I'm pretty new to Mongoose and MongoDB in general so I'm having a difficult time figuring out if something like this is possible:
Item = new Schema({
id: Schema.ObjectId,
dateCreated: { type: Date, default: Date.now },
title: { type: String, default: 'No Title' },
description: { type: String, default: 'No Description' },
tags: [ { type: Schema.ObjectId, ref: 'ItemTag' }]
});
ItemTag = new Schema({
id: Schema.ObjectId,
tagId: { type: Schema.ObjectId, ref: 'Tag' },
tagName: { type: String }
});
var query = Models.Item.find({});
query
.desc('dateCreated')
.populate('tags')
.where('tags.tagName').in(['funny', 'politics'])
.run(function(err, docs){
// docs is always empty
});
Is there a better way do this?
Edit
Apologies for any confusion. What I'm trying to do is get all Items that contain either the funny tag or politics tag.
Edit
Document without where clause:
[{
_id: 4fe90264e5caa33f04000012,
dislikes: 0,
likes: 0,
source: '/uploads/loldog.jpg',
comments: [],
tags: [{
itemId: 4fe90264e5caa33f04000012,
tagName: 'movies',
tagId: 4fe64219007e20e644000007,
_id: 4fe90270e5caa33f04000015,
dateCreated: Tue, 26 Jun 2012 00:29:36 GMT,
rating: 0,
dislikes: 0,
likes: 0
},
{
itemId: 4fe90264e5caa33f04000012,
tagName: 'funny',
tagId: 4fe64219007e20e644000002,
_id: 4fe90270e5caa33f04000017,
dateCreated: Tue, 26 Jun 2012 00:29:36 GMT,
rating: 0,
dislikes: 0,
likes: 0
}],
viewCount: 0,
rating: 0,
type: 'image',
description: null,
title: 'dogggg',
dateCreated: Tue, 26 Jun 2012 00:29:24 GMT
}, ... ]
With the where clause, I get an empty array.
With a modern MongoDB greater than 3.2 you can use $lookup as an alternate to .populate() in most cases. This also has the advantage of actually doing the join "on the server" as opposed to what .populate() does which is actually "multiple queries" to "emulate" a join.
So .populate() is not really a "join" in the sense of how a relational database does it. The $lookup operator on the other hand, actually does the work on the server, and is more or less analogous to a "LEFT JOIN":
Item.aggregate(
[
{ "$lookup": {
"from": ItemTags.collection.name,
"localField": "tags",
"foreignField": "_id",
"as": "tags"
}},
{ "$unwind": "$tags" },
{ "$match": { "tags.tagName": { "$in": [ "funny", "politics" ] } } },
{ "$group": {
"_id": "$_id",
"dateCreated": { "$first": "$dateCreated" },
"title": { "$first": "$title" },
"description": { "$first": "$description" },
"tags": { "$push": "$tags" }
}}
],
function(err, result) {
// "tags" is now filtered by condition and "joined"
}
)
N.B. The .collection.name here actually evaluates to the "string" that is the actual name of the MongoDB collection as assigned to the model. Since mongoose "pluralizes" collection names by default and $lookup needs the actual MongoDB collection name as an argument ( since it's a server operation ), then this is a handy trick to use in mongoose code, as opposed to "hard coding" the collection name directly.
Whilst we could also use $filter on arrays to remove the unwanted items, this is actually the most efficient form due to Aggregation Pipeline Optimization for the special condition of as $lookup followed by both an $unwind and a $match condition.
This actually results in the three pipeline stages being rolled into one:
{ "$lookup" : {
"from" : "itemtags",
"as" : "tags",
"localField" : "tags",
"foreignField" : "_id",
"unwinding" : {
"preserveNullAndEmptyArrays" : false
},
"matching" : {
"tagName" : {
"$in" : [
"funny",
"politics"
]
}
}
}}
This is highly optimal as the actual operation "filters the collection to join first", then it returns the results and "unwinds" the array. Both methods are employed so the results do not break the BSON limit of 16MB, which is a constraint that the client does not have.
The only problem is that it seems "counter-intuitive" in some ways, particularly when you want the results in an array, but that is what the $group is for here, as it reconstructs to the original document form.
It's also unfortunate that we simply cannot at this time actually write $lookup in the same eventual syntax the server uses. IMHO, this is an oversight to be corrected. But for now, simply using the sequence will work and is the most viable option with the best performance and scalability.
