许多人使用猫鼬

Question

我有两个型号:

Item.js

const mongoose = require('mongoose');

const itemSchema = new mongoose.Schema({
   name: String,
   stores: [{ type: mongoose.Schema.Types.ObjectId, ref: 'Store' }]
});

const Item = mongoose.model('Item', itemSchema);

module.exports = Item;

Store.js

const mongoose = require('mongoose');

const storeSchema = new mongoose.Schema({
   name: String,
   items: [{ type: mongoose.Schema.Types.ObjectId, ref: 'Item' }]
});

const Store = mongoose.model('Store', storeSchema);

module.exports = Store;

还有一个seed.js文件:

const faker = require('faker');
const Store = require('./models/Store');
const Item = require('./models/Item');

console.log('Seeding..');

let item = new Item({
   name: faker.name.findName() + " Item"
});

item.save((err) => {
   if (err) return;

   let store = new Store({
      name: faker.name.findName() + " Store"
   });
   store.items.push(item);
   store.save((err) => {
      if (err) return;
   })
});

的store保存用items含有1阵列item.该item但是,没有stores.我错过了什么？如何自动更新MongoDB/Mongoose中的多对多关系？我习惯了Rails,一切都是自动完成的.

Answer 1

The problem you presently have is that you saved the reference in one model but you did not save it in the other. There is no "automatic referential integrity" in MongoDB, and such concept of "relations" are really a "manual" affair, and in fact the case with .populate() is actually a whole bunch of additional queries in order to retrieve the referenced information. No "magic" here.

Correct handling of "many to many" comes down to three options:

Listing 1 - Keep arrays on Both documents

Following your current design, the parts you are missing is storing the referenced on "both" the related items. For a listing to demonstrate:

const { Schema } = mongoose = require('mongoose');

mongoose.Promise = global.Promise;
mongoose.set('debug',true);
mongoose.set('useFindAndModify', false);
mongoose.set('useCreateIndex', true);

const uri = 'mongodb://localhost:27017/manydemo',
      options = { useNewUrlParser: true };

const itemSchema = new Schema({
  name: String,
  stores: [{ type: Schema.Types.ObjectId, ref: 'Store' }]
});

const storeSchema = new Schema({
  name: String,
  items: [{ type: Schema.Types.ObjectId, ref: 'Item' }]
});

const Item = mongoose.model('Item', itemSchema);
const Store = mongoose.model('Store', storeSchema);


const log = data => console.log(JSON.stringify(data,undefined,2))

(async function() {

  try {

    const conn = await mongoose.connect(uri,options);

    // Clean data
    await Promise.all(
      Object.entries(conn.models).map(([k,m]) => m.deleteMany() )
    );


    // Create some instances
    let [toothpaste,brush] = ['toothpaste','brush'].map(
      name => new Item({ name })
    );

    let [billsStore,tedsStore] = ['Bills','Teds'].map(
      name => new Store({ name })
    );

    // Add items to stores
    [billsStore,tedsStore].forEach( store => {
      store.items.push(toothpaste);   // add toothpaste to store
      toothpaste.stores.push(store);  // add store to toothpaste
    });

    // Brush is only in billsStore
    billsStore.items.push(brush);
    brush.stores.push(billsStore);

    // Save everything
    await Promise.all(
      [toothpaste,brush,billsStore,tedsStore].map( m => m.save() )
    );

    // Show stores
    let stores = await Store.find().populate('items','-stores');
    log(stores);

    // Show items
    let items = await Item.find().populate('stores','-items');
    log(items);

  } catch(e) {
    console.error(e);
  } finally {
    mongoose.disconnect();
  }

})();

This creates the "items" collection:

{
    "_id" : ObjectId("59ab96d9c079220dd8eec428"),
    "name" : "toothpaste",
    "stores" : [
            ObjectId("59ab96d9c079220dd8eec42a"),
            ObjectId("59ab96d9c079220dd8eec42b")
    ],
    "__v" : 0
}
{
    "_id" : ObjectId("59ab96d9c079220dd8eec429"),
    "name" : "brush",
    "stores" : [
            ObjectId("59ab96d9c079220dd8eec42a")
    ],
    "__v" : 0
}

And the "stores" collection:

