搜索引擎（Elasticsearch聚合分析）

时间  2019-11-12
标签 搜索引擎 elasticsearch 聚合 分析 栏目 搜索引擎 繁體版
原文   原文链接

学习目标

掌握聚合分析的查询语法。
掌握指标聚合、桶聚合的用法html

聚合分析简介

ES聚合分析是什么？正则表达式

聚合分析是数据库中重要的功能特性，完成对一个查询的数据集中数据的聚合计算，如：找出某字段（或计算表达式的结果）的最大值、最小值，计算和、平均值等。ES做为搜索引擎兼数据库，一样提供了强大的聚合分析能力。数据库

对一个数据集求最大、最小、和、平均值等指标的聚合，在ES中称为指标聚合   metric
而关系型数据库中除了有聚合函数外，还能够对查询出的数据进行分组group by，再在组上进行指标聚合。在 ES 中group by 称为分桶，桶聚合  bucketingless

ES中还提供了矩阵聚合（matrix）、管道聚合（pipleline），但还在完善中。elasticsearch

ES聚合分析查询的写法ide

在查询请求体中以aggregations节点按以下语法定义聚合分析：函数

"aggregations" : {
    "<aggregation_name>" : {         //aggregations 也可简写为 aggs
        "<aggregation_type>" : {
            <aggregation_body>
        }
        [,"meta" : {  [<meta_data_body>] } ]?
        [,"aggregations" : { [<sub_aggregation>]+ } ]?
    }
    [,"<aggregation_name_2>" : { ... } ]*
}

聚合分析的值来源学习

聚合计算的值能够取字段的值，也但是脚本计算的结果。ui

 

指标聚合

max  min  sum  avg搜索引擎

POST /bank/_search?
{
  "size": 0, 
  "aggs": {
    "masssbalance": {
      "max": {
        "field": "balance"
      }
    }
  }
}
查询全部客户中余额的最大值
POST /bank/_search?
{
  "size": 2, 
  "query": {
    "match": {
      "age": 24
    }
  },
  "sort": [
    {
      "balance": {
        "order": "desc"
      }
    }
  ],
  "aggs": {
    "max_balance": {
      "max": {
        "field": "balance"
      }
    }
  }
}
年龄为24岁的客户中的余额最大值
POST /bank/_search?size=0
{
    "aggs" : {                   //值来源于脚本
        "avg_age" : {
            "avg" : {
                "script" : {    //查询全部客户的平均年龄是多少
                    "source" : "doc.age.value"
                }
            }
        },
        "avg_age10" : {
            "avg" : {
                "script" : {
                    "source" : "doc.age.value + 10"
                }
            }
        }
    }}
POST /bank/_search?size=0
{
  "aggs": {
    "sum_balance": {
      "sum": {
        "field": "balance",   //指定field，在脚本中用_value 取字段的值
        "script": {
            "source": "_value * 1.03"
        }
      }
    }
  }
}
POST /bank/_search?size=0
{
  "aggs": {
    "avg_age": {
      "avg": {
        "field": "age",
        "missing": 18
      }
    }  }}
POST /bank/_search?size=0
{
  "aggs": {
    "avg_age": {
      "avg": {
        "field": "age",    //为缺失值字段，指定值。如未指定，缺失该字段值的文档将被忽略。
        "missing": 18
      }
    }
  }
}

文档计数 count

POST /bank/_doc/_count
{
  "query": {
    "match": {
      "age" : 24
    }
  }
}

cardinality  值去重计数

POST /bank/_search?size=0
{
  "aggs": {
    "age_count": {
      "cardinality": {
        "field": "age"
      }
    },
    "state_count": {
      "cardinality": {
        "field": "state.keyword"
      }
    }
  }
}
state的使用它的keyword版

Value count 统计某字段有值的文档数

POST /bank/_search?size=0
{
    "aggs" : {
        "age_count" : { "value_count" : { "field" : "age" } }
    }
}

stats 统计 count max min avg sum 5个值

POST /bank/_search?size=0
{
  "aggs": {
    "age_stats": {
      "stats": {
        "field": "age"
      }
    }
  }
}

Extended stats

高级统计，比stats多4个统计结果： 平方和、方差、标准差、平均值加/减两个标准差的区间

POST /bank/_search?size=0
{
  "aggs": {
    "age_stats": {
      "extended_stats": {
        "field": "age"
      }
    }
  }

Percentiles 占比百分位对应的值统计

对指定字段（脚本）的值按从小到大累计每一个值对应的文档数的占比（占全部命中文档数的百分比），返回指定占比比例对应的值。默认返回[ 1, 5, 25, 50, 75, 95, 99 ]分位上的值。以下中间的结果，能够理解为：占比为50%的文档的age值 <= 31，或反过来：age<=31的文档数占总命中文档数的50%

