From my website client I am sending an API request to the backend Node.js server and finding a specific document by ID like so:
var ObjectID = require('mongodb').ObjectID;
db.collection('users').find({"_id": new ObjectID(req.body._id)})
Where req.body._id equals the entire ID string, such as '5d0381ad681a2a3aa1dc5872'
However I would prefer to send only the INC (ever incrementing value) portion of the string as the argument: 'c5872'
How should I find a specific document based on just the INC value? (I'm assuming the INC is unique)
Any help is greatly appreciated.
You can temporarily transform your _id using in a string to be able to use a regular expression :
db.users.aggregate([
{
$addFields: { id: { $toString: '$_id' } }
},
{
$match: { id: /c5872$/ }
}
])
A cleaner solution is to create the field directly with a substring to avoid using a regular expression :
db.users.aggregate([
{
$addFields: { id: { $substr: [{ $toString: '$_id' }, 19, 24] } }
},
{
$match: { id: 'c5872' }
}
])
https://docs.mongodb.com/manual/reference/operator/aggregation/addFields/
https://docs.mongodb.com/manual/reference/operator/aggregation/substr/
You could create an additional ID field and a unique index to ensure that indexed fields do not store duplicate values, but note that for a five hex string, we have "1,048,576" possible combinations (16 ^ 5 = 1048576).
Note: Using a regular expression could lead to a collection scan.
A regular expression is a "prefix expression" if it starts with a
caret (^) or a left anchor (\A), followed by a string of simple
symbols. For example, the regex /^abc.*/ will be optimized by matching
only against the values from the index that start with abc.
Regular expression and index use
Related
What I was hoping to do was store an array of objects using RedisJSON very simply and then query that array.
I have something similar to this:
const data = [
{
_id: '63e7d1d85ad7e2f69df8ed6e',
artist: {
genre: 'rock',
},
},
{
_id: '63e7d1d85ad7e2f69df8ed6f',
artist: {
genre: 'metal',
},
},
{
_id: '63e7d1d85ad7e2f69df8ed6g',
artist: {
genre: 'rock',
},
},
]
then I can easily store and retrieve this:
await redisClient.json.set(cacheKey, '$', data)
await redisClient.json.get(cacheKey)
works great. but now I want to also query this data, I've tried creating an index as below:
await redisClient.ft.create(
`idx:gigs`,
{
'$.[0].artist.genre': {
type: SchemaFieldTypes.TEXT,
AS: 'genre',
},
},
{
ON: 'JSON',
PREFIX: 'GIGS',
}
)
and when I try and search this index what I expect is it to return the 2 documents with the correct search filter, but instead it always returns the entire array:
const searchResult = await redisClient.ft.search(`idx:gigs`, '#genre:(rock)')
produces:
{
total: 1,
documents: [
{ id: 'cacheKey', value: [Array] }
]
}
I can't quite work out at which level I'm getting this wrong, but any help would be greatly appreciated.
Is it possible to store an array of objects and then search the nested objects for nested values with RedisJSON?
The Search capability in Redis stack treats each key containing a JSON document as a separate search index entry. I think what you are doing is perhaps storing your whole array of documents in a single Redis key, which means any matches will return the document at that key which contains all of your data.
I would suggest that you store each object in your data array as its own key in Redis. Make sure that these will be indexed by using the GIGS prefix in the key name, for example GIGS:63e7d1d85ad7e2f69df8ed6e and GIGS:63e7d1d85ad7e2f69df8ed6f.
You'd want to change your index definition to account for each document being an object too so it would look something like this:
await redisClient.ft.create(
`idx:gigs`,
{
'$.artist.genre': {
type: SchemaFieldTypes.TEXT,
AS: 'genre',
},
},
{
ON: 'JSON',
PREFIX: 'GIGS:',
}
)
Note I also updated your PREFIX to be GIGS: not GIGS - this isn't strictly necessary, but does stop your index from accidentally looking at other keys in Redis whose name begins GIGS<whatever other characters>.
I have 2 collections:
Office -
{
_id: ObjectId(someOfficeId),
name: "some name",
..other fields
}
Documents -
{
_id: ObjectId(SomeId),
name: "Some document name",
officeId: ObjectId(someOfficeId),
...etc
}
I need to get list of offices sorted by count of documetns that refer to office. Also should be realized pagination.
