笔记三十八：Bucket & Metric 聚合分析及嵌套聚合

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Bucket & Metric Aggregation

Metric 一些系列的统计方法
Bucket 一组满足条件的文档

ES 笔记三十八：Bucket & Metric 聚合分析及嵌套聚合

Aggregation 的语法

Aggregation属于Search 的一部分。一般情况下，建议将其Size指定为0

ES 笔记三十八：Bucket & Metric 聚合分析及嵌套聚合

例子

ES 笔记三十八：Bucket & Metric 聚合分析及嵌套聚合

Mertric Aggregation

单值分析：只输出一个分析结果
- min，max，avg，sum
- Cardinality（类似 distinct Count）
多值分析：输出多个分析结果
- stats ,extended stats
- percentile, percentile rank
- top hits （排在前面的示例）

Metric 聚合的具体Demo

查看最低工资
查看最高工资
一个聚合输出多个值

一次查询包含多个聚合

同时查看最低最高和平均工资

PUT /employees/
{
"mappings" : {
"properties" : {
  "age" : {
    "type" : "integer"
  },
  "gender" : {
    "type" : "keyword"
  },
  "job" : {
    "type" : "text",
    "fields" : {
      "keyword" : {
        "type" : "keyword",
        "ignore_above" : 50
      }
    }
  },
  "name" : {
    "type" : "keyword"
  },
  "salary" : {
    "type" : "integer"
  }
}
}
}
PUT /employees/_bulk
{ "index" : {  "_id" : "1" } }
{ "name" : "Emma","age":32,"job":"Product Manager","gender":"female","salary":35000 }
{ "index" : {  "_id" : "2" } }
{ "name" : "Underwood","age":41,"job":"Dev Manager","gender":"male","salary": 50000}
{ "index" : {  "_id" : "3" } }
{ "name" : "Tran","age":25,"job":"Web Designer","gender":"male","salary":18000 }
{ "index" : {  "_id" : "4" } }
{ "name" : "Rivera","age":26,"job":"Web Designer","gender":"female","salary": 22000}
{ "index" : {  "_id" : "5" } }
{ "name" : "Rose","age":25,"job":"QA","gender":"female","salary":18000 }
{ "index" : {  "_id" : "6" } }
{ "name" : "Lucy","age":31,"job":"QA","gender":"female","salary": 25000}
{ "index" : {  "_id" : "7" } }
{ "name" : "Byrd","age":27,"job":"QA","gender":"male","salary":20000 }
{ "index" : {  "_id" : "8" } }
{ "name" : "Foster","age":27,"job":"Java Programmer","gender":"male","salary": 20000}
{ "index" : {  "_id" : "9" } }
{ "name" : "Gregory","age":32,"job":"Java Programmer","gender":"male","salary":22000 }
{ "index" : {  "_id" : "10" } }
{ "name" : "Bryant","age":20,"job":"Java Programmer","gender":"male","salary": 9000}
{ "index" : {  "_id" : "11" } }
{ "name" : "Jenny","age":36,"job":"Java Programmer","gender":"female","salary":38000 }
{ "index" : {  "_id" : "12" } }
{ "name" : "Mcdonald","age":31,"job":"Java Programmer","gender":"male","salary": 32000}
{ "index" : {  "_id" : "13" } }
{ "name" : "Jonthna","age":30,"job":"Java Programmer","gender":"female","salary":30000 }
{ "index" : {  "_id" : "14" } }
{ "name" : "Marshall","age":32,"job":"Javascript Programmer","gender":"male","salary": 25000}
{ "index" : {  "_id" : "15" } }
{ "name" : "King","age":33,"job":"Java Programmer","gender":"male","salary":28000 }
{ "index" : {  "_id" : "16" } }
{ "name" : "Mccarthy","age":21,"job":"Javascript Programmer","gender":"male","salary": 16000}
{ "index" : {  "_id" : "17" } }
{ "name" : "Goodwin","age":25,"job":"Javascript Programmer","gender":"male","salary": 16000}
{ "index" : {  "_id" : "18" } }
{ "name" : "Catherine","age":29,"job":"Javascript Programmer","gender":"female","salary": 20000}
{ "index" : {  "_id" : "19" } }
{ "name" : "Boone","age":30,"job":"DBA","gender":"male","salary": 30000}
{ "index" : {  "_id" : "20" } }
{ "name" : "Kathy","age":29,"job":"DBA","gender":"female","salary": 20000}
//查询
POST employees/_search
{
"size":0,
"aggs": {
"min": {
"min": {
  "field": "salary"
}
},
"max":{
"max" :{
  "field": "salary"
}
},
"avg":{
"avg": {
  "field": "salary"
}
}
}
}
//返回
{
"took" : 111,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 20,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"avg" : {
"value" : 24700.0
},
"min" : {
"value" : 9000.0
},
"max" : {
"value" : 50000.0
}
}
}
# 一个聚合，输出多值
POST employees/_search
{
"size": 0,
"aggs": {
"stats_salary": {
"stats": {
  "field":"salary"
}
}
}
}
//
"aggregations" : {
"stats_salary" : {
"count" : 20,
"min" : 9000.0,
"max" : 50000.0,
"avg" : 24700.0,
"sum" : 494000.0
}
}