Addendum - MongoDB 3.6 and upwards
Though the pattern shown here is fairly optimized due to how the other stages get rolled into the $lookup, it does have one failing in that the "LEFT JOIN" which is normally inherent to both $lookup and the actions of populate() is negated by the "optimal" usage of $unwind here which does not preserve empty arrays. You can add the preserveNullAndEmptyArrays option, but this negates the "optimized" sequence described above and essentially leaves all three stages intact which would normally be combined in the optimization.
MongoDB 3.6 expands with a "more expressive" form of $lookup allowing a "sub-pipeline" expression. Which not only meets the goal of retaining the "LEFT JOIN" but still allows an optimal query to reduce results returned and with a much simplified syntax:
Item.aggregate([
{ "$lookup": {
"from": ItemTags.collection.name,
"let": { "tags": "$tags" },
"pipeline": [
{ "$match": {
"tags": { "$in": [ "politics", "funny" ] },
"$expr": { "$in": [ "$_id", "$$tags" ] }
}}
]
}}
])
The $expr used in order to match the declared "local" value with the "foreign" value is actually what MongoDB does "internally" now with the original $lookup syntax. By expressing in this form we can tailor the initial $match expression within the "sub-pipeline" ourselves.
In fact, as a true "aggregation pipeline" you can do just about anything you can do with an aggregation pipeline within this "sub-pipeline" expression, including "nesting" the levels of $lookup to other related collections.
Further usage is a bit beyond the scope of what the question here asks, but in relation to even "nested population" then the new usage pattern of $lookup allows this to be much the same, and a "lot" more powerful in it's full usage.
Working Example
The following gives an example using a static method on the model. Once that static method is implemented the call simply becomes:
Item.lookup(
{
path: 'tags',
query: { 'tags.tagName' : { '$in': [ 'funny', 'politics' ] } }
},
callback
)
Or enhancing to be a bit more modern even becomes:
let results = await Item.lookup({
path: 'tags',
query: { 'tagName' : { '$in': [ 'funny', 'politics' ] } }
})
Making it very similar to .populate() in structure, but it's actually doing the join on the server instead. For completeness, the usage here casts the returned data back to mongoose document instances at according to both the parent and child cases.
It's fairly trivial and easy to adapt or just use as is for most common cases.
N.B The use of async here is just for brevity of running the enclosed example. The actual implementation is free of this dependency.
const async = require('async'),
mongoose = require('mongoose'),
Schema = mongoose.Schema;
mongoose.Promise = global.Promise;
mongoose.set('debug', true);
mongoose.connect('mongodb://localhost/looktest');
const itemTagSchema = new Schema({
tagName: String
});
const itemSchema = new Schema({
dateCreated: { type: Date, default: Date.now },
title: String,
description: String,
tags: [{ type: Schema.Types.ObjectId, ref: 'ItemTag' }]
});
itemSchema.statics.lookup = function(opt,callback) {
let rel =
mongoose.model(this.schema.path(opt.path).caster.options.ref);
let group = { "$group": { } };
this.schema.eachPath(p =>
group.$group[p] = (p === "_id") ? "$_id" :
(p === opt.path) ? { "$push": `$${p}` } : { "$first": `$${p}` });
let pipeline = [
{ "$lookup": {
"from": rel.collection.name,
"as": opt.path,
"localField": opt.path,
"foreignField": "_id"
}},
{ "$unwind": `$${opt.path}` },
{ "$match": opt.query },
group
];
this.aggregate(pipeline,(err,result) => {
if (err) callback(err);
result = result.map(m => {
m[opt.path] = m[opt.path].map(r => rel(r));
return this(m);
});
callback(err,result);
});
}
const Item = mongoose.model('Item', itemSchema);
const ItemTag = mongoose.model('ItemTag', itemTagSchema);
function log(body) {
console.log(JSON.stringify(body, undefined, 2))
}
async.series(
[
// Clean data
(callback) => async.each(mongoose.models,(model,callback) =>
model.remove({},callback),callback),
// Create tags and items
(callback) =>
async.waterfall(
[
(callback) =>
ItemTag.create([{ "tagName": "movies" }, { "tagName": "funny" }],
callback),
(tags, callback) =>
Item.create({ "title": "Something","description": "An item",
"tags": tags },callback)
],