{
    "_id" : ObjectId("59ab96d9c079220dd8eec42a"),
    "name" : "Bills",
    "items" : [
            ObjectId("59ab96d9c079220dd8eec428"),
            ObjectId("59ab96d9c079220dd8eec429")
    ],
    "__v" : 0
}
{
    "_id" : ObjectId("59ab96d9c079220dd8eec42b"),
    "name" : "Teds",
    "items" : [
            ObjectId("59ab96d9c079220dd8eec428")
    ],
    "__v" : 0
}

And produces overall output such as:

Mongoose: items.deleteMany({}, {})
Mongoose: stores.deleteMany({}, {})
Mongoose: items.insertOne({ name: 'toothpaste', _id: ObjectId("59ab96d9c079220dd8eec428"), stores: [ ObjectId("59ab96d9c079220dd8eec42a"), ObjectId("59ab96d9c079220dd8eec42b") ], __v: 0 })
Mongoose: items.insertOne({ name: 'brush', _id: ObjectId("59ab96d9c079220dd8eec429"), stores: [ ObjectId("59ab96d9c079220dd8eec42a") ], __v: 0 })
Mongoose: stores.insertOne({ name: 'Bills', _id: ObjectId("59ab96d9c079220dd8eec42a"), items: [ ObjectId("59ab96d9c079220dd8eec428"), ObjectId("59ab96d9c079220dd8eec429") ], __v: 0 })
Mongoose: stores.insertOne({ name: 'Teds', _id: ObjectId("59ab96d9c079220dd8eec42b"), items: [ ObjectId("59ab96d9c079220dd8eec428") ], __v: 0 })
Mongoose: stores.find({}, { fields: {} })
Mongoose: items.find({ _id: { '$in': [ ObjectId("59ab96d9c079220dd8eec428"), ObjectId("59ab96d9c079220dd8eec429") ] } }, { fields: { stores: 0 } })
[
  {
    "_id": "59ab96d9c079220dd8eec42a",
    "name": "Bills",
    "__v": 0,
    "items": [
      {
        "_id": "59ab96d9c079220dd8eec428",
        "name": "toothpaste",
        "__v": 0
      },
      {
        "_id": "59ab96d9c079220dd8eec429",
        "name": "brush",
        "__v": 0
      }
    ]
  },
  {
    "_id": "59ab96d9c079220dd8eec42b",
    "name": "Teds",
    "__v": 0,
    "items": [
      {
        "_id": "59ab96d9c079220dd8eec428",
        "name": "toothpaste",
        "__v": 0
      }
    ]
  }
]
Mongoose: items.find({}, { fields: {} })
Mongoose: stores.find({ _id: { '$in': [ ObjectId("59ab96d9c079220dd8eec42a"), ObjectId("59ab96d9c079220dd8eec42b") ] } }, { fields: { items: 0 } })
[
  {
    "_id": "59ab96d9c079220dd8eec428",
    "name": "toothpaste",
    "__v": 0,
    "stores": [
      {
        "_id": "59ab96d9c079220dd8eec42a",
        "name": "Bills",
        "__v": 0
      },
      {
        "_id": "59ab96d9c079220dd8eec42b",
        "name": "Teds",
        "__v": 0
      }
    ]
  },
  {
    "_id": "59ab96d9c079220dd8eec429",
    "name": "brush",
    "__v": 0,
    "stores": [
      {
        "_id": "59ab96d9c079220dd8eec42a",
        "name": "Bills",
        "__v": 0
      }
    ]
  }
]

The key points being that you actually add the reference data to each document in each collection where a relationship exists. The "arrays" present are used here to store those references and "lookup" the results from the related collection and replace them with the object data that was stored there.

Pay attention to parts like:

// Add items to stores
[billsStore,tedsStore].forEach( store => {
  store.items.push(toothpaste);   // add toothpaste to store
  toothpaste.stores.push(store);  // add store to toothpaste
});

Because that means not only are we adding the toothpaste to the "items" array in each store, but we are also adding each "store" to the "stores" array of the toothpaste item. This is done so the relationships can work being queried from either direction. If you only wanted "items from stores" and never "stores from items", then you would not need to store the relation data on the "item" entries at all.

Listing 2 - Use Virtuals and an Intermediary Collection

This is essentially the classic "many to many" relation. Where instead of directly defining relationships between the two collections, there is another collection ( table ) that stores the details about which item is related to which store.

