MongoDB查找查询 [英] Mongodb find query
问题描述
seasons.json
seasons.json
{
"_id" : "unique_1",
"spring" : [{
"fruit" : "mango",
"person_id" : [101.0, 102.0, 103.0, 104.0]
}, {
"fruit" : "banana",
"person_id" : [151.0, 152.0, 153.0, 154.0]
}],
"summer" : [{
"fruit" : "mango",
"person_id" : [201.0, 202.0, 203.0, 204.0]
}, {
"fruit" : "banana",
"person_id" : [251.0, 252.0, 253.0, 254.0]
}],
"fall" : [{
"fruit" : "mango",
"person_id" : [301.0, 302.0, 303.0, 304.0]
}, {
"fruit" : "banana",
"person_id" : [351.0, 352.0, 353.0, 354.0]
}],
"winter" : [{
"fruit" : "mango",
"person_id" : [401.0, 402.0, 403.0]
}, {
"fruit" : "banana",
"person_id" : [451.0, 452.0, 453.0]
}]
}
/* 2 */
{
"_id" : "unique_2",
"spring" : [{
"fruit" : "banana",
"person_id" : [151.0, 152.0, 153.0, 154.0]
}],
"summer" : [{
"fruit" : "mango",
"person_id" : [201.0, 202.0, 203.0, 204.0]
}, {
"fruit" : "banana",
"person_id" : [251.0, 252.0, 253.0, 254.0]
}],
"fall" : [{
"fruit" : "banana",
"person_id" : [351.0, 352.0, 353.0, 354.0]
}],
"winter" : [{
"fruit" : "mango",
"person_id" : [401.0, 402.0, 403.0]
}, {
"fruit" : "banana",
"person_id" : [451.0, 452.0, 453.0]
}]
}
以上JSON记录显示哪个人哪个季节食用芒果和哪个季节食用香蕉.
Above JSON records shows which season which person has eaten mango and which has eaten banana.
这是我要查找的内容: 当我提前或在查找记录之前知道记录的_id(主键)时-
Here's what I want to find: when i know the _id(primary key) of the record in advance or prior to record finding -
1)所有person_id，范围为101-350，其中person_id是唯一的 2)person_id只吃芒果 3)有记录的吃芒果或香蕉水果的总人数.
1) all the person_id ranging from 101 - 350 in which person_id is unique 2) person_id eating only mango 3) total number of person in a record eating fruit either mango or banana.
推荐答案
使用这样的模式，要运行像您所需的这种性质的查询将非常困难.考虑更改架构，以便每个子文档都有一个主键，例如seasons，它可以具有四个不同的数组元素，即春天，夏天，冬天和秋天.将架构更改为此:
With a schema like this it's going to be pretty difficult to run queries of such a nature like the ones you require. Consider changing the schema such that you have for each subdocument, one main key say for instance seasons which can have four different array elements i.e. spring, summer, winter and fall. Change the schema to this:
/* 1 */
{
"_id" : "unique_1",
"seasons" : [
{
"name" : "spring",
"fruits" : [
{
"name" : "mango",
"person_id" : [
101,
102,
103,
104
]
},
{
"name" : "banana",
"person_id" : [
151,
152,
153,
154
]
}
]
},
{
"name" : "summer",
"fruits" : [
{
"name" : "mango",
"person_id" : [
201,
202,
203,
204
]
},
{
"name" : "banana",
"person_id" : [
251,
252,
253,
254
]
}
]
},
{
"name" : "fall",
"fruits" : [
{
"name" : "mango",
"person_id" : [
301,
302,
303,
304
]
},
{
"name" : "banana",
"person_id" : [
351,
352,
353,
354
]
}
]
},
{
"name" : "winter",
"fruits" : [
{
"name" : "mango",
"person_id" : [
401,
402,
403
]
},
{
"name" : "banana",
"person_id" : [
451,
452,
453
]
}
]
}
]
}
使用此架构，可以更轻松地运行以下聚合查询:
With this schema it becomes much easier to run the following aggregation queries:
1)所有person_id都在101-350之间，其中person_id是唯一的
1) all the person_id ranging from 101 - 350 in which person_id is unique
var pipeline1 = [
{ "$match": { "_id": "unique_1" },
{ "$unwind": "$seasons" },
{ "$unwind": "$seasons.fruits" },
{ "$unwind": "$seasons.fruits.person_id" },
{
"$match": {
"seasons.fruits.person_id": {
"$gte": 101,
"$lte": 350
}
}
},
{
"$group": {
"_id": 0,
"person_ids": {
"$addToSet": "$seasons.fruits.person_id"
}
}
},
{
"$project": {
"_id": 0,
"person_ids": 1
}
}
];
db.season.aggregate(pipeline1);
输出:
/* 1 */
{
"result" : [
{
"person_ids" : [
304,
253,
201,
251,
301,
203,
252,
204,
152,
102,
202,
154,
254,
101,
302,
153,
104,
103,
303,
151
]
}
],
"ok" : 1
}
2)person_id只吃芒果
2) person_id eating only mango
var pipeline2 = [
{ "$match": { "_id": "unique_1" },
{ "$unwind": "$seasons" },
{ "$unwind": "$seasons.fruits" },
{ "$unwind": "$seasons.fruits.person_id" },
{
"$match": {
"seasons.fruits.name": "mango"
}
},
{
"$group": {
"_id": 0,
"person_ids": {
"$addToSet": "$seasons.fruits.person_id"
}
}
},
{
"$project": {
"_id": 0,
"person_ids": 1
}
}
];
db.season.aggregate(pipeline2);
输出:
/* 1 */
{
"result" : [
{
"person_ids" : [
402.0000000000000000,
304.0000000000000000,
303.0000000000000000,
302.0000000000000000,
301.0000000000000000,
204.0000000000000000,
202.0000000000000000,
201.0000000000000000,
203.0000000000000000,
104.0000000000000000,
102.0000000000000000,
103.0000000000000000,
403.0000000000000000,
401.0000000000000000,
101.0000000000000000
]
}
],
"ok" : 1
}
3)记录中吃芒果或香蕉水果的总人数.
3) total number of person in a record eating fruit either mango or banana.
var pipeline3 = [
{ "$match": { "_id": "unique_1" },
{ "$unwind": "$seasons" },
{ "$unwind": "$seasons.fruits" },
{ "$unwind": "$seasons.fruits.person_id" },
{
"$match": {
"seasons.fruits.name": {
"$in": ["mango", "banana"]
}
}
},
{
"$group": {
"_id": "$_id",
"count": {
"$sum": 1
}
}
},
{
"$project": {
"_id": 0,
"count": 1
}
}
];
db.season.aggregate(pipeline3);
输出:
/* 1 */
{
"result" : [
{
"count" : 30
}
],
"ok" : 1
}
这篇关于MongoDB查找查询的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
