For our app I'm using the free-tier (for now) on MongoDB-Atlas.
our documents have, among other fields, a start time which is a Datetime object, and a userId int.
export interface ITimer {
id?: string,
_id?: string, // id property assigned by mongo
userId?: number,
projectId?: number,
description?: string,
tags?: number[],
isBillable?: boolean,
isManual?: boolean,
start?: Date,
end?: Date,
createdAt?: Date,
updatedAt?: Date,
createdBy?: number,
updatedBy?: number
};
I'm looking for an index that will match the following query:
let query: FilterQuery<ITimer> = {
start: {$gte: start, $lte: end},
userId: userId,
};
Where start and end parameters are date objects or ISOStrings passed to define a range of days.
Here I invoke the query, sorting results:
let result = await collection.find(query).sort({start: 1}).toArray();
It seems simple enough that the following index would match the above query:
{
key: {
start: 1,
userId: 1,
},
name: 'find_between_dates_by_user',
background: true,
unique: false,
},
But using mongodb-compass to monitor the collection, I see this index is not used.
Moreover, mongodb documentation specifically states that if an index matches a query completely, than no documents will have to be examined, and the results will be based on the indexed information alone.
unfortunately, for every query I run, I see documents ARE examined, meaning my indexes do not match.
Any suggestions? I feel this should be very simple and straightforward, but maybe I'm missing something.
attached is an screenshot from mongodb-compass 'explaining' the query and execution.
Related
In a nodejs backend I have a function where I insert some values on a MongoDB collection.
I'm using this:
const result = await SomeModel.insertMany(someArrayOfData);
This takes a lot of time, like 2 minutes.
I'm inserting like 11.000 documents, each document has this schema:
const someModelSchema = mongoose.Schema({
IDEvento: Number,
descMet: String,
metrica: Number,
local: String,
porcent: Number,
tipoBono: String,
year: String
}, { timestamps: true });
Once is inserted I can see the values like:
Why could be some reasons for taking so much? the array is not a big array of data (the length is 2800), only 2800 documents, and each document are pretty simple, not objects nor long strings, they have very short values.
Also, there's a:
await SomeModel.deleteMany({ year });
And takes a lot of time too, like 1 minute
I'm having a problem with the time of my mongoDB query, from a node backend using mongoose. i have a collection called people that has 10M records, and every record is queried from the backend and inserted from another part of the system that's written in c++ and needs to be very fast.
this is my mongoose schema:
{
_id: {type: String, index: {unique: true}}, // We generate our own _id! Might it be related to the slowness?
age: { type: Number },
id_num: { type: String },
friends: { type: Object }
}
schema.index({'id_num': 1}, { unique: true, collation: { locale: 'en_US', strength: 2 } })
schema.index({'age': 1})
schema.index({'id_num': 'text'});
Friends is an object looking like that: {"Adam": true, "Eve": true... etc.}.
there's no meaning to the value, and we use dictionaries to avoid duplicates fast on C++.
also, we didn't encounter a set/unique-list type of field in mongoDB.
The Problem:
We display people in a table with pagination. the table has abilities of sort, search, and select number of results.
At first, I queried all people and searched, sorted and paged it on the js. but when there are a lot of documents, It's turning problematic (memory problems).
The next thing i did was to try to fit those manipulations (searching, sorting & paging) on my query.
I used mongo's text search- but it not matches a partial word. is there any way to search a partial insensitive string? (I prefer not to use regex, to avoid unexpected problems)
I have to sort before paging, so I tried to use mongo sort. the problem is, that when the user wants to sort by "Friends", we want to return the people sorted by their number of friends (number of entries in the object).
The only way i succeeded pulling it off was using $addFields in aggregation:
{$addFields: {$size: {$ifNull: [{$objectToArray: '$friends'}, [] ]}}}
this addition is taking forever! when sorting by friends, the query takes about 40s for 8M people, and without this part it takes less than a second.
I used limit and skip for pagination. it works ok, but we have to wait until the user requests the second page and make another very long query.
In the end, this is the the interesting code part:
const { sortBy, sortDesc, search, page, itemsPerPage } = req.query
// Search never matches partial string
const match = search ? {$text: {$search: search}} : {}
const sortByInDB = ['age', 'id_num']
let sort = {$sort : {}}
const aggregate = [{$match: match}]
// if sortBy is on a simple type, we just use mongos sort
// else, we sortBy friends, and add a friends_count field.
if(sortByInDB.includes(sortBy)){
sort.$sort[sortBy] = sortDesc === 'true' ? -1 : 1
} else {
sort.$sort[sortBy+'_count'] = sortDesc === 'true' ? -1 : 1
// The problematic part of the query:
aggregate.push({$addFields: {friends_count: {$size: {
$ifNull: [{$objectToArray: '$friends'},[]]
}}}})
}
const numItems = parseInt(itemsPerPage)
const numPage = parseInt(page)
aggregate.push(sort, {$skip: (numPage - 1)*numItems}, {$limit: numItems})
// Takes a long time (when sorting by "friends")
let users = await User.aggregate(aggregate)
I tried indexing all simple fields, but the time is still too much.