As a full listing:

const { Schema } = mongoose = require('mongoose');

mongoose.Promise = global.Promise;
mongoose.set('debug',true);
mongoose.set('useFindAndModify', false);
mongoose.set('useCreateIndex', true);

const uri = 'mongodb://localhost:27017/manydemo',
      options = { useNewUrlParser: true };

const itemSchema = new Schema({
  name: String,
},{
 toJSON: { virtuals: true }
});

itemSchema.virtual('stores', {
  ref: 'StoreItem',
  localField: '_id',
  foreignField: 'itemId'
});

const storeSchema = new Schema({
  name: String,
},{
 toJSON: { virtuals: true }
});

storeSchema.virtual('items', {
  ref: 'StoreItem',
  localField: '_id',
  foreignField: 'storeId'
});

const storeItemSchema = new Schema({
  storeId: { type: Schema.Types.ObjectId, ref: 'Store', required: true },
  itemId: { type: Schema.Types.ObjectId, ref: 'Item', required: true }
});

const Item = mongoose.model('Item', itemSchema);
const Store = mongoose.model('Store', storeSchema);
const StoreItem = mongoose.model('StoreItem', storeItemSchema);

const log = data => console.log(JSON.stringify(data,undefined,2));

(async function() {

  try {

    const conn = await mongoose.connect(uri,options);

    // Clean data
    await Promise.all(
      Object.entries(conn.models).map(([k,m]) => m.deleteMany() )
    );

    // Create some instances
    let [toothpaste,brush] = await Item.insertMany(
      ['toothpaste','brush'].map( name => ({ name }) )
    );
    let [billsStore,tedsStore] = await Store.insertMany(
      ['Bills','Teds'].map( name => ({ name }) )
    );

    // Add toothpaste to both stores
    for( let store of [billsStore,tedsStore] ) {
      await StoreItem.update(
        { storeId: store._id, itemId: toothpaste._id },
        { },
        { 'upsert': true }
      );
    }

    // Add brush to billsStore
    await StoreItem.update(
      { storeId: billsStore._id, itemId: brush._id },
      {},
      { 'upsert': true }
    );

    // Show stores
    let stores = await Store.find().populate({
      path: 'items',
      populate: { path: 'itemId' }
    });
    log(stores);

    // Show Items
    let items = await Item.find().populate({
      path: 'stores',
      populate: { path: 'storeId' }
    });
    log(items);


  } catch(e) {
    console.error(e);
  } finally {
    mongoose.disconnect();
  }

})();

The relations are now in their own collection, so the data now appears differently, for "items":

{
    "_id" : ObjectId("59ab996166d5cc0e0d164d74"),
    "__v" : 0,
    "name" : "toothpaste"
}
{
    "_id" : ObjectId("59ab996166d5cc0e0d164d75"),
    "__v" : 0,
    "name" : "brush"
}

And "stores":

{
    "_id" : ObjectId("59ab996166d5cc0e0d164d76"),
    "__v" : 0,
    "name" : "Bills"
}
{
    "_id" : ObjectId("59ab996166d5cc0e0d164d77"),
    "__v" : 0,
    "name" : "Teds"
}

And now for "storeitems" which maps the relations:

{
    "_id" : ObjectId("59ab996179e41cc54405b72b"),
    "itemId" : ObjectId("59ab996166d5cc0e0d164d74"),
    "storeId" : ObjectId("59ab996166d5cc0e0d164d76"),
    "__v" : 0
}
{
    "_id" : ObjectId("59ab996179e41cc54405b72d"),
    "itemId" : ObjectId("59ab996166d5cc0e0d164d74"),
    "storeId" : ObjectId("59ab996166d5cc0e0d164d77"),
    "__v" : 0
}
{
    "_id" : ObjectId("59ab996179e41cc54405b72f"),
    "itemId" : ObjectId("59ab996166d5cc0e0d164d75"),
    "storeId" : ObjectId("59ab996166d5cc0e0d164d76"),
    "__v" : 0
}

With full output like:

