ES的聚合操作
构建数据：
@Test
public void createIndex(){
/**
* 创建索引
* */
client.admin().indices().prepareCreate("player").get();
}
/**
* 创建映射
*/
@Test
public void testCreateIndexMapping_boost() throws Exception{
/**
* 格式：
"mappings": {
"player": {
"properties": {
"name": {"index": "not_analyzed","type": "string"},
"age": {"type": "integer"},
"salary": {"type": "integer"},
"team": {"index": "not_analyzed","type": "string"},
"position": {"index": "not_analyzed","type": "string"}
}
}
}
*/
//构建json的数据格式，创建映射
XContentBuilder mappingBuilder = XContentFactory.jsonBuilder()
.startObject()
.startObject("player")
.startObject("properties")
.startObject("name").field("type","string").field("index", "not_analyzed").endObject()
.startObject("age").field("type","integer").endObject()
.startObject("salary").field("type","integer").endObject()
.startObject("team").field("type","string").field("index", "not_analyzed").endObject()
.startObject("position").field("type","string").field("index", "not_analyzed").endObject()
.endObject()
.endObject()
.endObject();
PutMappingRequest request = Requests.putMappingRequest("player")
.type("player")
.source(mappingBuilder);
client.admin().indices().putMapping(request).get();
}
@Test
public void BulkInsertDocument() throws IOException {
BulkRequestBuilder bulkRequest = client.prepareBulk();
// either use client#prepare, or use Requests# to directly build index/delete requests
bulkRequest.add(client.prepareIndex("player", "player", "1")
.setSource(jsonBuilder()
.startObject()
.field("name", "郭德纲")
.field("age", 33)
.field("salary",3000)
.field("team" , "cav")
.field("position" , "sf")
.endObject()
)
);
bulkRequest.add(client.prepareIndex("player", "player", "2")
.setSource(jsonBuilder()
.startObject()
.field("name", "于谦")
.field("age", 25)
.field("salary",2000)
.field("team" , "cav")
.field("position" , "pg")
.endObject()
)
);
bulkRequest.add(client.prepareIndex("player", "player", "3")
.setSource(jsonBuilder()
.startObject()
.field("name", "岳云鹏")
.field("age", 29)
.field("salary",1000)
.field("team" , "war")
.field("position" , "pg")
.endObject()
)
);
bulkRequest.add(client.prepareIndex("player", "player", "4")
.setSource(jsonBuilder()
.startObject()
.field("name", "孙越")
.field("age", 26)
.field("salary",2000)
.field("team" , "war")
.field("position" , "sg")
.endObject()
)
);
bulkRequest.add(client.prepareIndex("player", "player", "5")
.setSource(jsonBuilder()
.startObject()
.field("name", "张云雷")
.field("age", 26)
.field("salary",2000)
.field("team" , "war")
.field("position" , "pf")
.endObject()
)
);
bulkRequest.add(client.prepareIndex("player", "player", "6")
.setSource(jsonBuilder()
.startObject()
.field("name", "爱迪生")
.field("age", 40)
.field("salary",1000)
.field("team" , "tim")
.field("position" , "pf")
.endObject()
)
);
bulkRequest.add(client.prepareIndex("player", "player", "7")
.setSource(jsonBuilder()
.startObject()
.field("name", "牛顿")
.field("age", 21)
.field("salary",500)
.field("team" , "tim")
.field("position" , "c")
.endObject()
)
);
bulkRequest.add(client.prepareIndex("player", "player", "4")
.setSource(jsonBuilder()
.startObject()
.field("name", "爱因斯坦")
.field("age", 21)
.field("salary",300)
.field("team" , "tim")
.field("position" , "sg")
.endObject()
)
);
bulkRequest.add(client.prepareIndex("player", "player", "8")
