mongodb 为每个检索到的文档添加计数器 [英] mongodb add counter to each retrieved document

问题描述

嘿，有没有办法向从 mongo 检索到的每个文档添加一个计数器?

Hey is there a way to add to each document retrieved from mongo a counter?

假设我们在 mongo 中有用户:{_id, name}.我想全部获取它们，并为每个检索到的文档添加一个计数器字段，并在获取文档时增加它.

So lets say we have users : {_id, name} in mongo . I want to fetch them all and to each retrieved document I want to add a counter field and increase it as I fetch the docs.

所以结果是

users : [{_id: "some_id_1", name: "john", counter: 1}, {_id: "some_id_2", name: "bob", counter: 2]

所以这个计数器字段会动态生成?

so this counter field would be generated on the fly ?

推荐答案

为了完成前面的 3 个答案，我写了另一个答案.

I write another answer in order to complete the 3 previous ones.

我对这三个答案进行了一些(简单的)基准测试.

I realized some (simple) benchmarkings on these three answers.

数据集:10000 个文档，如下所示:

Dataset : 10000 documents like the following :

{ 
    "_id" : "5e7b55cb911ef7ebdfd72c08", 
    "name" : "Dominguez"
}

我循环运行了 3 个聚合集 1000 次.

I ran the 3 aggregations set 1000 times in a loop.

var results=[];
for(i=0;i<1000;i++){ 

    var before = new Date();
    tmp_res_matthPen=db.testing.aggregate(aggregation_mpenicaud);
    var after = new Date();
    var mpe = after-before;

    var before = new Date();
    tmp_res_prasad=db.testing.aggregate(aggregation_prasad);
    var after = new Date();
    var pra = after-before;

    var before = new Date();
    tmp_res_valijon=db.testing.aggregate(aggregation_valijon);
    var after = new Date();
    var val = after-before;

    results.push({"pra":pra,"val":val,"mpe":mpe});
}
db.results.insert(results);

这是提供答案的平均值(以毫秒为单位):

        "mpe" : 7.725, 
        "val" : 15.441, 
        "pra" : 14.911

但是...查看 Valijon 的回答，我注意到 $sort 阶段在这里都不是很有用，因为没有问(并且 _id 字段通常已经根据时间按 _id 生成排序).有些我尝试从管道中删除它们.

BUT ... Looking at the Valijon's answer, i noticed that both $sort stage are not very useful here, as not asked (and _id field is often already sorted by _id generation based on time). Some i try to remove them from pipeline.

    "mpe" : 7.399, 
    "val" : 7.149, 
    "pra" : 13.541

并在所有管道中的 _id 上添加 $sort 阶段(此处 _id 充当索引字段)

And adding a $sort stage on _id in all pipelines (here _id acts as an indexed field)

    "mpe" : 17.518, 
    "val" : 16.166, 
    "pra" : 23.078

最后，我按名称排序，因为它没有编入索引并且是随机生成的.

And finally, i sort by name, as it is not indexed and randomly generated.

"mpe" : 16.858, 
"val" : 14.27, 
"pra" : 24.777

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