Mongoose: items.deleteMany({}, {})
Mongoose: stores.deleteMany({}, {})
Mongoose: storeitems.deleteMany({}, {})
Mongoose: items.insertMany([ { __v: 0, name: 'toothpaste', _id: 59ab996166d5cc0e0d164d74 }, { __v: 0, name: 'brush', _id: 59ab996166d5cc0e0d164d75 } ])
Mongoose: stores.insertMany([ { __v: 0, name: 'Bills', _id: 59ab996166d5cc0e0d164d76 }, { __v: 0, name: 'Teds', _id: 59ab996166d5cc0e0d164d77 } ])
Mongoose: storeitems.update({ itemId: ObjectId("59ab996166d5cc0e0d164d74"), storeId: ObjectId("59ab996166d5cc0e0d164d76") }, { '$setOnInsert': { __v: 0 } }, { upsert: true })
Mongoose: storeitems.update({ itemId: ObjectId("59ab996166d5cc0e0d164d74"), storeId: ObjectId("59ab996166d5cc0e0d164d77") }, { '$setOnInsert': { __v: 0 } }, { upsert: true })
Mongoose: storeitems.update({ itemId: ObjectId("59ab996166d5cc0e0d164d75"), storeId: ObjectId("59ab996166d5cc0e0d164d76") }, { '$setOnInsert': { __v: 0 } }, { upsert: true })
Mongoose: stores.find({}, { fields: {} })
Mongoose: storeitems.find({ storeId: { '$in': [ ObjectId("59ab996166d5cc0e0d164d76"), ObjectId("59ab996166d5cc0e0d164d77") ] } }, { fields: {} })
Mongoose: items.find({ _id: { '$in': [ ObjectId("59ab996166d5cc0e0d164d74"), ObjectId("59ab996166d5cc0e0d164d75") ] } }, { fields: {} })
[
  {
    "_id": "59ab996166d5cc0e0d164d76",
    "__v": 0,
    "name": "Bills",
    "items": [
      {
        "_id": "59ab996179e41cc54405b72b",
        "itemId": {
          "_id": "59ab996166d5cc0e0d164d74",
          "__v": 0,
          "name": "toothpaste",
          "stores": null,
          "id": "59ab996166d5cc0e0d164d74"
        },
        "storeId": "59ab996166d5cc0e0d164d76",
        "__v": 0
      },
      {
        "_id": "59ab996179e41cc54405b72f",
        "itemId": {
          "_id": "59ab996166d5cc0e0d164d75",
          "__v": 0,
          "name": "brush",
          "stores": null,
          "id": "59ab996166d5cc0e0d164d75"
        },
        "storeId": "59ab996166d5cc0e0d164d76",
        "__v": 0
      }
    ],
    "id": "59ab996166d5cc0e0d164d76"
  },
  {
    "_id": "59ab996166d5cc0e0d164d77",
    "__v": 0,
    "name": "Teds",
    "items": [
      {
        "_id": "59ab996179e41cc54405b72d",
        "itemId": {
          "_id": "59ab996166d5cc0e0d164d74",
          "__v": 0,
          "name": "toothpaste",
          "stores": null,
          "id": "59ab996166d5cc0e0d164d74"
        },
        "storeId": "59ab996166d5cc0e0d164d77",
        "__v": 0
      }
    ],
    "id": "59ab996166d5cc0e0d164d77"
  }
]
Mongoose: items.find({}, { fields: {} })
Mongoose: storeitems.find({ itemId: { '$in': [ ObjectId("59ab996166d5cc0e0d164d74"), ObjectId("59ab996166d5cc0e0d164d75") ] } }, { fields: {} })
Mongoose: stores.find({ _id: { '$in': [ ObjectId("59ab996166d5cc0e0d164d76"), ObjectId("59ab996166d5cc0e0d164d77") ] } }, { fields: {} })
[
  {
    "_id": "59ab996166d5cc0e0d164d74",
    "__v": 0,
    "name": "toothpaste",
    "stores": [
      {
        "_id": "59ab996179e41cc54405b72b",
        "itemId": "59ab996166d5cc0e0d164d74",
        "storeId": {
          "_id": "59ab996166d5cc0e0d164d76",
          "__v": 0,
          "name": "Bills",
          "items": null,
          "id": "59ab996166d5cc0e0d164d76"
        },
        "__v": 0
      },
      {
        "_id": "59ab996179e41cc54405b72d",
        "itemId": "59ab996166d5cc0e0d164d74",
        "storeId": {
          "_id": "59ab996166d5cc0e0d164d77",
          "__v": 0,
          "name": "Teds",
          "items": null,
          "id": "59ab996166d5cc0e0d164d77"
        },
        "__v": 0
      }
    ],
    "id": "59ab996166d5cc0e0d164d74"
  },
  {
    "_id": "59ab996166d5cc0e0d164d75",
    "__v": 0,
    "name": "brush",
    "stores": [
      {
        "_id": "59ab996179e41cc54405b72f",
        "itemId": "59ab996166d5cc0e0d164d75",
        "storeId": {
          "_id": "59ab996166d5cc0e0d164d76",
          "__v": 0,
          "name": "Bills",
          "items": null,
          "id": "59ab996166d5cc0e0d164d76"
        },
        "__v": 0
      }
    ],
    "id": "59ab996166d5cc0e0d164d75"
  }
]

