1.db.EVI_EGZ_GEAR_DAY.find({"quantity0":27}).pretty()
类似MySQL的select * from EVI_EGZ_GEAR_DAY where quantity0=27
2.db.EVI_EGZ_GEAR_DAY.find({"lastModify":{$gt:ISODate("2020-07-02T16:08:45+08:00")}}).pretty()
类似MySQL的select * from EVI_EGZ_GEAR_DAY where lastModify>"2020-07-02T16:08:45+08:00"
db.EVI_BIZ_DAYINFO.find({"ReportDay":{$gte:20200601 ,$lte: 20200630},"LoginID":"304095318","Is_Statistics":1})
操作 格式 范例 RDBMS中的类似语句
等于 {<key>:<value>} db.col.find({"by":"菜鸟教程"}).pretty() where by = '菜鸟教程'
小于 {<key>:{$lt:<value>}} db.col.find({"likes":{$lt:50}}).pretty() where likes < 50
小于或等于 {<key>:{$lte:<value>}} db.col.find({"likes":{$lte:50}}).pretty() where likes <= 50
大于 {<key>:{$gt:<value>}} db.col.find({"likes":{$gt:50}}).pretty() where likes > 50
大于或等于 {<key>:{$gte:<value>}} db.col.find({"likes":{$gte:50}}).pretty() where likes >= 50
不等于 {<key>:{$ne:<value>}} db.col.find({"likes":{$ne:50}}).pretty() where likes != 50
3.db.EVI_EGZ_GEAR_DAY.aggregate([{$group: {_id:"$loginId"}}])
类似MySQL的select loginId from EVI_EGZ_GEAR_DAY group by loginId
4.db.EVI_EGZ_GEAR_DAY.aggregate([{$match: {loginId:"100870655"}},{$group: {_id:"$loginId",count:{$sum: 1}}}])
类似MySQL的select loginId,count(*) from EVI_EGZ_GEAR_DAY where loginId=100870655 group by loginId
5.db.EVI_RPT_MARKETMON_ANALYSIS.find({"reportTime":"201810","areaParentCode":"430000","machineCode":"MT0000000212","machineType":"2","nationCode":"CN","calcType":"0"},
{"areaName":1,"machineName":1,"workTime":1,"equCount":1,"workCount":1,"restCount":1,"highWorkCount":1,"avgWorkTime":1,"workRate":1,"calcType":"1"}).sort({ equCount:-1 })
6.聚合查询
db.EVI_BIZ_DAYINFO.aggregate([{
"$match": {
"ReportTime" : ISODate("2020-07-01T00:00:00.000+08:00"),
"Is_Statistics": 1,
"IsOnline": 1,
"MachineType_Code1" : "MT0000000276"// 按照一级机型分类统计,否则查询不到数据
}
},
{
"$group" : {
_id:{
countyCode :"$County_Code",
cityCode :"$City_Code",
provinceCode :"$Province_Code",
machineType1 :"$MachineType_Code1",
machineType2 :"$MachineType_Code2",
nationCode:"$Nation_Code"
},
highWorkCount : {$sum: { $cond: [ {$gte: [ "$WorkTime",8] },
1,
0 ] }},
countWork: {
$sum: '$IsWork'
},
workTime: {
$sum: '$WorkTime'
},
equCount:{
$sum: 1
}
}
}
])
7.and查询
db.EVI_BIZ_DAYINFO.find({"ReportDay":20200201,"LoginID":"302060888"})
8.聚合查询类似SQL中的(group by xxx having )
db.EVI_BIZ_DAYINFO.aggregate([{
"$match": {"LoginID":"101065868",
"ReportDay":{$gte: 20200701,$lte:20200731}
}
},
{
"$group": {
_id:{
LoginID:"$LoginID",
ReportDay:"$ReportDay"
},
},
WorkTimes:{
$sum: "$WorkTime"
},
totalDay:{
$sum: {$cond: [ { $gt: ["$WorkTime",0]}, 1, 0 ]}
}
}
},
{"$match": {WorkTimes:{$gt:0}}}
])
9.更新操作 会把查询到的符合更新条件的都跟新一遍
db.EVI_ALARM_FLEET.update({"reportTime":ISODate("2020-08-21T00:00:00.000+08:00")},{$set:{"reportTime":ISODate("2020-08-22T00:00:00.000+08:00")}},false,true)
10.更新操作,只更新一条
db.EVI_ALARM_FLEET.update({"reportTime":ISODate("2020-08-21T00:00:00.000+08:00")},{$set:{"reportTime":ISODate("2020-08-22T00:00:00.000+08:00")}})
11.OR查询
db.EVI_BIZ_DAYINFO.find({$or:[{"LoginID":"104259298"},{"LoginID":"132349918"}]})
12模糊查询
db.configuration.find({"envType":"hxevi.test","key":{$regex:/mail/}})
相当于MySQL的select * from configuration where envType='hxevi.test' and key like '%mail%'
13分组去重查询,条件判断查询,根据索引查询数组,排序,根据排序取最新一条数据的相关值(先按时间排序)
db.EVI_BIZ_DAYINFO.aggregate([
{
"$match": {
"ReportTime":{"$gte":ISODate("2021-01-18T00:00:00.000+08:00"),"$lte":ISODate("2021-01-24T00:00:00.000+08:00")},
"Is_Statistics": 1,
"LoginID": "101102108"