callback
),
// Query with our static
(callback) =>
Item.lookup(
{
path: 'tags',
query: { 'tags.tagName' : { '$in': [ 'funny', 'politics' ] } }
},
callback
)
],
(err,results) => {
if (err) throw err;
let result = results.pop();
log(result);
mongoose.disconnect();
}
)
Or a little more modern for Node 8.x and above with async/await and no additional dependencies:
const { Schema } = mongoose = require('mongoose');
const uri = 'mongodb://localhost/looktest';
mongoose.Promise = global.Promise;
mongoose.set('debug', true);
const itemTagSchema = new Schema({
tagName: String
});
const itemSchema = new Schema({
dateCreated: { type: Date, default: Date.now },
title: String,
description: String,
tags: [{ type: Schema.Types.ObjectId, ref: 'ItemTag' }]
});
itemSchema.statics.lookup = function(opt) {
let rel =
mongoose.model(this.schema.path(opt.path).caster.options.ref);
let group = { "$group": { } };
this.schema.eachPath(p =>
group.$group[p] = (p === "_id") ? "$_id" :
(p === opt.path) ? { "$push": `$${p}` } : { "$first": `$${p}` });
let pipeline = [
{ "$lookup": {
"from": rel.collection.name,
"as": opt.path,
"localField": opt.path,
"foreignField": "_id"
}},
{ "$unwind": `$${opt.path}` },
{ "$match": opt.query },
group
];
return this.aggregate(pipeline).exec().then(r => r.map(m =>
this({ ...m, [opt.path]: m[opt.path].map(r => rel(r)) })
));
}
const Item = mongoose.model('Item', itemSchema);
const ItemTag = mongoose.model('ItemTag', itemTagSchema);
const log = body => console.log(JSON.stringify(body, undefined, 2));
(async function() {
try {
const conn = await mongoose.connect(uri);
// Clean data
await Promise.all(Object.entries(conn.models).map(([k,m]) => m.remove()));
// Create tags and items
const tags = await ItemTag.create(
["movies", "funny"].map(tagName =>({ tagName }))
);
const item = await Item.create({
"title": "Something",
"description": "An item",
tags
});
// Query with our static
const result = (await Item.lookup({
path: 'tags',
query: { 'tags.tagName' : { '$in': [ 'funny', 'politics' ] } }
})).pop();
log(result);
mongoose.disconnect();
} catch (e) {
console.error(e);
} finally {
process.exit()
}
})()
And from MongoDB 3.6 and upward, even without the $unwind and $group building:
const { Schema, Types: { ObjectId } } = mongoose = require('mongoose');
const uri = 'mongodb://localhost/looktest';
mongoose.Promise = global.Promise;
mongoose.set('debug', true);
const itemTagSchema = new Schema({
tagName: String
});
const itemSchema = new Schema({
title: String,
description: String,
tags: [{ type: Schema.Types.ObjectId, ref: 'ItemTag' }]
},{ timestamps: true });
itemSchema.statics.lookup = function({ path, query }) {
let rel =
mongoose.model(this.schema.path(path).caster.options.ref);
// MongoDB 3.6 and up $lookup with sub-pipeline
let pipeline = [
{ "$lookup": {
"from": rel.collection.name,
"as": path,
"let": { [path]: `$${path}` },
"pipeline": [
{ "$match": {
...query,
"$expr": { "$in": [ "$_id", `$$${path}` ] }
}}
]
}}
];
return this.aggregate(pipeline).exec().then(r => r.map(m =>
this({ ...m, [path]: m[path].map(r => rel(r)) })
));
};
const Item = mongoose.model('Item', itemSchema);
const ItemTag = mongoose.model('ItemTag', itemTagSchema);
const log = body => console.log(JSON.stringify(body, undefined, 2));
(async function() {
try {
const conn = await mongoose.connect(uri);
// Clean data
await Promise.all(Object.entries(conn.models).map(([k,m]) => m.remove()));
// Create tags and items
const tags = await ItemTag.insertMany(
["movies", "funny"].map(tagName => ({ tagName }))
);
const item = await Item.create({
"title": "Something",
"description": "An item",
tags
});
// Query with our static
let result = (await Item.lookup({
path: 'tags',
query: { 'tagName': { '$in': [ 'funny', 'politics' ] } }
})).pop();
log(result);
await mongoose.disconnect();
} catch(e) {
console.error(e)
} finally {
process.exit()
}
})()
what you are asking for isn't directly supported but can be achieved by adding another filter step after the query returns.
first, .populate( 'tags', null, { tagName: { $in: ['funny', 'politics'] } } ) is definitely what you need to do to filter the tags documents. then, after the query returns you'll need to manually filter out documents that don't have any tags docs that matched the populate criteria. something like:
query....
