Elasticsearch桶聚合和管道聚合

1. 根据名称统计数量 

GET order/_search
{"_source": false,"aggs": {"aggs_name": {  // 自定义查询结果名称"terms": {  // 使用的函数"field": "name.keyword"}}}
}查询结果例子：
"aggregations" : {"aggs_name" : {"doc_count_error_upper_bound" : 0,"sum_other_doc_count" : 0,"buckets" : [{"key" : "张三","doc_count" : 3},{"key" : "李四","doc_count" : 6}]}
}

2. 根据名称和级别统计数量

GET order/_search
{"_source": false,"aggs": {"aggs_name": {"multi_terms": {"terms": [{"field": "name.keyword"},{"field": "level.keyword"}]}}}
}

3. 根据名称分组，再根据价格区间分组，然后统计数量

GET order/_search
{"_source": false,"aggs": {"aggs_name": {"terms": {"field": "name.keyword"},"aggs": {"aggs_price_count": {"range": {"field": "price","ranges": [{"from": 1000,"to": 3000},{"from": 3000}]}}}}}
}

  4. 根据名称分组，然后取各组的最大值，然后取各组最大值的平均值

GET order/_search
{"_source": false,"aggs": {"aggs_term": { // 桶聚合分组"terms": {"field": "name.keyword"},"aggs": {"aggs_max_price": {  // 指标聚合取最大值"max": {"field": "price"}}}},"pip_avg":{ // 管道聚合求最大值的平均值"avg_bucket": {"buckets_path": "aggs_term>aggs_max_price" // 取值的桶的路径地址 >也可以用.代替：aggs_term.aggs_max_price}}}
}

5. 多个指标聚合查询，stats是max，min，avg，sum，count合并的查询语法

GET order/_search
{"_source": false,"aggs": {"aggs_term": {"terms": {"field": "name.keyword"},"aggs": {"aggs_max_price": {"max": {"field": "price"}},"aggs_avg_price": {"avg": {"field": "price"}},"aggs_all": {"stats": {"field": "price"}}}}}
}
查询结果：
"buckets" : [{"key" : "name1","doc_count" : 3,"aggs_avg_price" : {"value" : 2000.0},"aggs_max_price" : {"value" : 3000.0},"aggs_all" : {"count" : 3,"min" : 1000.0,"max" : 3000.0,"avg" : 2000.0,"sum" : 6000.0}},{"key" : "name2","doc_count" : 3,"aggs_avg_price" : {"value" : 3666.6666666666665},"aggs_max_price" : {"value" : 6000.0},"aggs_all" : {"count" : 3,"min" : 2000.0,"max" : 6000.0,"avg" : 3666.6666666666665,"sum" : 11000.0}}
]