.setSource(jsonBuilder()
.startObject()
.field("name", "特斯拉")
.field("age", 20)
.field("salary",500)
.field("team" , "tim")
.field("position" , "sf")
.endObject()
)
);
BulkResponse bulkResponse = bulkRequest.get();
if (bulkResponse.hasFailures()) {
// process failures by iterating through each bulk response item
}
}
1：分组求count
计算每个球队的球员数量：
select team, count(*) as player_count from player group by team;
@Test
public void groupAndCount() {
//1：构建查询提交
SearchRequestBuilder builder = client.prepareSearch("player").setTypes("player");
//2：指定聚合条件
TermsAggregationBuilder team = AggregationBuilders.terms("player_count").field("team");
//3:将聚合条件放入查询条件中
builder.addAggregation(team);
//4:执行action，返回searchResponse
SearchResponse searchResponse = builder.get();
//5:将查询返回的searchResponse转换成map
Map<String, Aggregation> aggregationMap = searchResponse.getAggregations().asMap();
//6:取出聚合的字段
StringTerms teamTerms = (StringTerms)aggregationMap.get("player_count");
System.out.println(teamTerms);
//7:对聚合的字段进行迭代
Iterator<StringTerms.Bucket> iterator = teamTerms.getBuckets().iterator();
while (iterator.hasNext()){
StringTerms.Bucket bucket = iterator.next();
System.out.println("每个球队 :" + bucket.getKey() + "有 【"+bucket.getDocCount()+"】 个人");
}
}
2：Group by 多个字段
计算每个球队每个位置的球员数 select team, position, count(*) as pos_count from player group by team,position;
/**
* group by 多个字段
* 计算每个球队每个位置的球员数
* select team, position, count(*) as pos_count from player group by team, position;
* */
@Test
public void groupMutilFields() {
//1：构建查询提交
SearchRequestBuilder builder = client.prepareSearch("player").setTypes("player");
//2：指定聚合条件
TermsAggregationBuilder team = AggregationBuilders.terms("player_count").field("team");
TermsAggregationBuilder potition = AggregationBuilders.terms("position_count").field("position");
//注意父子关系
team.subAggregation(potition);
//3:将聚合条件放入查询条件中
builder.addAggregation(team).addAggregation(potition);
//4:执行action，返回searchResponse
SearchResponse searchResponse = builder.get();
//5:将查询返回的searchResponse转换成map
Map<String, Aggregation> aggregationMap = searchResponse.getAggregations().asMap();
//6:取出聚合的字段
StringTerms teamTerms = (StringTerms)aggregationMap.get("player_count");
//7:对聚合的字段进行迭代
Iterator<StringTerms.Bucket> iterator = teamTerms.getBuckets().iterator();
while (iterator.hasNext()){
StringTerms.Bucket bucket = iterator.next();
//8:获取所有子聚合
Map<String, Aggregation> position_map = bucket.getAggregations().asMap();
StringTerms potitionTerms = (StringTerms)position_map.get("position_count");
//9：对子集合下面的内容迭代 队名--位置--球员
Iterator<StringTerms.Bucket> sub_iterator = potitionTerms.getBuckets().iterator();
while (sub_iterator.hasNext()){
StringTerms.Bucket sub_bucket = sub_iterator.next();
System.out.println("球队 :" + bucket.getKey() + "下面的 "+sub_bucket.getKey()+"的位置 有"+sub_bucket.getDocCount());
}
}
}
3：分组求最大
计算每个球队年龄最大/最小/总/平均的球员年龄
select team, max(age) as max_age from player group by team;
/**
* 分组求：最大值、最小值、平均值
* 计算每个球队年龄最大/最小/总/平均的球员年龄
select team, max(age) as max_age from player group by team;
*
* */
@Test
public void groupMax(){
//1：构建查询提交
SearchRequestBuilder builder = client.prepareSearch("player").setTypes("player");
//2：指定聚合条件
TermsAggregationBuilder team = AggregationBuilders.terms("player_count").field("team");