I tryied to do this by aggregation and using $lookup
const aggregation = [
{
$lookup: {
from: 'documents',
let: {
id: '$id'
},
pipeline: [
{
$match: {
$expr: {
$eq: ['$officeId', '$id']
},
// sent_at: {
// $gte: start,
// $lt: end,
// },
}
}
],
as: 'documents'
},
},
{ $sortByCount: "$documents" },
{ $skip: (page - 1) * limit },
{ $limit: limit },
];
But this doesn't work for me
Any Ideas how to realize this?
p.s. I need to show offices with 0 documents, so get offices by documets - doesn't work for me
Query
you can use lookup to join on that field, and pipeline to group so you count the documents of each office (instead of putting the documents into an array, because you only case for the count)
$set is to get that count at top level field
sort using the noffices field
you can use the skip/limit way for pagination, but if your collection is very big it will be slow see this. Alternative you can do the pagination using the _id natural order, or retrieve more document in each query and have them in memory (instead of retriving just 1 page's documents)
Test code here
offices.aggregate(
[{"$lookup":
{"from":"documents",
"localField":"_id",
"foreignField":"officeId",
"pipeline":[{"$group":{"_id":null, "count":{"$sum":1}}}],
"as":"noffices"}},
{"$set":
{"noffices":
{"$cond":
[{"$eq":["$noffices", []]}, 0,
{"$arrayElemAt":["$noffices.count", 0]}]}}},
{"$sort":{"noffices":-1}}])
As the other answer pointed out you forgot the _ of id, but you don't need the let or match inside the pipeline with $expr, with the above lookup. Also $sortByCount doesn't count the member of an array, you would need $size (sort by count is just group and count its not for arrays). But you dont need $size also you can count them in the pipeline, like above.
Edit
Query
you can add in the pipeline what you need or just remove it
this keeps all documents, and counts the array size
and then sorts
Test code here
offices.aggregate(
[{"$lookup":
{"from":"documents",
"localField":"_id",
"foreignField":"officeId",
"pipeline":[],
"as":"alldocuments"}},
{"$set":{"ndocuments":{"$size":"$alldocuments"}}},
{"$sort":{"ndocuments":-1}}])
There are two errors in your lookup
While passing the variable in with $let. You forgot the _ of the $_id local field
let: {
id: '$id'
},
In the $exp, since you are using a variable id and not a field of the
Documents collection, you should use $$ to make reference to the variable.
$expr: {
$eq: ['$officeId', '$$id']
},
I have documents in a MongoDB as below -
[
{
"_id": "17tegruebfjt73efdci342132",
"name": "Test User1",
"obj": "health=8,type=warrior",
},
{
"_id": "wefewfefh32j3h42kvci342132",
"name": "Test User2",
"obj": "health=6,type=magician",
}
.
.
]
I want to run a query say health>6 and it should return the "Test User1" entry. The obj key is indexed as a text field so I can do {$text:{$search:"health=8"}} to get an exact match but I am trying to incorporate mathematical operators into the search.
I am aware of the $gt and $lt operators, however, it cannot be used in this case as health is not a key of the document. The easiest way out is to make health a key of the document for sure, but I cannot change the document structure due to certain constraints.
Is there anyway this can be achieved? I am aware that mongo supports running javascript code, not sure if that can help in this case.
I don't think it's possible in $text search index, but you can transform your object conditions to an array of objects using an aggregation query,
$split to split obj by "," and it will return an array
$map to iterate loop of the above split result array
$split to split current condition by "=" and it will return an array
$let to declare the variable cond to store the result of the above split result
$first to return the first element from the above split result in k as a key of condition
$last to return the last element from the above split result in v as a value of the condition
now we have ready an array of objects of string conditions:
"objTransform": [
{ "k": "health", "v": "9" },
{ "k": "type", "v": "warrior" }
]
$match condition for key and value to match in the same object using $elemMatch
$unset to remove transform array objTransform, because it's not needed
db.collection.aggregate([
{
$addFields: {
objTransform: {
$map: {
input: { $split: ["$obj", ","] },
in: {
$let: {
vars: {
cond: { $split: ["$$this", "="] }
},
in: {
k: { $first: "$$cond" },
v: { $last: "$$cond" }
}
}
}
}
}
}
},
{
$match: {
objTransform: {
$elemMatch: {
k: "health",
v: { $gt: "8" }
}
}
}
},
{ $unset: "objTransform" }
])
Playground
The second upgraded version of the above aggregation query to do less operation in condition transformation if it's possible to manage in your client-side,
$split to split obj by "," and it will return an array
$map to iterate loop of the above split result array
$split to split current condition by "=" and it will return an array
now we have ready a nested array of string conditions:
"objTransform": [
["type", "warrior"],
["health", "9"]
]
$match condition for key and value to match in the array element using $elemMatch, "0" to match the first position of the array and "1" to match the second position of the array
$unset to remove transform array objTransform, because it's not needed
db.collection.aggregate([
{
$addFields: {
objTransform: {
$map: {
input: { $split: ["$obj", ","] },
in: { $split: ["$$this", "="] }
}
}
}
},
{
$match: {
objTransform: {
$elemMatch: {
"0": "health",
"1": { $gt: "8" }
}
}
}
},
{ $unset: "objTransform" }
])
Playground
Using JavaScript is one way of doing what you want. Below is a find that uses the index on obj by finding documents that have health= text followed by an integer (if you want, you can anchor that with ^ in the regex).
