Example:
> db.stuff.save({"foo":"bar"});
> db.stuff.find({"foo":"bar"}).count();
1
> db.stuff.find({"foo":"BAR"}).count();
0
You could use a regex.
In your example that would be:
db.stuff.find( { foo: /^bar$/i } );
I must say, though, maybe you could just downcase (or upcase) the value on the way in rather than incurring the extra cost every time you find it. Obviously this wont work for people's names and such, but maybe use-cases like tags.
UPDATE:
The original answer is now obsolete. Mongodb now supports advanced full text searching, with many features.
ORIGINAL ANSWER:
It should be noted that searching with regex's case insensitive /i means that mongodb cannot search by index, so queries against large datasets can take a long time.
Even with small datasets, it's not very efficient. You take a far bigger cpu hit than your query warrants, which could become an issue if you are trying to achieve scale.
As an alternative, you can store an uppercase copy and search against that. For instance, I have a User table that has a username which is mixed case, but the id is an uppercase copy of the username. This ensures case-sensitive duplication is impossible (having both "Foo" and "foo" will not be allowed), and I can search by id = username.toUpperCase() to get a case-insensitive search for username.
If your field is large, such as a message body, duplicating data is probably not a good option. I believe using an extraneous indexer like Apache Lucene is the best option in that case.
Starting with MongoDB 3.4, the recommended way to perform fast case-insensitive searches is to use a Case Insensitive Index.
I personally emailed one of the founders to please get this working, and he made it happen! It was an issue on JIRA since 2009, and many have requested the feature. Here's how it works:
A case-insensitive index is made by specifying a collation with a strength of either 1 or 2. You can create a case-insensitive index like this:
db.cities.createIndex(
{ city: 1 },
{
collation: {
locale: 'en',
strength: 2
}
}
);
You can also specify a default collation per collection when you create them:
db.createCollection('cities', { collation: { locale: 'en', strength: 2 } } );
In either case, in order to use the case-insensitive index, you need to specify the same collation in the find operation that was used when creating the index or the collection:
db.cities.find(
{ city: 'new york' }
).collation(
{ locale: 'en', strength: 2 }
);
This will return "New York", "new york", "New york" etc.
Other notes
The answers suggesting to use full-text search are wrong in this case (and potentially dangerous). The question was about making a case-insensitive query, e.g. username: 'bill' matching BILL or Bill, not a full-text search query, which would also match stemmed words of bill, such as Bills, billed etc.
The answers suggesting to use regular expressions are slow, because even with indexes, the documentation states:
"Case insensitive regular expression queries generally cannot use indexes effectively. The $regex implementation is not collation-aware and is unable to utilize case-insensitive indexes."
$regex answers also run the risk of user input injection.
If you need to create the regexp from a variable, this is a much better way to do it: https://stackoverflow.com/a/10728069/309514
You can then do something like:
var string = "SomeStringToFind";
var regex = new RegExp(["^", string, "$"].join(""), "i");
// Creates a regex of: /^SomeStringToFind$/i
db.stuff.find( { foo: regex } );
This has the benefit be being more programmatic or you can get a performance boost by compiling it ahead of time if you're reusing it a lot.
Keep in mind that the previous example:
db.stuff.find( { foo: /bar/i } );
will cause every entries containing bar to match the query ( bar1, barxyz, openbar ), it could be very dangerous for a username search on a auth function ...
You may need to make it match only the search term by using the appropriate regexp syntax as:
db.stuff.find( { foo: /^bar$/i } );
See http://www.regular-expressions.info/ for syntax help on regular expressions
db.company_profile.find({ "companyName" : { "$regex" : "Nilesh" , "$options" : "i"}});
db.zipcodes.find({city : "NEW YORK"}); // Case-sensitive
db.zipcodes.find({city : /NEW york/i}); // Note the 'i' flag for case-insensitivity
TL;DR
Correct way to do this in mongo
Do not Use RegExp
Go natural And use mongodb's inbuilt indexing , search
Step 1 :
db.articles.insert(
[
{ _id: 1, subject: "coffee", author: "xyz", views: 50 },
{ _id: 2, subject: "Coffee Shopping", author: "efg", views: 5 },
{ _id: 3, subject: "Baking a cake", author: "abc", views: 90 },
{ _id: 4, subject: "baking", author: "xyz", views: 100 },
{ _id: 5, subject: "Café Con Leche", author: "abc", views: 200 },
{ _id: 6, subject: "Сырники", author: "jkl", views: 80 },
{ _id: 7, subject: "coffee and cream", author: "efg", views: 10 },
{ _id: 8, subject: "Cafe con Leche", author: "xyz", views: 10 }
]
)
Step 2 :
Need to create index on whichever TEXT field you want to search , without indexing query will be extremely slow
db.articles.createIndex( { subject: "text" } )
step 3 :
db.articles.find( { $text: { $search: "coffee",$caseSensitive :true } } ) //FOR SENSITIVITY
db.articles.find( { $text: { $search: "coffee",$caseSensitive :false } } ) //FOR INSENSITIVITY
One very important thing to keep in mind when using a Regex based query - When you are doing this for a login system, escape every single character you are searching for, and don't forget the ^ and $ operators. Lodash has a nice function for this, should you be using it already:
db.stuff.find({$regex: new RegExp(_.escapeRegExp(bar), $options: 'i'})
Why? Imagine a user entering .* as his username. That would match all usernames, enabling a login by just guessing any user's password.
