mongodb聚合sql写法
1、聚合查询配上分页加排序
bash
DBQuery.shellBatchSize = 30000
db.getCollection('svOrderRecordMo').aggregate([
{$match:{"actionType":9}},
{$group:{_id:"$svOrderId",total:{"$sum":1}}},
{$sort:{"createTime":1}},
{$skip:0},
{$limit:100}
])
2、在1的聚合查询基础上进行match过滤(过滤出total>1的数据)
bash
DBQuery.shellBatchSize = 30000
db.getCollection('svOrderRecordMo').aggregate([
{$match:{"actionType":9}},
{$group:{_id:"$svOrderId",total:{"$sum":1}}},
{$match:{"total":{"$gt":1}}},
{$sort:{"createTime":1}},
{$skip:0},
{$limit:3000}
])
3、聚合查询时间范围并把Date的日期格式转成字符串(yyyyMMdd)然后聚合查询
bash
db.getCollection('svRegisterRecordMo').aggregate([
{$match:{"$and":[{"createTime":{"$gte":ISODate("2023-01-01T00:00:00.000+08:00")}}
,{"createTime":{"$lte":ISODate("2023-07-02T00:00:00.000+08:00")}}] }},
{
$project: {
convertedDate: {
$dateToString: {
format: "%Y%m%d",
date: "$createTime"
}
}
}
},
{
$group: {
_id: "$convertedDate",
count: { $sum: 1 }
}
}
])
4、排序,聚合,sum求和同时应用
bash
db.getCollection('reportAgentMo').aggregate([
{$match:{"dataType":"1.1","reportType":1,"platformType":2,"reportDate":{"$in":["2023-01-25","2023-02-25","2023-03-25","2023-04-25","2023-05-25","2023-06-25","2023-07-25","2023-08-25"]}}},
{$group:{_id:"$agentId",total:{"$sum":"$issuePercent"}}},
{$sort:{"total":-1}},
{$limit:10}
])
5、聚合对两字段求和,并把两个求和的值相除然后排序
bash
db.getCollection('reportAgentMo').aggregate([
{$match:{"dataType":"1.1","reportType":1,"platformType":2,
"reportDate":{"$in":["2023-01-25","2023-02-25","2023-03-25","2023-04-25","2023-05-25","2023-06-25","2023-07-25","2023-08-25"]}}},
{$group:{_id:"$agentId",total1:{"$sum":"$issueNum"},total2:{"$sum":"$svNum"}}},
{$match:{total2:{"$gt":0}}},
{$project:{_id:1,aver:{"$divide":["$total1","$total2"]}}},
{$sort:{aver:-1}},
{$limit:11}
])
6、聚合时使用$first关键字(根据customTextAnswer.text聚合,并获取第一条数据)
bash
db.getCollection('orderExtraInfoMo').aggregate([
{$match:{"topic":"家庭年收入"
,"customTextAnswer.number":{"$ne":null}}},
{$group:{_id:"$customTextAnswer.text",svOrderId:{"$first":"$svOrderId"},"number":{"$first":"$customTextAnswer.number"}}},
{$sort:{"svOrderId":-1}},
{$skip:0},
{$limit:10000}
])
7、对targetValue字段进行聚合统计,key是cId
bash
db.getCollection("channelTargetMo").aggregate([
{$match:{"targetDate":{"$gte":"2022-08-03"},"targetDate":{"$lte":"2022-09-02"},"targetDateType":"day","targetType":"deal_sv","cIdType":"subId","cId":"62eb25c3b6d6033cb3fd9174"}},
{$group:{_id:"$cId",total:{"$sum":"$targetValue"}}}
]);
8、mongodb的两表关联查询
如下所示:左表是reportCustDealInfoMo,右表是reportCustDataMo,连接条件是reportCustDealInfoMo.custId=reportCustDataMo.cId。因为默认是1对多 情况,所以aa是一个数组,
$unwind 是把aa数组展开
bash
db.reportCustDealInfoMo.aggregate([
{
$match:{"isDeleted":false,"isDeal":true}
},
{
$lookup: {
from: "reportCustDataMo",
localField: "custId",
foreignField: "cId",
as: "aa"
}
},
{
$unwind: "$aa"
},
{
$match: {
"aa.cIdType": "custId",
"aa.reportType": "year",
"aa.reportDate":"2021"
}
},
{$group:{_id:null,
dealInternetAmount:{"$sum":"$aa.dealInternetAmount"},
dealHighCriterionAmount:{"$sum":"$aa.dealHighCriterionAmount"},
dealCarCriterionAmount:{"$sum":"$aa.dealCarCriterionAmount"},
dealGroupCriterionAmount:{"$sum":"$aa.dealGroupCriterionAmount"},
dealLifeCriterionAmount:{"$sum":"$aa.dealLifeCriterionAmount"},
underwriteCdCriterionAmount:{"$sum":"$aa.underwriteCdCriterionAmount"}
}}
,
{$project:{
dealInternetAmount:1,
dealHighCriterionAmount:1,
dealCarCriterionAmount:1,
dealGroupCriterionAmount:1,
dealLifeCriterionAmount:1,
underwriteCdCriterionAmount:1,
totalStaAmount:{"$add":["$dealInternetAmount","$dealHighCriterionAmount","$dealCarCriterionAmount","$dealGroupCriterionAmount","$dealLifeCriterionAmount"]}}}
])