.exec(function(err, docs){
docs = docs.filter(function(doc){
return doc.tags.length;
})
// do stuff with docs
});
Try replacing
.populate('tags').where('tags.tagName').in(['funny', 'politics'])
by
.populate( 'tags', null, { tagName: { $in: ['funny', 'politics'] } } )
Update: Please take a look at the comments - this answer does not correctly match to the question, but maybe it answers other questions of users which came across (I think that because of the upvotes) so I will not delete this "answer":
First: I know this question is really outdated, but I searched for exactly this problem and this SO post was the Google entry #1. So I implemented the docs.filter version (accepted answer) but as I read in the mongoose v4.6.0 docs we can now simply use:
Item.find({}).populate({
path: 'tags',
match: { tagName: { $in: ['funny', 'politics'] }}
}).exec((err, items) => {
console.log(items.tags)
// contains only tags where tagName is 'funny' or 'politics'
})
Hope this helps future search machine users.
After having the same problem myself recently, I've come up with the following solution:
First, find all ItemTags where tagName is either 'funny' or 'politics' and return an array of ItemTag _ids.
Then, find Items which contain all ItemTag _ids in the tags array
ItemTag
.find({ tagName : { $in : ['funny','politics'] } })
.lean()
.distinct('_id')
.exec((err, itemTagIds) => {
if (err) { console.error(err); }
Item.find({ tag: { $all: itemTagIds} }, (err, items) => {
console.log(items); // Items filtered by tagName
});
});
#aaronheckmann 's answer worked for me but I had to replace return doc.tags.length; to return doc.tags != null; because that field contain null if it doesn't match with the conditions written inside populate.
So the final code:
query....
.exec(function(err, docs){
docs = docs.filter(function(doc){
return doc.tags != null;
})
// do stuff with docs
});
I faced with this challenge to assign array to another array such that the arrays won't be reactive on changes from one of the array.
So to achieve this I made a local copy of the same array and assigned one to another but I would love to do stuffs dynamically where I am having the reactive issues.
Below is what am trying to achieve
const ComponentA = {
data: function() {
return {
categories:[
{
name: 'Category 1',
series: [
{
name: 'Series 1',
value: 5
},
{
name: 'Series 2',
value: 5
}
]
},
{
name: 'Category 2',
series: [
{
name: 'Series 1',
value: 50
},
{
name: 'Series 2',
value: 56
}
]
}
],
tempCategories:[
{
name: 'Category 1',
series: [
{
name: 'Series 1',
value: 5
},
{
name: 'Series 2',
value: 5
}
]
},
{
name: 'Category 2',
series: [
{
name: 'Series 1',
value: 50
},
{
name: 'Series 2',
value: 56
}
]
}
]
}
},
methods: {
resetCategory() {
this.tempCategories.forEach((category,i)=>{
category.series.forEach((series,j)=>{
this.categories[i].series[j] = series;
});
});
}
}
}
after computations on categories i can reset the categories array with tempCategories by calling
this.resetCategory() and it works as expected.
Meanwhile I want to be able to do this assignment dynamically whereby when i have copy of the category array I can assign the array to both categories and tempCategories arrays, respectively and after computations with categories array i can reset the categories array with tempCategories array. So I did the following.
initialize(category) {
this.tempCategories = category;
this.categories = category;
}
I realize changes in this.categories reflects on this.tempCategories; I've even used the following options
initialize(category) {
this.tempCategories = category.slice();
//or this.tempCategories = Json.parse(Json.stringify(category));
this.categories = category.slice();
//or this.categories = Json.parse(Json.stringify(category));
}
yet the two arrays are still reactive. Please I need help on how to solve this problem.
Thanks guys, it works now both method
initialize(categories){
//let copy = _.cloneDeep(categories);
let copy = JSON.parse(JSON.stringify(categories));
this.tempCategories = copy;
this.categories = copy;
},
resetCategories(){
//this.categories = _.cloneDeep(this.tempCategories);
this.categories = JSON.parse(JSON.stringify(this.tempCategories));
},
There's no such Json. but It may be JSON.
initialize(category) {
this.tempCategories = JSON.parse(JSON.stringify(category));
this.categories = JSON.parse(JSON.stringify(category));
}
And you can't prevent fake copy of by
this.tempCategories = category;
this.categories = category;
May be those three Arrays are exactly same even one of them is updated.