Suppose you want to search "column" in "Table" and you want case insensitive search. The best and efficient way is:
//create empty JSON Object
mycolumn = {};
//check if column has valid value
if(column) {
mycolumn.column = {$regex: new RegExp(column), $options: "i"};
}
Table.find(mycolumn);
It just adds your search value as RegEx and searches in with insensitive criteria set with "i" as option.
Mongo (current version 2.0.0) doesn't allow case-insensitive searches against indexed fields - see their documentation. For non-indexed fields, the regexes listed in the other answers should be fine.
For searching a variable and escaping it:
const escapeStringRegexp = require('escape-string-regexp')
const name = 'foo'
db.stuff.find({name: new RegExp('^' + escapeStringRegexp(name) + '$', 'i')})
Escaping the variable protects the query against attacks with '.*' or other regex.
escape-string-regexp
The best method is in your language of choice, when creating a model wrapper for your objects, have your save() method iterate through a set of fields that you will be searching on that are also indexed; those set of fields should have lowercase counterparts that are then used for searching.
Every time the object is saved again, the lowercase properties are then checked and updated with any changes to the main properties. This will make it so you can search efficiently, but hide the extra work needed to update the lc fields each time.
The lower case fields could be a key:value object store or just the field name with a prefixed lc_. I use the second one to simplify querying (deep object querying can be confusing at times).
Note: you want to index the lc_ fields, not the main fields they are based off of.
Using Mongoose this worked for me:
var find = function(username, next){
User.find({'username': {$regex: new RegExp('^' + username, 'i')}}, function(err, res){
if(err) throw err;
next(null, res);
});
}
If you're using MongoDB Compass:
Go to the collection, in the filter type -> {Fieldname: /string/i}
For Node.js using Mongoose:
Model.find({FieldName: {$regex: "stringToSearch", $options: "i"}})
The aggregation framework was introduced in mongodb 2.2 . You can use the string operator "$strcasecmp" to make a case-insensitive comparison between strings. It's more recommended and easier than using regex.
Here's the official document on the aggregation command operator: https://docs.mongodb.com/manual/reference/operator/aggregation/strcasecmp/#exp._S_strcasecmp .
You can use Case Insensitive Indexes:
The following example creates a collection with no default collation, then adds an index on the name field with a case insensitive collation. International Components for Unicode
/* strength: CollationStrength.Secondary
* Secondary level of comparison. Collation performs comparisons up to secondary * differences, such as diacritics. That is, collation performs comparisons of
* base characters (primary differences) and diacritics (secondary differences). * Differences between base characters takes precedence over secondary
* differences.
*/
db.users.createIndex( { name: 1 }, collation: { locale: 'tr', strength: 2 } } )
To use the index, queries must specify the same collation.
db.users.insert( [ { name: "Oğuz" },
{ name: "oğuz" },
{ name: "OĞUZ" } ] )
// does not use index, finds one result
db.users.find( { name: "oğuz" } )
// uses the index, finds three results
db.users.find( { name: "oğuz" } ).collation( { locale: 'tr', strength: 2 } )
// does not use the index, finds three results (different strength)
db.users.find( { name: "oğuz" } ).collation( { locale: 'tr', strength: 1 } )
or you can create a collection with default collation:
db.createCollection("users", { collation: { locale: 'tr', strength: 2 } } )
db.users.createIndex( { name : 1 } ) // inherits the default collation
I'm surprised nobody has warned about the risk of regex injection by using /^bar$/i if bar is a password or an account id search. (I.e. bar => .*#myhackeddomain.com e.g., so here comes my bet: use \Q \E regex special chars! provided in PERL
db.stuff.find( { foo: /^\Qbar\E$/i } );
You should escape bar variable \ chars with \\ to avoid \E exploit again when e.g. bar = '\E.*#myhackeddomain.com\Q'
Another option is to use a regex escape char strategy like the one described here Javascript equivalent of Perl's \Q ... \E or quotemeta()
Use RegExp,
In case if any other options do not work for you, RegExp is a good option. It makes the string case insensitive.
var username = new RegExp("^" + "John" + "$", "i");;
use username in queries, and then its done.
I hope it will work for you too. All the Best.
If there are some special characters in the query, regex simple will not work. You will need to escape those special characters.
