我想得到满足一定条件的群体数量。在SQL术语中,我想在Elasticsearch中执行以下操作。
SELECT COUNT(*) FROM
(
SELECT
senderResellerId,
SUM(requestAmountValue) AS t_amount
FROM
transactions
GROUP BY
senderResellerId
HAVING
t_amount > 10000 ) AS dum;
到目前为止,我可以通过term Aggsel对senderResellerId进行分组。但是当我应用过滤器时,它不能按预期工作。
弹性请求
{
"aggregations": {
"reseller_sale_sum": {
"aggs": {
"sales": {
"aggregations": {
"reseller_sale": {
"sum": {
"field": "requestAmountValue"
}
}
},
"filter": {
"range": {
"reseller_sale": {
"gte": 10000
}
}
}
}
},
"terms": {
"field": "senderResellerId",
"order": {
"sales>reseller_sale": "desc"
},
"size": 5
}
}
},
"ext": {},
"query": { "match_all": {} },
"size": 0
}
实际响应
{
"took" : 21,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"failed" : 0
},
"hits" : {
"total" : 150824,
"max_score" : 0.0,
"hits" : [ ]
},
"aggregations" : {
"reseller_sale_sum" : {
"doc_count_error_upper_bound" : -1,
"sum_other_doc_count" : 149609,
"buckets" : [
{
"key" : "RES0000000004",
"doc_count" : 8,
"sales" : {
"doc_count" : 0,
"reseller_sale" : {
"value" : 0.0
}
}
},
{
"key" : "RES0000000005",
"doc_count" : 39,
"sales" : {
"doc_count" : 0,
"reseller_sale" : {
"value" : 0.0
}
}
},
{
"key" : "RES0000000006",
"doc_count" : 57,
"sales" : {
"doc_count" : 0,
"reseller_sale" : {
"value" : 0.0
}
}
},
{
"key" : "RES0000000007",
"doc_count" : 134,
"sales" : {
"doc_count" : 0,
"reseller_sale" : {
"value" : 0.0
}
}
}
}
}
]
}
}
}
从上面的响应可以看出,它返回了代理商,但 reseller_sale 聚合在结果中为零。
更多详情请见here。
答案 0 :(得分:11)
您可以使用其中一个pipeline aggregations
,即bucket selector aggregation。查询将如下所示:
POST my_index/tdrs/_search
{
"aggregations": {
"reseller_sale_sum": {
"aggregations": {
"sales": {
"sum": {
"field": "requestAmountValue"
}
},
"max_sales": {
"bucket_selector": {
"buckets_path": {
"var1": "sales"
},
"script": "params.var1 > 10000"
}
}
},
"terms": {
"field": "senderResellerId",
"order": {
"sales": "desc"
},
"size": 5
}
}
},
"size": 0
}
将以下文件放入索引后:
"hits": [
{
"_index": "my_index",
"_type": "tdrs",
"_id": "AV9Yh5F-dSw48Z0DWDys",
"_score": 1,
"_source": {
"requestAmountValue": 7000,
"senderResellerId": "ID_1"
}
},
{
"_index": "my_index",
"_type": "tdrs",
"_id": "AV9Yh684dSw48Z0DWDyt",
"_score": 1,
"_source": {
"requestAmountValue": 5000,
"senderResellerId": "ID_1"
}
},
{
"_index": "my_index",
"_type": "tdrs",
"_id": "AV9Yh8TBdSw48Z0DWDyu",
"_score": 1,
"_source": {
"requestAmountValue": 1000,
"senderResellerId": "ID_2"
}
}
]
查询结果为:
"aggregations": {
"reseller_sale_sum": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ID_1",
"doc_count": 2,
"sales": {
"value": 12000
}
}
]
}
}
即。只有累计销售额为senderResellerId
的{{1}}。
要实现等效的>10000
,可以使用bucket script aggregation与sum bucket aggregation的组合。虽然似乎没有直接的方法来计算SELECT COUNT(*) FROM (... HAVING)
实际选择的多少个桶,但我们可能会根据条件定义生成bucket_selector
或bucket_script
的{{1}},以及产生0
的<{1}}:
1
输出将是:
sum_bucket
所需的存储桶数位于sum
。
我必须指出两件事:
管道聚合对其他聚合产生的输出起作用而不是 从文档集中,将信息添加到输出树。
这意味着POST my_index/tdrs/_search
{
"aggregations": {
"reseller_sale_sum": {
"aggregations": {
"sales": {
"sum": {
"field": "requestAmountValue"
}
},
"max_sales": {
"bucket_script": {
"buckets_path": {
"var1": "sales"
},
"script": "if (params.var1 > 10000) { 1 } else { 0 }"
}
}
},
"terms": {
"field": "senderResellerId",
"order": {
"sales": "desc"
}
}
},
"max_sales_stats": {
"sum_bucket": {
"buckets_path": "reseller_sale_sum>max_sales"
}
}
},
"size": 0
}
聚合将应用于 "aggregations": {
"reseller_sale_sum": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
...
]
},
"max_sales_stats": {
"value": 1
}
}
上max_sales_stats.value
聚合的结果之后和之后。例如,如果bucket_selector
聚合定义的terms
senderResellerId
senderResellerId
size
terms
,则sum(sales) > 10000
的{ID>} ,但仅限于出现在terms
聚合输出中的那些。考虑使用排序和/或设置足够的size
参数。
这也适用于第二种情况COUNT() (... HAVING)
,它只计算实际存在于聚合输出中的那些存储桶。
如果此查询太重或存储桶数量太大,请考虑denormalizing您的数据或将此总和直接存储在文档中,这样您就可以使用纯range
查询来实现目标
希望有所帮助!