}
},
{"$sort": {"ReportTime": -1}},
{
"$group": {
"_id": "$LoginID",
"WorkTime": {
"$sum": "$WorkTime"
},
"IdleTime": {
"$sum": "$IdleTime"
},
"FuelConsume": {
"$sum": "$FuelConsume"
},
"IdleFuelConsume": {
"$sum": "$IdleFuelConsume"
},
"ReportTime": {"$first": "$ReportTime"},
"City_Code": {"$first": "$City_Code"},
"City_Name": {"$first": "$City_Name"},
"County_Code": {"$first": "$County_Code"},
"County_Name": {"$first": "$County_Name"},
"Nation_Code": {"$first": "$Nation_Code"},
"Nation_Name": {"$first": "$Nation_Name"},
"Province_Code": {"$first": "$Province_Code"},
"Province_Name": {"$first": "$Province_Name"},
"Latitude": {"$first": "$Latitude"},
"Longitude": {"$first": "$Longitude"},
"TotalIdleFC": {"$first": "$TotalIdleFC"},
"TotalIdleTime": {"$first": "$TotalIdleTime"},
"TotalWorkTime": {"$first": "$TotalWorkTime"},
"TotalFC": {"$first": "$TotalFC"},
"DataVersion": {"$addToSet": '$DataVersion'},
"Machine_Model": {"$addToSet": '$Machine_Model'},
"MachineType_Code1": {"$addToSet": '$MachineType_Code1'},
"MachineType_Code2": {"$addToSet": '$MachineType_Code2'},
"MachineType_Code3": {"$addToSet": '$MachineType_Code3'},
"MachineType_Name1": {"$addToSet": '$MachineType_Name1'},
"MachineType_Name2": {"$addToSet": '$MachineType_Name2'},
"MachineType_Name3": {"$addToSet": '$MachineType_Name3'},
"Serialno": {"$addToSet": '$Serialno'},
"Customer_Code": {"$addToSet": '$Customer_Code'},
"Customer_Name": {"$addToSet": '$Customer_Name'},
"Customer_Tel": {"$addToSet": '$Customer_Tel'},
"SaleDealer": {"$addToSet": '$SaleDealer'},
"SaleDealer_Code": {"$addToSet": '$SaleDealer_Code'},
"SvrDealer": {"$addToSet": '$SvrDealer'},
"SvrDealer_Code": {"$addToSet": '$SvrDealer_Code'},
"Register_Date": {"$addToSet": '$Register_Date'},
"sumIsOnline": {"$sum": '$IsOnline'}
}
},
{
"$project":{
"LoginID":"$_id",
"WorkTime":"$WorkTime",
"IdleTime":"$IdleTime",
"FuelConsume":"$FuelConsume",
"IdleFuelConsume":"$IdleFuelConsume",
"City_Code":"$City_Code",
"City_Name": "$City_Name",
"County_Code": "$County_Code",
"County_Name": "$County_Name",
"Nation_Code": "$Nation_Code",
"Nation_Name": "$Nation_Name",
"Province_Code": "$Province_Code",
"Province_Name": "$Province_Name",
"Latitude": "$Latitude",
"Longitude": "$Longitude",
"TotalIdleFC": "$TotalIdleFC",
"TotalIdleTime": "$TotalIdleTime",
"TotalWorkTime": "$TotalWorkTime",
"TotalFC": "$TotalFC",
"DataVersion": {"$arrayElemAt":["$DataVersion",0]},
"Machine_Model": {"$arrayElemAt":["$Machine_Model",0]},
"MachineType_Code1": {"$arrayElemAt":["$MachineType_Code1",0]},
"MachineType_Code2": {"$arrayElemAt":["$MachineType_Code2",0]},
"MachineType_Code3": {"$arrayElemAt":["$MachineType_Code3",0]},
"MachineType_Name1": {"$arrayElemAt":["$MachineType_Name1",0]},
"MachineType_Name2": {"$arrayElemAt":["$MachineType_Name2",0]},
"MachineType_Name3": {"$arrayElemAt":["$MachineType_Name3",0]},
"Serialno": {"$arrayElemAt":["$Serialno",0]},
"Customer_Code": {"$arrayElemAt":["$Customer_Code",0]},
"Customer_Name": {"$arrayElemAt":["$Customer_Name",0]},
"Customer_Tel": {"$arrayElemAt":["$Customer_Tel",0]},
"SaleDealer": {"$arrayElemAt":["$SaleDealer",0]},
"SaleDealer_Code": {"$arrayElemAt":["$SaleDealer_Code",0]},
"SvrDealer": {"$arrayElemAt":["$SvrDealer",0]},
"SvrDealer_Code": {"$arrayElemAt":["$SvrDealer_Code",0]},
"Register_Date": {"$arrayElemAt":["$Register_Date",0]},
"IsOnline": {"$cond": {
"if":{"$gt":["$sumIsOnline",0]},"then":1,
"else":0
}}
}
}],
{ allowDiskUse: true }).pretty()