ElasticSearch入门ElastichSearchelasticsearch

七、Elasticsearch快速入门案例(3)-聚合分析

2017-07-01  本文已影响371人  编程界的小学生

1、解释说明:
聚合分析就是对应于数据库的聚合函数。
ES中用aggs标签

2、实战演练
需求1:计算所有商品的价格总和

GET /ecommerce/product/_search
{
  "aggs": {
    "sum_price": {
      "sum": {
        "field": "price"
      }
    }
  }
}

结果:

{
  "took": 3,
  "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": {
    "sum_price": {
      "value": 145
    }
  }
}

结果发现只有最后这部分是我们需要的,上面所有商品的记录我们不想输出,可以用size:0去控制,如下:

GET /ecommerce/product/_search
{
  "size": 0,
  "aggs": {
    "sum_price": {
      "sum": {
        "field": "price"
      }
    }
  }
}

输出结果:

{
  "took": 1,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 4,
    "max_score": 0,
    "hits": []
  },
  "aggregations": {
    "sum_price": {
      "value": 145
    }
  }
}

需求2:找出最贵的商品

GET /ecommerce/product/_search
{
  "size": 0,
  "aggs": {
    "max_price": {
      "max": {
        "field": "price"
      }
    }
  }
}

需求3:计算价钱的平均值

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

需求4:计算每个tag下的商品数量
需要用terms标签,需要先将所用字段正排索引下,否则报错
正排索引:

PUT /ecommerce/_mapping/product
{
  "properties": {
    "tags": {
      "type": "text",
      "fielddata": true
    }
  }
}
GET /ecommerce/product/_search
{
  "size": 0, 
  "aggs": {
    "group_by_tag" : {
      "terms": {
        "field": "tags"
      }
    }
  }
}

输出结果

{
  "took": 5,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 4,
    "max_score": 0,
    "hits": []
  },
  "aggregations": {
    "group_by_tag": {
      "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
        }
      ]
    }
  }
}

需求5: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
{
  "query": {
    "match": {
      "name": "yagao"
    }
  },
  "aggs": {
    "group_by_tags": {
      "terms": {
        "field": "tags"
      }
    }
  }
}

需求6:先按照tags分组,在计算每组的商品的平均价格

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

需求7:先按照tags分组,在计算每组的商品的平均价格,并按照价格倒序排序

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

需求8:按照指定的价格范围区间进行分组,然后在每组内再按照tags进行分组,最后在计算每组的平均价格

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

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