Bucket

按照一定的规则，将文档分配到不同的桶中，从而达到分类的目的。ES提供的一些常见的Bucket Aggregation
- Term
- 数字类型
  - Range 、Date Range
  - Histogram / Data Histogram
支持嵌套：也就在桶里在做分桶

ES 笔记三十八：Bucket & Metric 聚合分析及嵌套聚合

Terms Aggregation

字段需要打开fielddata，才能进行Terms Aggregation
- Keyword 默认支持doc_values
- Text 需要在Mapping 中 enable ，会按照分词后的结果进行分

Demo

对job 和 job.keyword 进行聚合
对性别进行Terms聚合

指定bucket size

POST employees/_search
{
"size": 0,
"aggs": {
"jobs": {
"terms": {
  "field":"job.keyword"
}
}
}
}
//return 
"aggregations" : {
"jobs" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
  {
    "key" : "Java Programmer",
    "doc_count" : 7
  },
  {
    "key" : "Javascript Programmer",
    "doc_count" : 4
  },
  {
    "key" : "QA",
    "doc_count" : 3
  },
  {
    "key" : "DBA",
    "doc_count" : 2
  },
  {
    "key" : "Web Designer",
    "doc_count" : 2
  },
  {
    "key" : "Dev Manager",
    "doc_count" : 1
  },
  {
    "key" : "Product Manager",
    "doc_count" : 1
  }
]
}
}
# 对 Text 字段打开 fielddata，支持terms aggregation
PUT employees/_mapping
{
"properties" : {
  "job":{
     "type":     "text",
     "fielddata": true
  }
}
}
# 对 Text 字段进行 terms 分词。分词后的terms
POST employees/_search
{
"size": 0,
"aggs": {
  "jobs": {
    "terms": {
      "field":"job"
    }
  }
}
}
# 对job.keyword 和 job 进行 terms 聚合，分桶的总数并不一样
POST employees/_search
{
"size": 0,
"aggs": {
  "cardinate": {
    "cardinality": {
      "field": "job.keyword"
    }
  }
}
}
# 对 性别的 keyword 进行聚合
POST employees/_search
{
"size": 0,
"aggs": {
  "gender": {
    "terms": {
      "field":"gender"
    }
  }
}
}

Cardinality

类似SQL中的Distinct

Bucket Size & Top Hists Demo

应用场景：当后去分桶后，桶内最匹配的顶部文档列表
Size :按年龄分桶，找出指定数据量的分桶信息

Top Hits：查看各个工种中，年纪最大的3名员工

#指定 bucket 的 size
POST employees/_search
{
    "size": 0,
    "aggs": {
      "ages_5": {
        "terms": {
          "field":"age",
          "size":3
        }
      }
    }
}
# 指定size，不同工种中，年纪最大的3个员工的具体信息
POST employees/_search
{
"size": 0,
"aggs": {
  "jobs": {
    "terms": {
      "field": "job.keyword"
    },
  "aggs":{
    "old_employee":{
      "top_hits": {
        "size": 3,
        "sort": [{
          "age": {
            "order": "desc"
          }
        }]
      }
    }
  }
  }
}
}