Since the relations are now mapped in a separate collection there are a couple of changes here. Notably we want to define a "virtual" field on the collection that no longer has a fixed array of items. So you add one as is shown:

const itemSchema = new Schema({
  name: String,
},{
 toJSON: { virtuals: true }
});

itemSchema.virtual('stores', {
  ref: 'StoreItem',
  localField: '_id',
  foreignField: 'itemId'
});

You assign the virtual field with it's localField and foreignField mappings so the subsequent .populate() call knows what to use.

The intermediary collection has a fairly standard definition:

const storeItemSchema = new Schema({
  storeId: { type: Schema.Types.ObjectId, ref: 'Store', required: true },
  itemId: { type: Schema.Types.ObjectId, ref: 'Item', required: true }
});

And instead of "pushing" new items onto arrays, we instead add them to this new collection. A reasonable method for this is using "upserts" to create a new entry only when this combination does not exist:

// Add toothpaste to both stores
for( let store of [billsStore,tedsStore] ) {
  await StoreItem.update(
    { storeId: store._id, itemId: toothpaste._id },
    { },
    { 'upsert': true }
  );
}

It's a pretty simple method that merely creates a new document with the two keys supplied in the query where one was not found, or essentially tries to update the same document when matched, and with "nothing" in this case. So existing matches just end up as a "no-op", which is the desired thing to do. Alternately you could simply .insertOne() an ignore duplicate key errors. Whatever takes your fancy.

Actually querying this "related" data works a little differently again. Because there is another collection involved, we call .populate() in a way that considers it needs to "lookup" the relation on other retrieved property as well. So you have calls like this:

 // Show stores
  let stores = await Store.find().populate({
    path: 'items',
    populate: { path: 'itemId' }
  });
  log(stores);

Listing 3 - Use Modern Features to do it on the server

So depending on which approach taken, being using arrays or an intermediary collection to store the relation data in as an alternative to "growing arrays" within the documents, then the obvious thing you should be noting is that the .populate() calls used are actually making additional queries to MongoDB and pulling those documents over the network in separate requests.

This might appear all well and fine in small doses, however as things scale up and especially over volumes of requests, this is never a good thing. Additionally there might well be other conditions you want to apply that means you don't need to pull all the documents from the server, and would rather match data from those "relations" before you returned results.

This is why modern MongoDB releases include $lookup which actually "joins" the data on the server itself. By now you should have been looking at all the output those API calls produce as shown by mongoose.set('debug',true).

So instead of producing multiple queries, this time we make it one aggregation statement to "join" on the server, and return the results in one request:

// Show Stores
let stores = await Store.aggregate([
  { '$lookup': {
    'from': StoreItem.collection.name,
    'let': { 'id': '$_id' },
    'pipeline': [
      { '$match': {
        '$expr': { '$eq': [ '$$id', '$storeId' ] }
      }},
      { '$lookup': {
        'from': Item.collection.name,
        'let': { 'itemId': '$itemId' },
        'pipeline': [
          { '$match': {
            '$expr': { '$eq': [ '$_id', '$$itemId' ] }
          }}
        ],
        'as': 'items'
      }},
      { '$unwind': '$items' },
      { '$replaceRoot': { 'newRoot': '$items' } }
    ],
    'as': 'items'
  }}
])
log(stores);

Which whilst longer in coding, is actually far superior in efficiency even for the very trivial action right here. This of course scales considerably.

