doc_count" : 4
        },
        {
          "key" : "meibai",
          "doc_count" : 2
        },
        {
          "key" : "qingxin",
          "doc_count" : 1
        }
      ]
    }
  }
}

tip 可以設置"size": 0只顯示聚合結果,如下所示

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

需求2：對名稱中包含jiajieshi的商品，計算每個tag下的商品數量

比較簡單，增加一個query功能，不列出結果了

GET ecommerce/_search
{
  "query": {
    "match": {
      "name": "jiajieshi"
    }
  }, 
  "aggs": {
    "group_by_tags": {
      "terms": {
        "field": "tags"
      }
    }
  }
}

2、嵌套聚合/下鑽分析

需求3：先分組，再算每組的平均值，計算每個tag下的商品的平均價格

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

返回的 avg_price就是我們需要的平均價格

{
  "took" : 2,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 6,
      "relation" : "eq"
    },
    "max_score" : null,
    "hits" : [ ]
  },
  "aggregations" : {
    "group_by_tags" : {
      "doc_count_error_upper_bound" : 0,
      "sum_other_doc_count" : 0,
      "buckets" : [
        {
          "key" : "fangzhu",
          "doc_count" : 4,
          "avg_price" : {
            "value" : 27.25
          }
        },
        {
          "key" : "meibai",
          "doc_count" : 2,
          "avg_price" : {
            "value" : 42.0
          }
        },
        {
          "key" : "qingxin",
          "doc_count" : 1,
          "avg_price" : {
            "value" : 40.0
          }
        }
      ]
    }
  }
}

需求4：計算每個tag下的商品的平均價格，並且按照平均價格降序排序

增加order字段

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

需求5：按照指定的價格範圍區間進行分組，然後在每組內再按照tag進行分組，最後再計算每組的平均價格

GET /ecommerce/_search
{
  "size": 0,
  "aggs": {
    "group_by_price": {
      "range": {
        "field": "price",
        "ranges": [
          {
            "from": 0,
            "to": 20
          },
          {
            "from": 20,
            "to": 40
          },
          {
            "from": 40,
            "to": 60
          }
        ]
      },
      "aggs": {
        "group_by_tags": {
          "terms": {
            "field": "tags",
            "order": {
              "avg_price": "desc"
            }
          },
          "aggs": {
            "avg_price": {
              "avg": {
                "field": "price"
              }
            }
          }
        }
      }
    }
  }
} 

返回結果

{
  "took" : 2,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 6,
      "relation" : "eq"
    },
    "max_score" : null,
    "hits" : [ ]
  },
  "aggregations" : {
    "group_by_price" : {
      "buckets" : [
        {
          "key" : "0.0-20.0",
          "from" : 0.0,
          "to" : 20.0,
          "doc_count" : 0,
          "group_by_tags" : {
            "doc_count_error_upper_bound" : 0,
            "sum_other_doc_count" : 0,
            "buckets" : [ ]
          }
        },
        {
          "key" : "20.0-40.0",
          "from" : 20.0,
          "to" : 40.0,
          "doc_count" : 4,
          "group_by_tags" : {
            "doc_count_error_upper_bound" : 0,
            "sum_other_doc_count" : 0,
            "buckets" : [
              {
                "key" : "meibai",
                "doc_count" : 1,
                "avg_price" : {
                  "value" : 34.0
                }
              },
              {
                "key" : "fangzhu",
                "doc_count" : 4,
                "avg_price" : {
                  "value" : 27.25
                }
              }
            ]
          }
        },
        {
          "key" : "40.0-60.0",
          "from" : 40.0,
          "to" : 60.0,
          "doc_count" : 2,
          "group_by_tags" : {
            "doc_count_error_upper_bound" : 0,
            "sum_other_doc_count" : 0,
            "buckets" : [
              {
                "key" : "meibai",
                "doc_count" : 1,
                "avg_price" : {
                  "value" : 50.0
                }
              },
              {
                "key" : "qingxin",
                "doc_count" : 1,
                "avg_price" : {
                  "value" : 40.0
                }
              }
            ]
          }
        }
      ]
    }
  }
}

3、更多內容參考

Elasticsearch筆記（七）：聚合查詢大數據佈道-CSDN博客
https://blog.csdn.net/alex_xfboy/article/details/86100037