POST /bank/_search?size=0
{
  "aggs": {
    "age_percents": {
      "percentiles": {
        "field": "age"
      }
    }
  }
}
"aggregations": {
    "age_percents": {
      "values": {
        "1.0": 20,
        "5.0": 21,
        "25.0": 25,
        "50.0": 31,
        "75.0": 35,
        "95.0": 39,
        "99.0": 40
      }
    }
  }
POST /bank/_search?size=0
{
  "aggs": {
    "age_percents": {
      "percentiles": {
        "field": "age",
        "percents" : [95, 99, 99.9] 
      }
    }
  }
}
指定分位值

Percentiles rank 统计值小于等于指定值的文档占比

POST /bank/_search?size=0
{
  "aggs": {
    "gge_perc_rank": {
      "percentile_ranks": {
        "field": "age",
        "values": [
          25,
          30
        ]
      }
    }
  }
}
"aggregations": {
    "gge_perc_rank": {
      "values": {
        "25.0": 26.1,
        "30.0": 49.3
      }
    }
  }

Geo Bounds aggregation 求文档集中的坐标点的范围

https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-metrics-geobounds-aggregation.html

Geo Centroid aggregation  求中心点坐标值

https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-metrics-geocentroid-aggregation.html

桶聚合

Terms Aggregation  根据字段值项分组聚合

POST /bank/_search?size=0
{
  "aggs": {
    "age_terms": {
      "terms": {
        "field": "age"
      }
    }
  }
}
"aggregations": {
    "age_terms": {
      "doc_count_error_upper_bound": 0,    //文档计数的最大误差值
      "sum_other_doc_count": 463,          //未返回的其余项的文档数
      "buckets": [                         //默认状况下返回按文档计数从高到低的前10个分组
        {
          "key": 31,
          "doc_count": 61
        },
        {
          "key": 39,
          "doc_count": 60
        },
        {
          "key": 26,
          "doc_count": 59
        },
        ….
       ]
    }
  }

size 指定返回多少个分组

POST /bank/_search?size=0
{
  "aggs": {
    "age_terms": {
      "terms": {
        "field": "age",
        "size": 20
      }
    }  }}
POST /bank/_search?size=0
{
  "aggs": {
    "age_terms": {
      "terms": {
        "field": "age",
        "size": 5,
        "shard_size":20    //shard_size 指定每一个分片上返回多少个分组
      }                   
    } }}                    
shard_size 的默认值为：
 索引只有一个分片：= size
多分片：=  size * 1.5 + 10
POST /bank/_search?size=0
{
  "aggs": {
    "age_terms": {
      "terms": {
        "field": "age",
        "size": 5,                       //每一个分组上显示误差值
        "shard_size":20,
        "show_term_doc_count_error": true
      }    }  }}

order  指定分组的排序

POST /bank/_search?size=0
{
  "aggs": {
    "age_terms": {
      "terms": {
        "field": "age",
        "order" : { "_count" : "asc" }   //根据文档计数排序
      }
    }
  }
}
POST /bank/_search?size=0
{
  "aggs": {
    "age_terms": {
      "terms": {
        "field": "age",
        "order" : { "_key" : "asc" }   //根据分组值排序
      }
    }
  }
}

取分组指标值

POST /bank/_search?size=0
{
  "aggs": {
    "age_terms": {
      "terms": {
        "field": "age",
        "order": {
          "max_balance": "asc"
        }
      },
      "aggs": {
        "max_balance": {
          "max": {
            "field": "balance"
          }
        },
        "min_balance": {
          "min": {
            "field": "balance"
          }
        }      }    }  }}

根据分组指标值排序

POST /bank/_search?size=0
{
  "aggs": {
    "age_terms": {
      "terms": {
        "field": "age",
        "order": {
          "max_balance": "asc"
        }
      },
      "aggs": {
        "max_balance": {
          "max": {
            "field": "balance"
          }
        }
      }
    }  }}
POST /bank/_search?size=0
{
  "aggs": {
    "age_terms": {
      "terms": {
        "field": "age",
        "order": {
          "stats_balance.max": "asc"
        }
      },
      "aggs": {
        "stats_balance": {
          "stats": {
            "field": "balance"
          }
        }
      }
    }  }}

