MongoDB查询填充的字段 [英] MongoDB query on populated fields

问题描述

我有一些名为活动的模型，我正在查询（使用Mongoose）。他们的模式如下所示：

I have models called "Activities" that I am querying for (using Mongoose). Their schema looks like this:

var activitySchema = new mongoose.Schema({
    actor: {
        type: mongoose.Schema.ObjectId,
        ref: 'User',
        required: true
    },
    recipient: {
        type: mongoose.Schema.ObjectId,
        ref: 'User'
    },
    timestamp: {
        type: Date, 
        default: Date.now
    },
    activity: {
        type: String,
        required: true
    },
    event: {
        type: mongoose.Schema.ObjectId,
        ref: 'Event'
    },
    comment: {
        type: mongoose.Schema.ObjectId,
        ref: 'Comment'
    }
});

当我查询它们时，我正在填充 actor ，收件人，事件和评论字段（所有参考文献）。之后，我还深入填充事件字段以获取 event.creator 。以下是我的查询代码：

When I query for them, I am populating the actor, recipient, event, and comment fields (all the references). After that, I also deep-populate the event field to get event.creator. Here is my code for the query:

var activityPopulateObj = [
                { path: 'event' },
                { path: 'event.creator' },
                { path: 'comment' },
                { path: 'actor' },
                { path: 'recipient' },
                { path: 'event.creator' }
            ],
            eventPopulateObj = {
                path: 'event.creator',
                model: User
            };

Activity.find({ $or: [{recipient: user._id}, {actor: {$in: user.subscriptions}}, {event: {$in: user.attending}}], actor: { $ne: user._id} })
            .sort({ _id: -1 })
            .populate(activityPopulateObj)
            .exec(function(err, retrievedActivities) {
                if(err || !retrievedActivities) {
                    deferred.reject(new Error("No events found."));
                }
                else {
                    User.populate(retrievedActivities, eventPopulateObj, function(err, data){
                        if(err) {
                            deferred.reject(err.message);
                        }
                        else {
                            deferred.resolve(retrievedActivities);
                        }
                    });
                }
            });

这已经是一个相对复杂的查询，但我需要做更多。如果它击中 $或语句中 {actor：{$ in：user.subscriptions}} 的部分，我还需要确保事件的隐私字段等于字符串 public 。我尝试使用 $ elemMatch ，但由于事件必须首先填充，我无法查询其任何字段。我还需要在多个其他查询中实现同样的目标。

This is already a relatively complex query, but I need to do even more. If it hits the part of the $or statement that says {actor: {$in: user.subscriptions}}, I also need to make sure that the event's privacy field is equal to the string public. I tried using $elemMatch, but since the event has to be populated first, I couldn't query any of its fields. I need to achieve this same goal in multiple other queries, as well.

我有没有办法像我所描述的那样实现这种进一步的过滤？

Is there any way for me to achieve this further filtering like I have described?

推荐答案

答案是改变您的架构。

你已陷入从使用关系数据库的历史进入文档数据库开发时，许多开发人员面前的陷阱：MongoDB不是关系数据库，不应该被视为一个。

You've fallen into the trap that many devs have before you when coming into document database development from a history of using relational databases: MongoDB is not a relational database and should not be treated like one.

您需要停止考虑外键和完全标准化的数据，而是尽可能保持每个文档的自包含，考虑如何在文档中最好地嵌入相关的相关数据。

You need to stop thinking about foreign keys and perfectly normalized data and instead, keep each document as self-contained as possible, thinking about how to best embed relevant associated data within your documents.

这并不意味着您也无法维护关联。它可能意味着这样的结构，您只需要嵌入必要的详细信息，并在需要时查询完整记录：

This doesn't mean you can't maintain associations as well. It might mean a structure like this, where you embed only necessary details, and query for the full record when needed:

var activitySchema = new mongoose.Schema({
  event: {
    _id: { type: ObjectId, ref: "Event" },
    name: String,
    private: String
  },

  // ... other fields
});

重新思考您的嵌入策略将极大地简化您的查询并保持查询次数至少。 填充会快速计算您的数量，随着数据集的增长，这很可能会成为一个问题。

Rethinking your embed strategy will greatly simplify your queries and keep the query count to a minimum. populate will blow your count up quickly, and as your dataset grows this will very likely become a problem.

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