The only other solution i could think of, is making mongo calculate a field "friends_count" every time a document is created or updated- but i have no idea how to do it, without slowing our c++ that writes to the DB.
Do you have any creative idea to help me? I'm lost, and I have to shorten the time drastically.
Thank you!
P.S: some useful information- the C++ area is writing the people to the DB in a bulk once in a while. we can sync once in a while and mostly rely on the data to be true. So, if that gives any of you any idea for a performance boost, i'd love to hear it.
Thanks!
So I have documents that follow this schema:
{
_id: String,
globalXP: {
xp: {
type: Number,
default: 0
},
level: {
type: Number,
default: 0
}
},
guilds: [{ _id: String, xp: Number, level: Number }]
}
So basically users have their own global XP and xp based on each guild they are in.
Now I want to make a leaderboard for all the users that have a certain guildID in their document.
What's the most efficient way to fetch all the user documents that have the guild _id in their guilds array and how do I sort them afterwards?
I know it might be messy as hell but bare with me here.
If I've understand well, you only need this line of code:
var find = await model.find({"guilds._id":"your_guild_id"}).sort({"globalXP.level":-1})
This query will return all documentas where guilds array contains the specific _id and sort by player level.
In this way the best level will be displayed first.
Here is an example how the query works. Please check if it work as you expected.
I was wondering if there is way to force a unique collection entry but only if entry is not null.
e
Sample schema:
var UsersSchema = new Schema({
name : {type: String, trim: true, index: true, required: true},
email : {type: String, trim: true, index: true, unique: true}
});
'email' in this case is not required but if 'email' is saved I want to make sure that this entry is unique (on a database level).
Empty entries seem to get the value 'null' so every entry wih no email crashes with the 'unique' option (if there is a different user with no email).
Right now I'm solving it on an application level, but would love to save that db query.
thx
As of MongoDB v1.8+ you can get the desired behavior of ensuring unique values but allowing multiple docs without the field by setting the sparse option to true when defining the index. As in:
email : {type: String, trim: true, index: true, unique: true, sparse: true}
Or in the shell:
db.users.ensureIndex({email: 1}, {unique: true, sparse: true});
Note that a unique, sparse index still does not allow multiple docs with an email field with a value of null, only multiple docs without an email field.
See http://docs.mongodb.org/manual/core/index-sparse/
tl;dr
Yes, it is possible to have multiple documents with a field set to null or not defined, while enforcing unique "actual" values.
requirements:
MongoDB v3.2+.
Knowing your concrete value type(s) in advance (e.g, always a string or object when not null).
If you're not interested in the details, feel free to skip to the implementation section.
longer version
To supplement #Nolan's answer, starting with MongoDB v3.2 you can use a partial unique index with a filter expression.
The partial filter expression has limitations. It can only include the following:
equality expressions (i.e. field: value or using the $eq operator),
$exists: true expression,
$gt, $gte, $lt, $lte expressions,
$type expressions,
$and operator at the top-level only
This means that the trivial expression {"yourField"{$ne: null}} cannot be used.
However, assuming that your field always uses the same type, you can use a $type expression.
{ field: { $type: <BSON type number> | <String alias> } }
MongoDB v3.6 added support for specifying multiple possible types, which can be passed as an array:
{ field: { $type: [ <BSON type1> , <BSON type2>, ... ] } }
which means that it allows the value to be of any of a number of multiple types when not null.
Therefore, if we want to allow the email field in the example below to accept either string or, say, binary data values, an appropriate $type expression would be:
{email: {$type: ["string", "binData"]}}
implementation
mongoose
You can specify it in a mongoose schema:
const UsersSchema = new Schema({
name: {type: String, trim: true, index: true, required: true},
email: {
type: String, trim: true, index: {
unique: true,
partialFilterExpression: {email: {$type: "string"}}
}
}
});
or directly add it to the collection (which uses the native node.js driver):
User.collection.createIndex("email", {
unique: true,
partialFilterExpression: {
"email": {
$type: "string"
}
}
});
native mongodb driver
using collection.createIndex
db.collection('users').createIndex({
"email": 1
}, {
unique: true,
partialFilterExpression: {
"email": {
$type: "string"
}
}
},
function (err, results) {
// ...
}
);
mongodb shell
using db.collection.createIndex:
db.users.createIndex({
"email": 1
}, {
unique: true,
partialFilterExpression: {
"email": {$type: "string"}
}
})
This will allow inserting multiple records with a null email, or without an email field at all, but not with the same email string.
Just a quick update to those researching this topic.
The selected answer will work, but you might want to consider using partial indexes instead.
Changed in version 3.2: Starting in MongoDB 3.2, MongoDB provides the
option to create partial indexes. Partial indexes offer a superset of
the functionality of sparse indexes. If you are using MongoDB 3.2 or
later, partial indexes should be preferred over sparse indexes.
More doco on partial indexes: https://docs.mongodb.com/manual/core/index-partial/
Actually, only first document where "email" as field does not exist will get save successfully. Subsequent saves where "email" is not present will fail while giving error ( see code snippet below). For the reason look at MongoDB official documentation with respect to Unique Indexes and Missing Keys here at http://www.mongodb.org/display/DOCS/Indexes#Indexes-UniqueIndexes.