优化Terms聚合的性能

在聚合经常发生，性能高的，索引不断写入

Range & Histogram

按照数字的范围，进行分桶
在Range Aggregation中，可以自定义Key

Demo：

按照工资的Range 分桶

按照工资的间隔（Histogram）分桶

//Salary Ranges 分桶，可以自己定义 key
POST employees/_search
{
"size": 0,
"aggs": {
"salary_range": {
"range": {
  "field":"salary",
  "ranges":[
    {
      "to":10000
    },
    {
      "from":10000,
      "to":20000
    },
    {
      "key":">20000",
      "from":20000
    }
  ]
}
}
}
}
//return 
"aggregations" : {
"salary_range" : {
"buckets" : [
  {
    "key" : "*-10000.0",
    "to" : 10000.0,
    "doc_count" : 1
  },
  {
    "key" : "10000.0-20000.0",
    "from" : 10000.0,
    "to" : 20000.0,
    "doc_count" : 4
  },
  {
    "key" : ">20000",
    "from" : 20000.0,
    "doc_count" : 15
  }
]
}
}
//Salary Histogram,工资0到10万，以 5000一个区间进行分桶
POST employees/_search
{
"size": 0,
"aggs": {
"salary_histrogram": {
"histogram": {
  "field":"salary",
  "interval":10000,
  "extended_bounds":{
    "min":0,
    "max":100000

  }
}
}
}
}

Bucket + Metric Aggregation

Bucket 聚合分析允许通过添加子聚合分析进一步分析，子聚合分析可以是
- Bucket
- Metric

Demo

按照工作类型进行分桶，并统计工资信息

先按照工作类型分桶，然后按性别分桶，并统计工资信息

# 嵌套聚合1，按照工作类型分桶，并统计工资信息
POST employees/_search
{
"size": 0,
"aggs": {
"Job_salary_stats": {
"terms": {
  "field": "job.keyword"
},
"aggs": {
  "salary": {
    "stats": {
      "field": "salary"
    }
  }
}
}
}
}
# 多次嵌套。根据工作类型分桶，然后按照性别分桶，计算工资的统计信息
POST employees/_search
{
"size": 0,
"aggs": {
  "Job_gender_stats": {
    "terms": {
      "field": "job.keyword"
    },
    "aggs": {
      "gender_stats": {
        "terms": {
          "field": "gender"
        },
        "aggs": {
          "salary_stats": {
            "stats": {
              "field": "salary"
            }
          }
        }
      }
    }
  }
}
}

总结

聚合分析的具体语法
- 一个聚合查询中可以包含多个聚合：每个Bucket聚合可以包含多个子聚合
Metrix
- 单值输出 & 多值输出
Bucket
- Terms & 数字范围

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笔记三十八：Bucket & Metric 聚合分析及嵌套聚合

Bucket & Metric Aggregation

Aggregation 的语法

例子

Mertric Aggregation

Metric 聚合的具体Demo

Bucket

Terms Aggregation

Cardinality

Bucket Size & Top Hists Demo

优化Terms聚合的性能

Range & Histogram

Bucket + Metric Aggregation

总结

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笔记三十八：Bucket & Metric 聚合分析及嵌套聚合

Bucket & Metric Aggregation

Aggregation 的语法

例子

Mertric Aggregation

Metric 聚合的具体Demo

Bucket

Terms Aggregation

Cardinality

Bucket Size & Top Hists Demo

优化Terms聚合的性能

Range & Histogram

Bucket + Metric Aggregation

总结

社区赞助商

关于 LearnKu

资源推荐

服务提供商

其他信息

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