Following the same "intermediary" model as before ( and just for example, because it could be done either way ) we have a full listing:

const { Schema } = mongoose = require('mongoose');

const uri = 'mongodb://localhost:27017/manydemo',
      options = { useNewUrlParser: true };

mongoose.Promise = global.Promise;
mongoose.set('debug', true);
mongoose.set('useFindAndModify', false);
mongoose.set('useCreateIndex', true);

const itemSchema = new Schema({
  name: String
}, {
  toJSON: { virtuals: true }
});

itemSchema.virtual('stores', {
  ref: 'StoreItem',
  localField: '_id',
  foreignField: 'itemId'
});

const storeSchema = new Schema({
  name: String
}, {
  toJSON: { virtuals: true }
});

storeSchema.virtual('items', {
  ref: 'StoreItem',
  localField: '_id',
  foreignField: 'storeId'
});

const storeItemSchema = new Schema({
  storeId: { type: Schema.Types.ObjectId, ref: 'Store', required: true },
  itemId: { type: Schema.Types.ObjectId, ref: 'Item', required: true }
});

const Item = mongoose.model('Item', itemSchema);
const Store = mongoose.model('Store', storeSchema);
const StoreItem = mongoose.model('StoreItem', storeItemSchema);

const log = data => console.log(JSON.stringify(data, undefined, 2));

(async function() {

  try {

    const conn = await mongoose.connect(uri, options);

    // Clean data
    await Promise.all(
      Object.entries(conn.models).map(([k,m]) => m.deleteMany())
    );

    // Create some instances
    let [toothpaste, brush] = await Item.insertMany(
      ['toothpaste', 'brush'].map(name => ({ name }) )
    );
    let [billsStore, tedsStore] = await Store.insertMany(
      ['Bills', 'Teds'].map( name => ({ name }) )
    );

    // Add toothpaste to both stores
    for ( let { _id: storeId }  of [billsStore, tedsStore] ) {
      await StoreItem.updateOne(
        { storeId, itemId: toothpaste._id },
        { },
        { 'upsert': true }
      );
    }

    // Add brush to billsStore
    await StoreItem.updateOne(
      { storeId: billsStore._id, itemId: brush._id },
      { },
      { 'upsert': true }
    );

    // Show Stores
    let stores = await Store.aggregate([
      { '$lookup': {
        'from': StoreItem.collection.name,
        'let': { 'id': '$_id' },
        'pipeline': [
          { '$match': {
            '$expr': { '$eq': [ '$$id', '$storeId' ] }
          }},
          { '$lookup': {
            'from': Item.collection.name,
            'let': { 'itemId': '$itemId' },
            'pipeline': [
              { '$match': {
                '$expr': { '$eq': [ '$_id', '$$itemId' ] }
              }}
            ],
            'as': 'items'
          }},
          { '$unwind': '$items' },
          { '$replaceRoot': { 'newRoot': '$items' } }
        ],
        'as': 'items'
      }}
    ])

    log(stores);

    // Show Items
    let items = await Item.aggregate([
      { '$lookup': {
        'from': StoreItem.collection.name,
        'let': { 'id': '$_id' },
        'pipeline': [
          { '$match': {
            '$expr': { '$eq': [ '$$id', '$itemId' ] }
          }},
          { '$lookup': {
            'from': Store.collection.name,
            'let': { 'storeId': '$storeId' },
            'pipeline': [
              { '$match': {
                '$expr': { '$eq': [ '$_id', '$$storeId' ] }
              }}
            ],
            'as': 'stores',
          }},
          { '$unwind': '$stores' },
          { '$replaceRoot': { 'newRoot': '$stores' } }
        ],
        'as': 'stores'
      }}
    ]);

    log(items);


  } catch(e) {
    console.error(e);
  } finally {
    mongoose.disconnect();
  }

})()

And the output:

