# 一个例子：Pipeline： min_bucket

• 在员工数最多的工种里，找出平均工资最低的工种

# Pipeline

• 管道的概念：支持对聚合分析的结果，再次进行聚合分析
• Pipeline的分析结果会输出到原结果汇总，根据位置的不同，分为两类
• Sibling - 结果和现有分析结果同级
• Max，min，Avg&Sum Bucket
• Stats ， Extened Status Bucket
• Percentiles Bucket
• Parent - 结果内嵌到现有的聚合分析结果之中
• Derivative（求导）
• Cumultive Sum（累计求和）
• Moving Function（滑动窗口）

# Sibling Pipeline 的例子

• 对不同类型工作的，平均工资
• 求最大
• 平均
• 统计信息
• 百分位数
``````//插入数据
DELETE employees
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}``````
``````# 平均工资最低的工作类型
POST employees/_search
{
"size": 0,
"aggs": {
"jobs": {
"terms": {
"field": "job.keyword",
"size": 10
},
"aggs": {
"avg_salary": {
"avg": {
"field": "salary"
}
}
}
},
"min_salary_by_job": {
"min_bucket": {
"buckets_path": "jobs>avg_salary"
}
}
}
}
# 平均工资最高的工作类型
POST employees/_search
{
"size": 0,
"aggs": {
"jobs": {
"terms": {
"field": "job.keyword",
"size": 10
},
"aggs": {
"avg_salary": {
"avg": {
"field": "salary"
}
}
}
},
"max_salary_by_job":{
"max_bucket": {
"buckets_path": "jobs>avg_salary"
}
}
}
}
# 平均工资的平均工资
POST employees/_search
{
"size": 0,
"aggs": {
"jobs": {
"terms": {
"field": "job.keyword",
"size": 10
},
"aggs": {
"avg_salary": {
"avg": {
"field": "salary"
}
}
}
},
"avg_salary_by_job":{
"avg_bucket": {
"buckets_path": "jobs>avg_salary"
}
}
}
}``````

# Parent Pipeline ： Derivative

• 按年龄、对工资进行求导（看工资发展的趋势）
``````#按照年龄对平均工资求导
POST employees/_search
{
"size": 0,
"aggs": {
"age": {
"histogram": {
"field": "age",
"min_doc_count": 1,
"interval": 1
},
"aggs": {
"avg_salary": {
"avg": {
"field": "salary"
}
},
"derivative_avg_salary":{
"derivative": {
"buckets_path": "avg_salary"
}
}
}
}
}
}
//return
"aggregations" : {
"age" : {
"buckets" : [
{
"key" : 20.0,
"doc_count" : 1,
"avg_salary" : {
"value" : 9000.0
}
},
{
"key" : 21.0,
"doc_count" : 1,
"avg_salary" : {
"value" : 16000.0
},
"derivative_avg_salary" : {
"value" : 7000.0
}
}
]
}``````

# Parent Pipeline

• 年龄直方图划分的平均工资
• Cumulative Sum
• Moving Function
``````#Cumulative_sum
POST employees/_search
{
"size": 0,
"aggs": {
"age": {
"histogram": {
"field": "age",
"min_doc_count": 1,
"interval": 1
},
"aggs": {
"avg_salary": {
"avg": {
"field": "salary"
}
},
"cumulative_salary":{
"cumulative_sum": {
"buckets_path": "avg_salary"
}
}
}
}
}
}

#Moving Function
POST employees/_search
{
"size": 0,
"aggs": {
"age": {
"histogram": {
"field": "age",
"min_doc_count": 1,
"interval": 1
},
"aggs": {
"avg_salary": {
"avg": {
"field": "salary"
}
},
"moving_avg_salary":{
"moving_fn": {
"buckets_path": "avg_salary",
"window":10,
"script": "MovingFunctions.min(values)"
}
}
}
}
}
}``````

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