//3: 指定要查哪一个字段的最大值
MaxAggregationBuilder ageFiled = AggregationBuilders.max("max_age").field("age");
//: 找到聚合关系：父子关系
team.subAggregation(ageFiled);
//3:将聚合条件放入查询条件中
builder.addAggregation(team);
//4:执行action，返回searchResponse
SearchResponse searchResponse = builder.get();
//5:将查询返回的searchResponse转换成map
Map<String, Aggregation> aggregationMap = searchResponse.getAggregations().asMap();
//6:取出聚合的字段
StringTerms teamTerms = (StringTerms)aggregationMap.get("player_count");
//7:对聚合的字段进行迭代
Iterator<StringTerms.Bucket> iterator = teamTerms.getBuckets().iterator();
while (iterator.hasNext()){
StringTerms.Bucket bucket = iterator.next();
//8:获取所有子聚合
Map age_map = bucket.getAggregations().asMap();
int age = (int)((InternalMax) age_map.get("max_age")).getValue();
System.out.println("球队 :" + bucket.getKey() + " 最大年龄： "+age);
}
}
4：分组求最小
计算每个球队年龄最大/最小/总/平均的球员年龄 select team, min(age) as max_age from player group by team;
/**
* 分组求：最大值、最小值、平均值
* 计算每个球队年龄最大/最小/总/平均的球员年龄
select team, min(age) as max_age from player group by team;
*
* */
@Test
public void groupMin(){
//1：构建查询提交
SearchRequestBuilder builder = client.prepareSearch("player").setTypes("player");
//2：指定聚合条件
TermsAggregationBuilder team = AggregationBuilders.terms("player_count").field("team");
//3: 指定要查哪一个字段的最大值
MinAggregationBuilder ageFiled = AggregationBuilders.min("min_age").field("age");
//: 找到聚合关系：父子关系
team.subAggregation(ageFiled);
//3:将聚合条件放入查询条件中
builder.addAggregation(team);
//4:执行action，返回searchResponse
SearchResponse searchResponse = builder.get();
//5:将查询返回的searchResponse转换成map
Map<String, Aggregation> aggregationMap = searchResponse.getAggregations().asMap();
//6:取出聚合的字段
StringTerms teamTerms = (StringTerms)aggregationMap.get("player_count");
//7:对聚合的字段进行迭代
Iterator<StringTerms.Bucket> iterator = teamTerms.getBuckets().iterator();
while (iterator.hasNext()){
StringTerms.Bucket bucket = iterator.next();
//8:获取所有子聚合
Map age_map = bucket.getAggregations().asMap();
int age = (int)((InternalMin) age_map.get("max_age")).getValue();
System.out.println("球队 :" + bucket.getKey() + " 最小年龄： "+age);
}
}
5：分组求平均值
计算每个球队年龄最大/最小/总/平均的球员年龄 select team, min(age) as max_age from player group by team;
/**
* 分组求：最大值、最小值、平均值
* 计算每个球队年龄最大/最小/总/平均的球员年龄
select team, min(age) as max_age from player group by team;
*
* */
@Test
public void groupAvg(){
//1：构建查询提交
SearchRequestBuilder builder = client.prepareSearch("player").setTypes("player");
//2：指定聚合条件
TermsAggregationBuilder team = AggregationBuilders.terms("player_count").field("team");
//3: 指定要查哪一个字段的最大值
AvgAggregationBuilder ageFiled = AggregationBuilders.avg("avg_age").field("age");
//: 找到聚合关系：父子关系
team.subAggregation(ageFiled);
//3:将聚合条件放入查询条件中
builder.addAggregation(team);
//4:执行action，返回searchResponse
SearchResponse searchResponse = builder.get();
//5:将查询返回的searchResponse转换成map
Map<String, Aggregation> aggregationMap = searchResponse.getAggregations().asMap();
//6:取出聚合的字段
StringTerms teamTerms = (StringTerms)aggregationMap.get("player_count");
//7:对聚合的字段进行迭代
Iterator<StringTerms.Bucket> iterator = teamTerms.getBuckets().iterator();
while (iterator.hasNext()){
StringTerms.Bucket bucket = iterator.next();
//8:获取所有子聚合
Map age_map = bucket.getAggregations().asMap();
Double age = ((InternalAvg) age_map.get("avg_age")).getValue();
