问题描述
首先:我 - > MongoNoob我知道这已经有过一种或另一种方式的问题,但直到现在我还没有找到任何具体内容。
假设我有两个这样描述的Moongoose模型:
first: me -> MongoNoob and I know this has already been asked in one or the other way, but I haven't found anything specific until now.Let's say I have two Moongoose Models described like this:
var pollSchema = mongoose.Schema({
title: String,
choices: [{
content: String
}]
});
var choiceSchema = mongoose.Schema({
poll_id: mongoose.Schema.ObjectId,
option: Number
});
UI显示轮询,当用户选择一个选项时,它会被写入 choiceSchema
模型。现在我想创建一个'统计',告诉我有多少用户选择了选项1,选项2,选项3,....
我可以简单地用获取民意调查的所有选项找到
并在服务器代码中生成统计信息,但如果我有一百万用户选择,我将不得不处理相同大小的数组。这不可能是对的。
但是我可以生成一个查询并使用 count()
方法:
A UI shows the poll and when a user selects a choice, it is written into the choiceSchema
model. Now I would like to create a 'statistic', telling me how many users selected option 1, option 2, option 3,....I could simply fetch all choices for a poll with find
and generate the statistic in server code, but if I had a million user choices, I would have to deal with an array of the same size. This cannot be right.I could however generate a query and use the count()
method:
var query = Choice.find({poll_id: someId}),
query.where('option', 1);
var resultForOption1;
query.count(function(err, count)) {
resultForOption1 = count;
});
我如何为多个选项执行此操作并将结果加入(哈哈)到数组中?由于这都是异步的,我会嵌套调用,但这不是一个可变数量的查询的选项。
How would I do this for multiple options and 'join' (haha) the results into an array? Since this is all asynchronous I would have nest the calls, but that is not an option for a variable number of queries.
我是否想念树木: - )?有人可以指出我正确的方向吗?
Do I miss the wood for the trees :-)? Can somebody point me in the right direction?
BR,
Daniel
BR,Daniel
推荐答案
您可以使用 aggregate
来执行此操作:
You can use aggregate
to do this:
Choice.aggregate(
{$group: {_id: {poll_id: '$poll_id', option: '$option'}, count: {$sum: 1}}}
).exec(...);
这将对选项
集合文档进行分组 poll_id
和选项
并计算每个的出现次数,给出如下输出:
This will group the choices
collection docs by poll_id
and option
and count the occurrences of each, giving output that looks like:
{
"result": [
{
"_id": {
"poll_id": 2,
"option": 3
},
"count": 1
},
{
"_id": {
"poll_id": 1,
"option": 2
},
"count": 2
},
{
"_id": {
"poll_id": 2,
"option": 2
},
"count": 1
},
{
"_id": {
"poll_id": 1,
"option": 1
},
"count": 1
}
],
"ok": 1
}
然后您可以使用后续 $ group
和 $ project
您的汇总
管道中的阶段,以进一步分组和重塑基因根据需要评估文档。
You can then use subsequent $group
and $project
stages in your aggregate
pipeline to further group and reshape the generated docs as needed.
这篇关于多个mongoose count()查询到MongoDB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!