This article was my journey on NoSQL database lately this year, so this was from beginner to beginner guide.
MongoDB or NoSQL had been trending, but I still love SQL databases for some reason. However, MongoDB had a great Query Syntax (Despite on performance, etc.) that I admit I falling in love with that. I've been work with MongoDB quite sometimes now, and I want to share some tips on using aggregate! The powerful feature in MongoDB.
Oh yeah, you will be quite confused with the syntax, it looks like this :
.aggregate([{{{{{{{{{ }}}}}}}}}]) // I love aggregate, better use your space and get ready
We will learn how to use $facet, $match, $unwind, $project, and $group. Lest provide some data here first :
// Just a simple chat schema here for a real-world example
// RoomID for chat room since it chatting room
// Clients contains all clients on a room ~
{
"_id" : ObjectId("5d1449db6f934a2926c175d1"),
"clients" : [
"rooberduck@mail.com",
"sillybilly@mail.com"
],
"roomId" : 1,
"message" : [
{
"time" : ISODate("2019-06-27T04:44:49.528Z"),
"status" : "SEND",
"text" : "Hello!",
"sender" : "sillybilly@mail.com",
"receiver" : "rooberduck@mail.com",
"_id" : ObjectId("5d1449db6f934a2926c175d2")
},
{
"time" : ISODate("2019-06-27T04:54:49.528Z"),
"status" : "READ",
"text" : "Hello Wow Are You?",
"sender" : "rooberduck@mail.com",
"receiver" : "sillybilly@mail.com",
"_id" : ObjectId("5d1449ff6f934a2926c175d3")
}
],
"__v" : 0
....
}
1st case : get all message from one user and return his last message
Okay in order to do this you could use $match: { clients: "sillybilly@mail.com" } but how to display the last message only, you could use $project
In here project only takes what your requested field are, working with aggregate it is like working with stream or pipeline, you should care for every step of it.
db.chat.aggregate([
{ $match: { clients: "sillybilly@mail.com" } },
{ $project: { _id: "$roomId", message: { $slice: ["$message", -1] } } }
])
// result
[{
"_id" : 1,
"message" : [
{
"time" : ISODate("2019-06-27T04:54:49.528Z"),
"status" : "SEND",
"text" : "Hello!",
"sender" : "sillybilly@mail.com",
"receiver" : "rooberduck@mail.com",
"_id" : ObjectId("5d1449ff6f934a2926c175d3")
}
]
}, ... more other result ]
so $project takes field or result on previous result and project it, you can get the previous value of result by using "$" as long it matches the resulted field's.
"Ewww but how come that data are okay? you only had one message, why do you need an array? I don't need that! and why I should go to the message field takes array [0] and get sender" - a wholesome frontend developer.
2nd case: get what that frontend developer wants
Assume that you just select sillybilly as the sender, the one that uses your application, and other users that on clients array are other. $unwind to the rescue.
db.getCollection('chats').aggregate([
{ $match: { clients: "sillybilly@mail.com" } },
{ $unwind: "$clients" }
])
the result of that queries will give you deconstructed array element of matchning documents.
[{ foo: [bar, baz] }] // not using unwind
[{ foo: bar }, {foo: baz}] // using unwind $foo
// get that? so now every documents are decoupled
Okay then we can now get the receiver name :
db.getCollection('chats').aggregate([
{ $match: { clients: "sillybilly@mail.com" } },
{ $unwind: "$clients" },
{ $match: { clients: { $ne: 'sillybilly@mail.com' } } },
{ $project: {
_id: "$roomId",
receiver: "$clients",
message: { $slice: ["$message", -1]
}
}}
])
// result
[{
"_id" : 1,
"receiver" : "rooberduck@mail.com",
"message" : [
{
"time" : ISODate("2019-06-27T04:54:49.528Z"),
"status" : "SEND",
"text" : "Hello!",
"sender" : "sillybilly@mail.com",
"reciever" : "rooberduck@mail.com",
"_id" : ObjectId("5d1449ff6f934a2926c175d3")
}
]
} ... another result]
Okay nice now send a message to the frontend developer again. But hold on you see the design again it got unread message badge... you should count it. Hmmm. You sit down again and thingking..
3rd case: count unread message inside an array of messages object
Do you feel it the syntax of {{{{}}}} already? :lol:.
You already $unwind the clients, should you $unwind again the messages? Yes. It is like working with the stream so you should follow the pattern you create.
Since using $sum in $project requires a lot of $cond you can simplify your query using $group. $group had a lot of accumulator operator that can be useful, for detecting the $last / $first element.
// unwind it again
db.getCollection('chats').aggregate([
{ $match: { clients: "sillybilly@mail.com" } },
{ $unwind: "$clients" },
{ $match: { clients: { $ne: 'sillybilly@mail.com' } } },
{ $unwind: "$message" }, // messages decoupled her
{ $match: "$message.status": 'SEND' }
{ $group: {
_id: '$_id', // we group it by _id
roomId: { $first: '$roomId' }, // accumulator must be used otherwise error will thrown
receiver: { $first: '$clients' },
unread: { $sum: 1 },
message: { $last: '$message.text' },
time: { $last: '$message.time' }
}
}
])
// result
[{
"_id" : ObjectId("5d1449ff6f934a2926c175d3"),
"receiver" : "rooberduck@mail.com",
"unread": 1,
"message" : "Hello!",
"time": ISODate("2019-06-27T04:54:49.528Z")
}... another result]
I think this query isn't performing well, imagine if you had 1000 messages, you will unwind 1000 message, that can affect performance? Comment below if you know the best way 😁
So now you got a beautiful response from your database, the only thing you missing from the design UI is pagination!
4th case : paginate .aggregate() using $facet
The docs about $facet say something like this: "Processes multiple aggregation pipelines within a single stage on the same set of input documents".
That means that we can use aggregation inside $facet like $unwind. But we don't need to unwind again, to do your pagination via $facet you could just use this query :
db.getCollection('chats').aggregate([
{ $match: { clients: "sillybilly@mail.com" } },
{ $unwind: "$clients" },
{ $match: { clients: { $ne: 'sillybilly@mail.com' } } },
{ $unwind: "$message" },
{ $match: "$message.status": 'SEND' }
{ $group: {
_id: '$_id',
roomId: { $first: '$roomId' },
receiver: { $first: '$clients' },
unread: { $sum: 1 },
message: { $last: '$message.text' },
time: { $last: '$message.time' }
}
},
{
$facet: {
metadata: [{ $count: 'total' }, { $addFields: { page: 1 } }],
data: [
{ $skip: 0 },
{ $limit: 15 }
]
}
}
])
// result: now you got a paginated response
[{
"metadata": [ { $count: 'total' }, { page: 1 } ],
"data": [
{
"_id" : ObjectId("5d1449ff6f934a2926c175d3"),
"receiver" : "rooberduck@mail.com",
"unread": 1,
"message" : "Hello!",
"time": ISODate("2019-06-27T04:54:49.528Z")
}
]
}... another result]
That's it you got your beautiful response API, now you come the frontend dev and say, you got it done, and the he/she accept your API response.
See you next post, and had an awesome day :)
Feedback always welcome.
Top comments (1)
your the man.
if there a more intermediate/pro approach you would recommend ?