// NOTE: Code to executed in mongo console.
db.things.ensureIndex({firstname: 1}, {unique: true});
db.things.save({lastname: "Smith"});
// Next operation will fail because of the unique index on firstname.
db.things.save({lastname: "Jones"});
By definition unique index can only allow one value to be stored only once. If you consider null as one such value it can only be inserted once! You are correct in your approach by ensuring and validating it at application level. That is how it can be done.
You may also like to read this http://www.mongodb.org/display/DOCS/Querying+and+nulls
I was wondering if there is way to force a unique collection entry but only if entry is not null.
e
Sample schema:
var UsersSchema = new Schema({
name : {type: String, trim: true, index: true, required: true},
email : {type: String, trim: true, index: true, unique: true}
});
'email' in this case is not required but if 'email' is saved I want to make sure that this entry is unique (on a database level).
Empty entries seem to get the value 'null' so every entry wih no email crashes with the 'unique' option (if there is a different user with no email).
Right now I'm solving it on an application level, but would love to save that db query.
thx
As of MongoDB v1.8+ you can get the desired behavior of ensuring unique values but allowing multiple docs without the field by setting the sparse option to true when defining the index. As in:
email : {type: String, trim: true, index: true, unique: true, sparse: true}
Or in the shell:
db.users.ensureIndex({email: 1}, {unique: true, sparse: true});
Note that a unique, sparse index still does not allow multiple docs with an email field with a value of null, only multiple docs without an email field.
See http://docs.mongodb.org/manual/core/index-sparse/
tl;dr
Yes, it is possible to have multiple documents with a field set to null or not defined, while enforcing unique "actual" values.
requirements:
MongoDB v3.2+.
Knowing your concrete value type(s) in advance (e.g, always a string or object when not null).
If you're not interested in the details, feel free to skip to the implementation section.
longer version
To supplement #Nolan's answer, starting with MongoDB v3.2 you can use a partial unique index with a filter expression.
The partial filter expression has limitations. It can only include the following:
equality expressions (i.e. field: value or using the $eq operator),
$exists: true expression,
$gt, $gte, $lt, $lte expressions,
$type expressions,
$and operator at the top-level only
This means that the trivial expression {"yourField"{$ne: null}} cannot be used.
However, assuming that your field always uses the same type, you can use a $type expression.
{ field: { $type: <BSON type number> | <String alias> } }
MongoDB v3.6 added support for specifying multiple possible types, which can be passed as an array:
{ field: { $type: [ <BSON type1> , <BSON type2>, ... ] } }
which means that it allows the value to be of any of a number of multiple types when not null.
Therefore, if we want to allow the email field in the example below to accept either string or, say, binary data values, an appropriate $type expression would be:
{email: {$type: ["string", "binData"]}}
implementation
mongoose
You can specify it in a mongoose schema:
const UsersSchema = new Schema({
name: {type: String, trim: true, index: true, required: true},
email: {
type: String, trim: true, index: {
unique: true,
partialFilterExpression: {email: {$type: "string"}}
}
}
});
or directly add it to the collection (which uses the native node.js driver):
User.collection.createIndex("email", {
unique: true,
partialFilterExpression: {
"email": {
$type: "string"
}
}
});
native mongodb driver
using collection.createIndex
db.collection('users').createIndex({
"email": 1
}, {
unique: true,
partialFilterExpression: {
"email": {
$type: "string"
}
}
},
function (err, results) {
// ...
}
);
mongodb shell
using db.collection.createIndex:
db.users.createIndex({
"email": 1
}, {
unique: true,
partialFilterExpression: {
"email": {$type: "string"}
}
})
This will allow inserting multiple records with a null email, or without an email field at all, but not with the same email string.
Just a quick update to those researching this topic.
The selected answer will work, but you might want to consider using partial indexes instead.
Changed in version 3.2: Starting in MongoDB 3.2, MongoDB provides the
option to create partial indexes. Partial indexes offer a superset of
the functionality of sparse indexes. If you are using MongoDB 3.2 or
later, partial indexes should be preferred over sparse indexes.
More doco on partial indexes: https://docs.mongodb.com/manual/core/index-partial/
Actually, only first document where "email" as field does not exist will get save successfully. Subsequent saves where "email" is not present will fail while giving error ( see code snippet below). For the reason look at MongoDB official documentation with respect to Unique Indexes and Missing Keys here at http://www.mongodb.org/display/DOCS/Indexes#Indexes-UniqueIndexes.
// NOTE: Code to executed in mongo console.
db.things.ensureIndex({firstname: 1}, {unique: true});
db.things.save({lastname: "Smith"});
// Next operation will fail because of the unique index on firstname.
db.things.save({lastname: "Jones"});
By definition unique index can only allow one value to be stored only once. If you consider null as one such value it can only be inserted once! You are correct in your approach by ensuring and validating it at application level. That is how it can be done.
You may also like to read this http://www.mongodb.org/display/DOCS/Querying+and+nulls