英文:
How to query MongoDb subdocuments in Java
问题
亲爱的MongoDB专家们！我是Mongo的新手，目前正在使用Java处理MongoDB。
我有一个名为“teams”的集合的MongoDB，其示例结构如下：
[
{
"id": "123",
"name": "Dev1",
"employees": [
{"name": "John", "age": 30},
{"name": "Jane", "age": 30}
]
},
{
"id": "456",
"name": "Dev2",
"employees": [
{"name": "Mike", "age": 30},
{"name": "Oscar", "age": 27}
]
}
]
我想要一个查询，返回一个数组，其中包含所有年龄为30岁的员工。所以期望的结果将是：
[
{"name": "John", "age": 30},
{"name": "Jane", "age": 30},
{"name": "Mike", "age": 30}
]
甚至只获取员工的名字会更好（因为我知道我正在搜索的年龄），如下：
[
{"name": "John"},
{"name": "Jane"},
{"name": "Mike"}
]
我有一个MongoCollection对象：
MongoCollection<Document> collection = mongoClient
.getDatabase(databaseName)
.getCollection("teams");
我的问题是：是否可以从MongoDB中检索出我期望的结果？如果可以，我在集合对象上需要调用哪些操作？
英文:
Dear MongoDb Experts out there! I am new to Mongo and I am currently working with a MongoDb with Java.
Having a MongoDb with a collection called "teams" with the following example structure:
{[
{
"id": "123",
"name": "Dev1",
"employees": [
{"name": "John", "age": 30},
{"name": "Jane", "age": 30}
]
},
{
"id": "456",
"name": "Dev2",
"employees": [
{"name": "Mike", "age": 30},
{"name": "Oscar", "age": 27}
]
}
]}
I want to have a query which returns an array with all employees, that are 30 years old. So the expected result would be:
{[
{"name": "John", "age": 30},
{"name": "Jane", "age": 30},
{"name": "Mike", "age": 30}
]}
It would be even better to only get the employees name (since I know the age I searched for), like:
{[
{"name": "John"},
{"name": "Jane"},
{"name": "Mike"}
]}
I have a MongoCollection object:
MongoCollection<Document> collection = mongoClient
.getDatabase(databaseName)
.getCollection("teams")
My question: Is it possible to retrieve my expected result from the MongoDb? If so, which operations do I have to call on my collection object?
答案1
得分: 0
方法一：使用 $elemMatch 投影进行查找
db.getCollection('teams').find(
{"employees.age": 30},
{ "employees": { "$elemMatch": { "age": 30 } }, "_id": 0 }
)
输出格式：
{
"employees": [
{
"name": "John",
"age": 30.0
}
]
}
{
"employees": [
{
"name": "Mike",
"age": 30.0
}
]
}
方法二：使用 $unwind 和 $projection 进行聚合和键重命名
db.getCollection('teams').aggregate([
{"$match": {"employees.age": 30}},
{"$unwind": "$employees"},
{"$match": {"employees.age": 30}},
{"$project": {"name": "$employees.name", "_id": 0}}
])
输出格式：
{
"name": "John"
}
{
"name": "Jane"
}
{
"name": "Mike"
}
方法一可能更快，但需要在应用层进行额外的处理。建议将格式化任务转移到应用服务器上，而不是在数据库本身执行。
方法二可以立即提供格式化的结果，在数据库服务器上同时进行查询和格式化处理。
英文:
Approach 1: Find with $elemMatch projection
db.getCollection('teams').find(
{"employees.age":30},
{ "employees": { "$elemMatch": { "age": 30 } },"_id":0 }
)
Output Format:
{
"employees" : [
{
"name" : "John",
"age" : 30.0
}
]
}
{
"employees" : [
{
"name" : "Mike",
"age" : 30.0
}
]
}
Approach 2: Aggregate with $unwind and key renaming using $projection
db.getCollection('teams').aggregate([
{"$match": {"employees.age":30}} ,
{"$unwind": "$employees"},
{"$match": {"employees.age":30}} ,
{"$project": {"name": "$employees.name","_id":0}}
])
Output format:
{
"name" : "John"
}
{
"name" : "Jane"
}
{
"name" : "Mike"
}
Approach 1 would be faster, but require additional work at app layer. It is recommended to offload formatting tasks to app servers rather than on db itself.
Approach 2 can instantly give to the formatted results, doing the querying and formatting both in the database servers
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