System.out.println("球队 :" + bucket.getKey() + " 平均年龄： "+age);
}
}
6：分组求和
计算每个球队球员的平均年龄，同时又要计算总年薪 select team, avg(age)as avg_age, sum(salary) as total_salary from player group by team;
/**
* 分组求：最大值、最小值、平均值
* 计算每个球队球员的平均年龄，同时又要计算总年薪
select team, avg(age)as avg_age, sum(salary) as total_salary from player group by team;
*
* */
@Test
public void groupsum(){
//1：构建查询提交
SearchRequestBuilder builder = client.prepareSearch("player").setTypes("player");
//2：指定聚合条件
TermsAggregationBuilder team = AggregationBuilders.terms("player_count").field("team");
//3: 指定要查哪一个字段
AvgAggregationBuilder ageFiled = AggregationBuilders.avg("avg_age").field("age");
SumAggregationBuilder salaryField= AggregationBuilders.sum("sum_salary").field("salary");
//: 找到聚合关系：父子关系
team.subAggregation(ageFiled).subAggregation(salaryField);
//3:将聚合条件放入查询条件中
builder.addAggregation(team);
//4:执行action，返回searchResponse
SearchResponse searchResponse = builder.get();
//5:将查询返回的searchResponse转换成map
Map<String, Aggregation> aggregationMap = searchResponse.getAggregations().asMap();
//6:取出聚合的字段
StringTerms teamTerms = (StringTerms)aggregationMap.get("player_count");
//7:对聚合的字段进行迭代
Iterator<StringTerms.Bucket> iterator = teamTerms.getBuckets().iterator();
while (iterator.hasNext()){
StringTerms.Bucket bucket = iterator.next();
//8:获取所有子聚合
Map age_map = bucket.getAggregations().asMap();
Double age = ((InternalAvg) age_map.get("avg_age")).getValue();
double sum_salary = ((InternalSum) age_map.get("sum_salary")).getValue();
System.out.println("球队 :" + bucket.getKey() + " 平均年龄： "+age + " 球队总salary：" + sum_salary);
}
}
7：聚合排序
计算每个球队总年薪，并按照总年薪倒序排列 select team, sum(salary) as total_salary from player group by team order by total_salary desc;
/**
* 排序
计算每个球队总年薪，并按照总年薪倒序排列
select team, sum(salary) as total_salary from player group by team order by total_salary desc;
* */
@Test
public void groupOrder(){
/**
*
* TermsBuilder teamAgg= AggregationBuilders.terms("team").order(Order.aggregation("total_salary ", false);
SumBuilder salaryAgg= AggregationBuilders.avg("total_salary ").field("salary");
sbuilder.addAggregation(teamAgg.subAggregation(salaryAgg));
* */
//1：构建查询提交
SearchRequestBuilder builder = client.prepareSearch("player").setTypes("player");
//2：指定聚合条件
TermsAggregationBuilder team = AggregationBuilders.terms("player_count").field("team")
.order(Terms.Order.aggregation("total_salary", false));//false是降序，true是升序
//3: 指定要查哪一个字段
SumAggregationBuilder salaryField= AggregationBuilders.sum("total_salary").field("salary");
//: 找到聚合关系：父子关系
team.subAggregation(salaryField);
//3:将聚合条件放入查询条件中
builder.addAggregation(team);
//4:执行action，返回searchResponse
SearchResponse searchResponse = builder.get();
//5:将查询返回的searchResponse转换成map
Map<String, Aggregation> aggregationMap = searchResponse.getAggregations().asMap();
//6:取出聚合的字段
StringTerms teamTerms = (StringTerms)aggregationMap.get("player_count");
//7:对聚合的字段进行迭代
Iterator<StringTerms.Bucket> iterator = teamTerms.getBuckets().iterator();
while (iterator.hasNext()){
StringTerms.Bucket bucket = iterator.next();
//8:获取所有子聚合
Map age_map = bucket.getAggregations().asMap();
double sum_salary = ((InternalSum) age_map.get("total_salary")).getValue();
System.out.println("球队 :" + bucket.getKey() + " 球队总salary：" + sum_salary);
}
}
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