Mongoose: stores.aggregate([ { '$lookup': { from: 'storeitems', let: { id: '$_id' }, pipeline: [ { '$match': { '$expr': { '$eq': [ '$$id', '$storeId' ] } } }, { '$lookup': { from: 'items', let: { itemId: '$itemId' }, pipeline: [ { '$match': { '$expr': { '$eq': [ '$_id', '$$itemId' ] } } } ], as: 'items' } }, { '$unwind': '$items' }, { '$replaceRoot': { newRoot: '$items' } } ], as: 'items' } } ], {})
[
  {
    "_id": "5ca7210717dadc69652b37da",
    "name": "Bills",
    "__v": 0,
    "items": [
      {
        "_id": "5ca7210717dadc69652b37d8",
        "name": "toothpaste",
        "__v": 0
      },
      {
        "_id": "5ca7210717dadc69652b37d9",
        "name": "brush",
        "__v": 0
      }
    ]
  },
  {
    "_id": "5ca7210717dadc69652b37db",
    "name": "Teds",
    "__v": 0,
    "items": [
      {
        "_id": "5ca7210717dadc69652b37d8",
        "name": "toothpaste",
        "__v": 0
      }
    ]
  }
]
Mongoose: items.aggregate([ { '$lookup': { from: 'storeitems', let: { id: '$_id' }, pipeline: [ { '$match': { '$expr': { '$eq': [ '$$id', '$itemId' ] } } }, { '$lookup': { from: 'stores', let: { storeId: '$storeId' }, pipeline: [ { '$match': { '$expr': { '$eq': [ '$_id', '$$storeId' ] } } } ], as: 'stores' } }, { '$unwind': '$stores' }, { '$replaceRoot': { newRoot: '$stores' } } ], as: 'stores' } } ], {})
[
  {
    "_id": "5ca7210717dadc69652b37d8",
    "name": "toothpaste",
    "__v": 0,
    "stores": [
      {
        "_id": "5ca7210717dadc69652b37da",
        "name": "Bills",
        "__v": 0
      },
      {
        "_id": "5ca7210717dadc69652b37db",
        "name": "Teds",
        "__v": 0
      }
    ]
  },
  {
    "_id": "5ca7210717dadc69652b37d9",
    "name": "brush",
    "__v": 0,
    "stores": [
      {
        "_id": "5ca7210717dadc69652b37da",
        "name": "Bills",
        "__v": 0
      }
    ]
  }
]

What should be obvious is the significant reduction in the queries issued on the end to return the "joined" form of the data. This means lower latency and more responsive applications as a result of removing all the network overhead.

Final Notes

Those a are generally your approaches to dealing with "many to many" relations, which essentially comes down to either:

• Keeping arrays in each document on either side holding the references to the related items.

• Storing an intermediary collection and using that as a lookup reference to retrieving the other data.

In all cases it is up to you to actually store those references if you expect things to work on "both directions". Of course $lookup and even "virtuals" where that applies means that you don't always need to store on every source since you could then "reference" in just one place and use that information by applying those methods.

The other case is of course "embedding", which is an entirely different game and what document oriented databases such as MongoDB are really all about. Therefore instead of "fetching from another collection" the concept is of course to "embed" the data.

This means not just the ObjectId values that point to the other items, but actually storing the full data within arrays in each document. There is of course an issue of "size" and of course issues with updating data in multiple places. This is generally the trade off for there being a single request and a simple request that does not need to go and find data in other collections because it's "already there".

There is plenty of material around on the subject of referencing vs embedding. Once such summary source is Mongoose populate vs object nesting or even the very general MongoDB relationships: embed or reference? and many many others.

You should spend some time thinking about the concepts and how this applies to your application in general. And note that you are not actually using an RDBMS here, so you might as well use the correct features that you are meant to exploit, rather than simply making one act like the other.

Answer 2

在对数据库进行建模之前，您首先应该考虑应用程序中数据的使用情况。

我没有你的申请的详细要求。但为什么必须在 2 个模式中保留 2 个引用呢？为什么不只保留 1 个来自Storeto 的Item引用（这意味着 1 个商店有很多商品），然后如果您想执行查询来查找某个商品属于哪个商店，也可以通过查询集合来完成Store。

另外，MongoDB中没有所谓的“多对多”。这取决于数据的使用方式，您必须找出形成集合之间关系以及构建数据库的有效方法。

无论如何，如果您仍然想使用当前的模式，您可以首先创建项目，然后创建商店并将创建的项目的 id 推入数组items，然后使用创建的商店 id 对项目执行更新。