筛选分组

POST /bank/_search?size=0
{
  "aggs": {
    "age_terms": {
      "terms": {
        "field": "age",
        "min_doc_count": 60   //用文档计数来筛选
      }
    }
  }
}
POST /bank/_search?size=0
{
  "aggs": {
    "age_terms": {
      "terms": {
        "field": "age",
        "include": [20,24]   //筛选指定的值列表
      }
    }
  }
}
GET /_search
{
    "aggs" : {
        "tags" : {
            "terms" : {
                "field" : "tags",
                "include" : ".*sport.*",
                "exclude" : "water_.*"     //正则表达式匹配值
            }
        }
    }
}
GET /_search
{
    "aggs" : {
        "JapaneseCars" : {
             "terms" : {
                 "field" : "make",
                 "include" : ["mazda", "honda"]
             }   
         },                               //指定值列表
        "ActiveCarManufacturers" : {
             "terms" : {
                 "field" : "make",
                 "exclude" : ["rover", "jensen"]
             }
         }
    }
}

根据脚本计算值分组

GET /_search
{
    "aggs" : {
        "genres" : {
            "terms" : {
                "script" : {
                    "source": "doc['genre'].value",
                    "lang": "painless"
                }
            }
        }
    }
}

缺失值处理

GET /_search
{
    "aggs" : {
        "tags" : {
             "terms" : {
                 "field" : "tags",
                 "missing": "N/A" 
             }
         }
    }
}

filter Aggregation  对知足过滤查询的文档进行聚合计算

在查询命中的文档中选取复合过滤条件的文档进行聚合

POST /bank/_search?size=0
{
  "aggs": {
    "age_terms": {
      "filter": {"match":{"gender":"F"}},
      "aggs": {
        "avg_age": {
          "avg": {
            "field": "age"
          }
        }
      }
    }
  }
}

Filters Aggregation  多个过滤组聚合计算

PUT /logs/_doc/_bulk?refresh
{ "index" : { "_id" : 1 } }
{ "body" : "warning: page could not be rendered" }
{ "index" : { "_id" : 2 } }
{ "body" : "authentication error" }
{ "index" : { "_id" : 3 } }
{ "body" : "warning: connection timed out" }

GET logs/_search
{
  "size": 0,
  "aggs" : {
    "messages" : {
      "filters" : {
        "filters" : {
          "errors" :   { "match" : { "body" : "error"   }},
          "warnings" : { "match" : { "body" : "warning" }}
        }
      }    }  }}
GET logs/_search
{
  "size": 0,
  "aggs" : {
    "messages" : {
      "filters" : {
        "other_bucket_key": "other_messages",
        "filters" : {
          "errors" :   { "match" : { "body" : "error"   }},
          "warnings" : { "match" : { "body" : "warning" }}
        }
      }    //为其余值组指定key
    }
  }
}

Range Aggregation  范围分组聚合

POST /bank/_search?size=0
{
  "aggs": {
    "age_range": {
      "range": {
        "field": "age",
        "ranges": [
          {"to":25},
          {"from": 25,"to": 35},
          {"from": 35}
        ]
      },
      "aggs": {
        "bmax": {
          "max": {
            "field": "balance"
          }
        }
      }    }  }}
POST /bank/_search?size=0
{
  "aggs": {
    "age_range": {
      "range": {
        "field": "age",
        "keyed": true, 
        "ranges": [
          {"to":25,"key": "Ld"},
          {"from": 25,"to": 35,"key": "Md"},
          {"from": 35,"key": "Od"}
        ]
      }
    }              //为组指定key
  }
}

Date Range Aggregation  时间范围分组聚合

POST /sales/_search?size=0
{
    "aggs": {
        "range": {
            "date_range": {
                "field": "date",
                "format": "MM-yyy",
                "ranges": [
                    { "to": "now-10M/M" }, 
                    { "from": "now-10M/M" } 
                ]
            }
        }
    }
}

Date Histogram Aggregation  时间直方图（柱状）聚合

就是按天、月、年等进行聚合统计。可按 year (1y), quarter (1q), month (1M), week (1w), day (1d), hour (1h), minute (1m), second (1s) 间隔聚合或指定的时间间隔聚合。

POST /sales/_search?size=0
{
    "aggs" : {
        "sales_over_time" : {
            "date_histogram" : {
                "field" : "date",
                "interval" : "month"
            }
        }
    }
}
POST /sales/_search?size=0
{
    "aggs" : {
        "sales_over_time" : {
            "date_histogram" : {
                "field" : "date",
                "interval" : "90m"
            }
        }
    }
}

Missing Aggregation  缺失值的桶聚合

缺失指定字段值的文档做为一个桶进行聚合分析

POST /bank/_search?size=0
{
    "aggs" : {
        "account_without_a_age" : {
            "missing" : { "field" : "age" }
        }
    }
}

Geo Distance Aggregation  地理距离分区聚合

https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-bucket-geodistance-aggregation.html

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