ElasticSearch(四)：Filter查询、聚合查询

梦里梦外; 2023-05-21 15:18 29阅读 0赞

# 1. 简述 #

Filter查询时不计算相关性的，同时可以进行缓存，因此，Filter查询的速度要快于query查询；

# 2. 数据准备 #

POST /lib9/items/_bulk
    {"index": {"id": 1}}
    {"price": 40,"itemID": "ID100123"}
    {"index": {"_id": 2}}
    {"price": 50,"itemID": "ID100124"}
    {"index": {"_id": 3}}
    {"price": 25,"itemID": "ID100124"}
    {"index": {"_id": 4}}
    {"price": 30,"itemID": "ID100125"}
    {"index": {"_id": 5}}
    {"price": null,"itemID": "ID100127"}

# 3. filter查询 #

## 3.1 简单过滤查询 ##

# 查询price=40的文档
    GET /lib9/items/_search
    {
      "post_filter": {
        "term": {
          "price": 40
        }
      }
    }
    
    # 查询price等于25或40的文档
    GET /lib9/items/_search
    {
      "post_filter": {
        "terms": {
          "price": [
            25,
            40
          ]
        }
      }
    }
    
    # 查询itemID等于ID100123的文档(注意在这里要写成小写id)
    GET /lib9/items/_search
    {
      "post_filter": {
        "term": {
          "itemID": "id100123"
        }
      }
    }

## 3.2 bool过滤查询 ##

可以实现组合过滤查询

# 格式
    {
        "bool": {
            "must": [],
            "should": [],
            "must_not": []
        }
    }

**注意**  
**1. must：必须要满足的条件 --and  
2. should： 可以满足也可以不满足的条件 --or  
3. must\_not：不需要满足的条件 --not**

GET /lib9/items/_search
    {
      "post_filter": {
        "bool": {
          "should": [
            {
              "term": {
                "price": 25
              }
            },
            {
              "term": {
                "itemID": "id100123"
              }
            }
          ],
          "must_not": [
            {
              "term": {
                "price": 30
              }
            }
          ]
        }
      }
    }

GET /lib9/items/_search
    {
      "post_filter": {
        "bool": {
          "should": [
            {
              "term": {
                "itemID": "id100123"
              }
            },
            {
              "bool": {
                "must": [
                  {
                    "term": {
                      "itemID": "id100124"
                    }
                  },
                  {
                    "term": {
                      "price": 40
                    }
                  }
                ]
              }
            }
          ]
        }
      }
    }

## 3.3 range范围过滤 ##

gt：>  
lt：<  
gte：>=  
lte：<=

GET /lib9/items/_search
    {
      "post_filter": {
        "range": {
          "price": {
            "gt": 35,
            "lt": 50
          }
        }
      }
    }

## 3.4 过滤非空 ##

GET /lib9/items/_search
    {
      "query": {
        "bool": {
          "filter": {
            "exists": {
              "field": "price"
            }
          }
        }
      }
    }
    
    GET /lib9/items/_search
    {
      "query": {
        "constant_score": {
          "filter": {
            "exists": {
              "field": "price"
            }
          }
        }
      }
    }

## 3.5 过滤器缓存 ##

ElasticSearch有一种特殊的缓存，即过滤器缓存(filter cache)，用来存储过滤器的结果，被缓存的过滤器并不需要消耗过多的内存，而且可供后续所有与之相关的查询重复使用，从而极大地提高了查询性能。  
注意：ElasticSearch并不是默认缓存所有过滤器，

1.  以下过滤器默认不缓存：

numeric_range
    script
    geo_bbox
    geo_distance
    geo_distance_range
    geo_polygon
    geo_shape
    and
    or
    not

1.  以下过滤器默认开启缓存

exists
    missing
    range
    term
    terms

1.  开启方式：在filter查询语句后边加上 “\_catch”:true

# 4. 聚合查询 #

1.  sum

GET /lib9/items/_search
    {
      "size":0,
      "aggs": {
         "price_of_sum": {
             "sum": {
               "field": "price"
             }
         }
      }
    }

运行结果

{
      "took": 6,
      "timed_out": false,
      "_shards": {
        "total": 5,
        "successful": 5,
        "skipped": 0,
        "failed": 0
      },
      "hits": {
        "total": 5,
        "max_score": 0,
        "hits": []
      },
      "aggregations": {
        "price_of_sum": {
          "value": 160
        }
      }
    }

1.  min

GET /lib9/items/_search
    {
      "size": 0,
      "aggs": {
        "price_of_min": {
          "min": {
            "field": "price"
          }
        }
      }
    }

运行结果

{
      "took": 4,
      "timed_out": false,
      "_shards": {
        "total": 5,
        "successful": 5,
        "skipped": 0,
        "failed": 0
      },
      "hits": {
        "total": 5,
        "max_score": 0,
        "hits": []
      },
      "aggregations": {
        "price_of_min": {
          "value": 30
        }
      }
    }

1.  max、avg同上
2.  terms：分组

GET /lib9/items/_search
    {
      "size": 0,
      "aggs": {
        "price_group_by": {
          "terms": {
            "field": "price"
          }
        }
      }
    }