ES基础(三十七)Bucket & Metric Aggregation
demos
DELETE /employees 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} # Metric 聚合,找到最低的工资 POST employees/_search { "size": 0, "aggs": { "min_salary": { "min": { "field":"salary" } } } } # Metric 聚合,找到最高的工资 POST employees/_search { "size": 0, "aggs": { "max_salary": { "max": { "field":"salary" } } } } # 多个 Metric 聚合,找到最低最高和平均工资 POST employees/_search { "size": 0, "aggs": { "max_salary": { "max": { "field": "salary" } }, "min_salary": { "min": { "field": "salary" } }, "avg_salary": { "avg": { "field": "salary" } } } } # 一个聚合,输出多值 POST employees/_search { "size": 0, "aggs": { "stats_salary": { "stats": { "field":"salary" } } } } # 对keword 进行聚合 POST employees/_search { "size": 0, "aggs": { "jobs": { "terms": { "field":"job.keyword" } } } } # 对 Text 字段进行 terms 聚合查询,失败 POST employees/_search { "size": 0, "aggs": { "jobs": { "terms": { "field":"job" } } } } # 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" } } } } POST employees/_search { "size": 0, "aggs": { "jobs": { "terms": { "field":"job.keyword" } } } } # 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" } } } } # 对 性别的 keyword 进行聚合 POST employees/_search { "size": 0, "aggs": { "gender": { "terms": { "field":"gender" } } } } #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" } } ] } } } } } } #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 } ] } } } } #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":5000, "extended_bounds":{ "min":0, "max":100000 } } } } } # 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" } } } } } } } }
本文来自博客园,作者:秋华,转载请注明原文链接:https://www.cnblogs.com/qiu-hua/p/14197722.html