count(1)
select clssId,count(1) from student group by classId
{
"size":0,
"aggs": {
"group_by_classId": {
"terms": {
"field": "classId.keyword"
}
}
}
}
结果 key为classId doc_count 为count
size 0表示只看聚合结果不看搜索结果
{
"took": 82,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 4,
"max_score": 0,
"hits": []
},
"aggregations": {
"group_by_classId": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "2",
"doc_count": 3
},
{
"key": "5",
"doc_count": 1
}
]
}
}
}
count+avg
select clssId,count(1),avg(score) from student group by classId
{
"size":0,
"aggs": {
"group_by_classId": {
"terms": {
"field": "classId.keyword"
},
"aggs": {
"average_balance": {
"avg": {
"field": "score"
}
}
}
}
}
}
结果
{
"took": 95,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 4,
"max_score": 0,
"hits": []
},
"aggregations": {
"group_by_classId": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "2",
"doc_count": 3,
"average_balance": {
"value": 53.333333333333336
}
},
{
"key": "5",
"doc_count": 1,
"average_balance": {
"value": 10
}
}
]
}
}
}
聚合并排序
select clssId,count(1),avg(score) from student group by classId order by avg(score) desc
{
"size":0,
"aggs": {
"group_by_classId": {
"terms": {
"field": "classId.keyword",
"order": {
"average_score": "desc"
}
},
"aggs": {
"average_score": {
"avg": {
"field": "score"
}
}
}
}
}
}
Metric Aggregations
地理边界聚合
1.添加测试mapping
{
"mappings": {
"doc": {
"properties": {
"location": {
"type": "geo_point"
}
}
}
}
}
2.添加测试数据
{
"text": "成都",
"location": {
"lat": 11.12,
"lon": -5.34
}
}
{
"text": "广州",
"location": {
"lat": 66.12,
"lon": -22.34
}
}
{
"text": "深圳",
"location": {
"lat": 121.12,
"lon": -77.34
}
}
测试query
{
"size":0,
"query" : {
"match_all" : { }
},
"aggs" : {
"viewport" : {
"geo_bounds" : {
"field" : "location",
"wrap_longitude" : true //可选参数，指定边界框是否允许与国际日期变更线重叠，默认值是true。
}
}
}
}
结果
{
"took": 5,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 2,
"max_score": 0,
"hits": []
},
"aggregations": {
"viewport": {
"bounds": {
"top_left": {
"lat": 41.1199999647215,
"lon": -71.34000004269183
},
"bottom_right": {
"lat": 11.119999992661178,
"lon": -5.340000037103891
}
}
}
}
}
地理重心聚合
用以上测试数据
query
{
"size":0,
"query" : {
"match_all" : { }
},
"aggs" : {
"centroid" : {
"geo_centroid" : {
"field" : "location"
}
}
}
}
结果
{
"took": 3,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 2,
"max_score": 0,
"hits": []
},
"aggregations": {
"centroid": {
"location": {
"lat": 26.11999997869134,
"lon": -38.34000003989786
},
"count": 2
}
}
}
平均值聚合
{
"size":0,
"aggs" : {
"avg_grade" : { "avg" : { "field" : "mdProductId" } }
}
}
count聚合
{
"aggs" : {
"types_count" : { "value_count" : { "field" : "type" } }
}
}
最大值聚合
{
"aggs" : {
"max_price" : { "max" : { "field" : "price" } }
}
}
最小值聚合
{
"aggs" : {
"min_price" : { "min" : { "field" : "price" } }
}
}
使用脚本聚合
如最小值为例子
{
"aggs" : {
"min_price" : {
"min" : {
"script" : {
"inline" : "doc.price.value"
}
}
}
}
}
设置聚合默认值
POST /sales/_search
{
"aggs" : {
"grade_max" : {
"max" : {
"field" : "grade",
"missing": 10
}
}
}
}
聚合结果脚本运算
{
"aggs" : {
"min_price_in_euros" : {
"min" : {
"field" : "price",
"script" : {
"inline" : "_value * params.conversion_rate",
"params" : {
"conversion_rate" : 1.2
}
}
}
}
}
}
父子聚合
{
"size": 0,
"aggs": {
"detail": {
"children": {
"type": "ic_product_store_account"--子文档
},
"aggs": {
"sum_price": {
"sum": {
"field": "sumCount"--子文档聚合字段
}
}
}
}
}
}
goupBy语法
avg
{
"size": 0,
"aggs" : {
"group_by_tags" : {
"terms" : { "field" : "productId" },
"aggs" : {
"avg_price" : {
"avg" : { "field" : "price" }
}
}
}
}
}
select productId,avg(price) from type grup by productId
需要查询条件加上query语法就行了
