7、Elasticsearch快速入门_Elasticsearc

第一个分析需求：计算每个tag下的商品数量

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

结果出现这种错误

解决方式：将fielddata设置为true
PUT /ecommerce/_mapping/product
{
  "properties": {
    "tags": {
      "type": "text",
      "fielddata": true
    }
  }
}
-------------------------------------------------------------------------------------------------
设置fielddata为true后查询结果：
{
  "took": 9,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 4,
    "max_score": 1,
    "hits": [
      {
        "_index": "ecommerce",
        "_type": "product",
        "_id": "2",
        "_score": 1,
        "_source": {
          "name": "jiajieshi yagao",
          "desc": "youxiao fangzhu",
          "price": 25,
          "producer": "jiajieshi producer",
          "tags": [
            "fangzhu"
          ]
        }
      },
      {
        "_index": "ecommerce",
        "_type": "product",
        "_id": "4",
        "_score": 1,
        "_source": {
          "name": "special yagao",
          "desc": "special meibai",
          "price": 50,
          "producer": "special yagao producer",
          "tags": [
            "meibai"
          ]
        }
      },
      {
        "_index": "ecommerce",
        "_type": "product",
        "_id": "1",
        "_score": 1,
        "_source": {
          "name": "gaolujie yagao",
          "desc": "gaoxiao meibai",
          "price": 30,
          "producer": "gaolujie producer",
          "tags": [
            "meibai",
            "fangzhu"
          ]
        }
      },
      {
        "_index": "ecommerce",
        "_type": "product",
        "_id": "3",
        "_score": 1,
        "_source": {
          "name": "zhonghua yagao",
          "desc": "caoben zhiwu",
          "price": 40,
          "producer": "zhonghua producer",
          "tags": [
            "qingxin"
          ]
        }
      }
    ]
  },
  "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": 2
        },
        {
          "key": "qingxin",
          "doc_count": 1
        }
      ]
    }
  }
}

以上结果有其他数据，精简结果，设置size：0
GET /ecommerce/product/_search
{
  "size": 0, 
  "aggs": {
    "group_by_tags": {
      "terms": {
        "field": "tags"
      }
    }
  }
}

查询结果

第二个聚合分析的需求：对名称中包含yagao的商品，计算每个tag下的商品数量

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

对名称中包含yagao的商品，计算每个tag下的商品数量

第三个聚合分析的需求：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"
          }
        }
      }
    } 
  }
}

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

第四个数据分析需求：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": 20,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 4,
    "max_score": 0,
    "hits": []
  },
  "aggregations": {
    "all_tags": {
      "doc_count_error_upper_bound": 0,
      "sum_other_doc_count": 0,
      "buckets": [
        {
          "key": "meibai",
          "doc_count": 2,
          "avg_price": {
            "value": 40
          }
        },
        {
          "key": "qingxin",
          "doc_count": 1,
          "avg_price": {
            "value": 40
          }
        },
        {
          "key": "fangzhu",
          "doc_count": 2,
          "avg_price": {
            "value": 27.5
          }
        }
      ]
    }
  }
}

第五个数据分析需求：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": 60
          }
        ]
      },
      "aggs": {
        "group_by_tags": {
          "terms": {
            "field": "tags"
          }
          , "aggs": {
            "avg_price": {
              "avg": {
                "field": "price"
              }
            }
          }
        }
      }
    }
  }
}
-------------------------------------------------------------------------------------------------
结果：
{
  "took": 6,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 4,
    "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,
                "avg_price": {
                  "value": 27.5
                }
              },
              {
                "key": "meibai",
                "doc_count": 1,
                "avg_price": {
                  "value": 30
                }
              }
            ]
          }
        },
        {
          "key": "40.0-60.0",
          "from": 40,
          "to": 60,
          "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
                }
              },
              {
                "key": "qingxin",
                "doc_count": 1,
                "avg_price": {
                  "value": 40
                }
              }
            ]
          }
        }
      ]
    }
  }
}