It then uses a JavaScript function to parse out the actual integer after substringing your way past the health= part, doing a parseInt to get the int, and then the comparison operator/value you mentioned in the question.
db.collection.find({
// use the index on obj to potentially speed up the query
"obj":/health=\d+/,
// now apply a function to narrow down and do the math
$where: function() {
var i = this.obj.indexOf("health=") + 7;
var s = this.obj.substring(i);
var m = s.match(/\d+/);
if (m)
return parseInt(m[0]) > 6;
return false;
}
})
You can of course tweak it to your heart's content to use other operators.
NOTE: I'm using the JavaScript regex capability, which may not be supported by MongoDB. I used Mongo-Shell r4.2.6 where it is supported. If that's the case, in the JavaScript, you will have to extract the integer out a different way.
I provided a Mongo Playground to try it out in if you want to tweak it, but you'll get
Invalid query:
Line 3: Javascript regex are not supported. Use "$regex" instead
until you change it to account for the regex issue noted above. Still, if you're using the latest and greatest, this shouldn't be a limitation.
Performance
Disclaimer: This analysis is not rigorous.
I ran two queries against a small collection (a bigger one could possibly have resulted in different results) with Explain Plan in MongoDB Compass. The first query is the one above; the second is the same query, but with the obj filter removed.
and
As you can see the plans are different. The number of documents examined is fewer for the first query, and the first query uses the index.
The execution times are meaningless because the collection is small. The results do seem to square with the documentation, but the documentation seems a little at odds with itself. Here are two excerpts
Use the $where operator to pass either a string containing a JavaScript expression or a full JavaScript function to the query system. The $where provides greater flexibility, but requires that the database processes the JavaScript expression or function for each document in the collection.
and
Using normal non-$where query statements provides the following performance advantages:
MongoDB will evaluate non-$where components of query before $where statements. If the non-$where statements match no documents, MongoDB will not perform any query evaluation using $where.
The non-$where query statements may use an index.
I'm not totally sure what to make of this, TBH. As a general solution it might be useful because it seems you could generate queries that can handle all of your operators.
My document schema is as follows:
const CollectionSchema = mongoose.Schema({
ImageCategory:{type:String,required:true},
imgDetails: [
{
_id: false,
imageUrl:{type:String},
imageName:{type:String},
imageMimeType:{type:String},
}
],
Date: {
type: String,
default: `${year}-${month}-${day}`,
},
},{timestamps: true,})
So in the database for example one document has multiple images with a single image category. What I am trying to do is I want to delete an object from imgDetails array.
Let me explain my question more precisely: imgDetails is an array
Explanation: I want to loop in imgDetails and then find (where imgageUrl === req.body.imageUrl) if its match delete that whole object which have that req.body.imageUrl and then update the document.
Please guide me on how to write such a query. Regards
Demo - https://mongoplayground.net/p/qpl7lXbKAZE
Use $pull
The $pull operator removes from an existing array all instances of a value or values that match a specified condition.
db.collection.update(
{},
{ $pull: { "imgDetails": { imageUrl: "xyz" } } }
)
I am using Loopback node js framework with MongoDB.
Here I am checking if a field contains a given string or not
user.find({
where: {
or: [{
mobile: {
"regexp": '/' + data.search + '/i'
},
contacts:{
"regexp": '/' + data.search + '/i'
}}]
}
}, function(err, mobileResult) {
if (err) {
callback(err, null);
} else {
.......
.......
}
});
this one works with string type field contacts but not with number field mobile.
I tried answers from these post but it didn't worked for me.
I think you can use this solution:
Using aggregate for querying your data:
MongoDB aggregation on Loopback
Using this awesome way to search on a number in MongoDB: (Second Answer)
MongoDB Regex Search on Integer Value
I also agree with #Stennie which commented:
Regular expressions match patterns in strings. If you need to do
pattern matching I'd suggest storing your mobile values as strings
instead of numbers.