I have two tables defined "posts" and "comments". I want to get all posts and a number of there total comments, split by the comment type. Currently I can get the count, but cannot separate by comment type
const Sequelize = require('sequelize');
const sequelize = new Sequelize('postgres://username#localhost:5432/test');
const posts = sequelize.define('posts', {
name: Sequelize.STRING,
})
const comments = sequelize.define('comments', {
title: Sequelize.STRING,
type: Sequelize.STRING
})
posts.hasMany(comments);
comments.belongsTo(posts);
const importData = async () => {
// Insert test data
await sequelize.sync({ force: true });
await posts.create({ id: 1, name: 'Hello World' })
await comments.create({ postId: 1, title: 'This is great', type: 'text' })
await comments.create({ postId: 1, title: 'Thanks', type: 'text' })
await comments.create({ postId: 1, title: 'Oh Yeah', type: 'image' })
await comments.create({ postId: 1, title: 'Oh Yeah', type: 'video' })
// Fetch data
const post = await posts.findAll({
where: { id: 1 },
attributes: ['id', 'name', [sequelize.fn('COUNT', 'comments.id'), 'commentCount']],
include: [{ model: comments, attributes: [] }],
group: ['posts.id']
})
console.log(JSON.stringify(post, null, 4))
}
importData();
Output is
[
{
"id": 1,
"name": "Hello World",
"commentCount": "4"
}
]
Desired Output
[
{
"id": 1,
"name": "Hello World",
"commentCount": { "text": 2, "image": 1, "video": 1 }
}
]
Can this be done through Sequelize, or even raw SQL?
Raw SQL something like:
SELECT P.ID, C.Comment_Count, C.Type
FROM POSTS P
LEFT JOIN (SELECT count(*) Comment_Count, PostID, type
FROM Comments
GROUP BY POSTID, type) C
on P.ID = C.PostID
change
PostID to the column name in comments that is the FK to posts
change ID to the PK in posts.
I new to learn dojo and trying to learn by it using samples code.
Using dojo 1.6
With help of sample codes , I created a tree
now i want to apply sorting on root and also on child.
With the help of this sample code , i changed the code
Output is not sorted n but the root folder has changed their position and child is deleted.
Plz help me to resolve this.
My code :
dojo.require("dojo.data.ItemFileWriteStore");
dojo.require("dojo.data.ItemFileReadStore");
dojo.require("dijit.tree.ForestStoreModel");
dojo.require("dijit.Tree");
var data = [ { id: 1, name: "answerTypeLabel", type:'scenario', children:[{_reference: 2}]},
{ id: 2, name: "acceptRequestLabel", type:'paragraph', data: "acceptRequestLabel"},
{ id: 3, name: "rejectRequestLabel", type:'scenario', children:[{_reference: 5},{_reference: 6}]},
{ id: 4, name: "MoreInformationLabel", type:'scenario', children:[{_reference: 7},{_reference: 8}]},
{ id: 5, name: "rejectRequestStatusLabel", type:'paragraph', data: "rejectRequestStatusLabel"},
{ id: 6, name: "rejectRequestNotCoveredLabel", type:'paragraph', data: "rejectRequestNotCoveredLabel" },
{ id: 7, name: "MoreInformationDocumentLabel", type:'paragraph', data: "MoreInformationDocumentLabel"},
{ id: 8, name: "MoreInformationDataLabel", type:'paragraph', data: "MoreInformationDataLabel"}
];
dojo.addOnLoad(function() {
var sortableStore = new dojo.data.ItemFileReadStore({
data: {
identifier: 'id',
label: 'name',
items: data
}
});
var model = new dijit.tree.ForestStoreModel({
rootLabel: 'Names',
store: new dojo.data.ItemFileWriteStore({
data: {
identifier: 'id',
items: [],
label: 'name'
}
}) // blank itemsstore
})
var tree = new dijit.Tree({
model: model,
updateItems: function(items) {
var self = this;
console.log('pre', this.model.root.children);
dojo.forEach(items, function(newItem) {
console.log('add', newItem);
try {
self.model.store.newItem({
id: sortableStore.getValue(newItem, 'id'),
name: sortableStore.getValue(newItem, 'name'),
type: sortableStore.getValue(newItem, 'type'),
data: sortableStore.getValue(newItem, 'data'),
});
} catch (e) {
console.log(e);
}
});
console.log('post', this.model.root.children);
console.log("children: ", this.rootNode.getChildren());
},
});
tree.placeAt(dojo.body());
sortableStore.fetch({
query: {
type:'scenario'
},
sort: [{
attribute: "name"}],
onComplete: function(items) {
console.log(items, 'sorted');
tree.updateItems(items);
}
})
});
Output :
The 'Names' origins from you setting 'rootLabel'.
Btw, fiddles have revisions and is simply a paste-bin like feature :)
You need to use the tree model pasteItem to insert referenced items (the 'children' property of each 'newItem').
Otherwise, there's another approach, if you get rid of the '_reference' structure of your data. See: http://jsfiddle.net/GHFdA/1/