The following helper function can help without installing any third-party library:
const escapeSpecialChars = (str) => {
return str.replace(/[-[\]{}()*+?.,\\^$|#\s]/g, "\\$&");
}
And your query will be like this:
db.collection.find({ field: { $regex: escapeSpecialChars(query), $options: "i" }})
Hope it will help!
Using a filter works for me in C#.
string s = "searchTerm";
var filter = Builders<Model>.Filter.Where(p => p.Title.ToLower().Contains(s.ToLower()));
var listSorted = collection.Find(filter).ToList();
var list = collection.Find(filter).ToList();
It may even use the index because I believe the methods are called after the return happens but I haven't tested this out yet.
This also avoids a problem of
var filter = Builders<Model>.Filter.Eq(p => p.Title.ToLower(), s.ToLower());
that mongodb will think p.Title.ToLower() is a property and won't map properly.
I had faced a similar issue and this is what worked for me:
const flavorExists = await Flavors.findOne({
'flavor.name': { $regex: flavorName, $options: 'i' },
});
Yes it is possible
You can use the $expr like that:
$expr: {
$eq: [
{ $toLower: '$STRUNG_KEY' },
{ $toLower: 'VALUE' }
]
}
Please do not use the regex because it may make a lot of problems especially if you use a string coming from the end user.
I've created a simple Func for the case insensitive regex, which I use in my filter.
private Func<string, BsonRegularExpression> CaseInsensitiveCompare = (field) =>
BsonRegularExpression.Create(new Regex(field, RegexOptions.IgnoreCase));
Then you simply filter on a field as follows.
db.stuff.find({"foo": CaseInsensitiveCompare("bar")}).count();
These have been tested for string searches
{'_id': /.*CM.*/} ||find _id where _id contains ->CM
{'_id': /^CM/} ||find _id where _id starts ->CM
{'_id': /CM$/} ||find _id where _id ends ->CM
{'_id': /.*UcM075237.*/i} ||find _id where _id contains ->UcM075237, ignore upper/lower case
{'_id': /^UcM075237/i} ||find _id where _id starts ->UcM075237, ignore upper/lower case
{'_id': /UcM075237$/i} ||find _id where _id ends ->UcM075237, ignore upper/lower case
For any one using Golang and wishes to have case sensitive full text search with mongodb and the mgo godoc globalsign library.
collation := &mgo.Collation{
Locale: "en",
Strength: 2,
}
err := collection.Find(query).Collation(collation)
As you can see in mongo docs - since version 3.2 $text index is case-insensitive by default: https://docs.mongodb.com/manual/core/index-text/#text-index-case-insensitivity
Create a text index and use $text operator in your query.
I have this Mongoose schema:
var postSchema = mongoose.Schema({
postId: {
type: Number,
unique: true
},
upvotes: [
{
type: Number,
unique: true
}
]
});
what the best query to use to get the length of the upvotes array? I don't believe I need to use aggregation because I only want to query for one model, just need the length of the upvotes array for a given model.
Really struggling to find this info online - everything I search for mentions the aggregation methodology which I don't believe I need.
Also, as a side note, the unique schema property of the upvotes array doesn't work, perhaps I am doing that wrong.
find results can only include content from the docs themselves1, while aggregate can project new values that are derived from the doc's content (like an array's length). That's why you need to use aggregate for this, even though you're getting just a single doc.
Post.aggregate([{$match: {postId: 5}}, {$project: {upvotes: {$size: '$upvotes'}}}])
1Single exception is the $meta projection operator to project a $text query result's score.
I'm not normally a fan of caching values, but it might be an option (and after finding this stackoverflow answer is what I'm going to do for my use case) to calculate the length of the field when the record is updated in the pre('validate') hook. For example:
var schema = new mongoose.Schema({
name: String,
upvoteCount: Number,
upvotes: [{}]
});
schema.pre('validate', function (next) {
this.upvoteCount = this.upvotes.length
next();
});
Just note that you need to do your updates the mongoose way by loading the object using find and then saving changes using object.save() - don't use findOneAndUpdate
postSchema.virtual('upvoteCount').get(function () {
return this.upvotes.length
});
let doc = await Post.findById('foobar123')
doc.upvoteCount // length of upvotes
My suggestion would be to pull the entire upvotes fields data and use .length property of returned array in node.js code
//logic only, not a functional code
post.find( filterexpression, {upvote: 1}, function(err, res){
console.log(res.upvotes.length);
});
EDIT:
Other way of doing would be stored Javascript. You can query the
upvote and count the same in mongodb side stored Javascript using
.length
Here is my Mongoose Schema:
var SchemaA = new Schema({
field1: String,
.......
fieldB : { type: Schema.Types.ObjectId, ref: 'SchemaB' }
});
var SchemaB = new Schema({
field1: String,
.......
fieldC : { type: Schema.Types.ObjectId, ref: 'SchemaC' }
});
var SchemaC = new Schema({
field1: String,
.......
.......
.......
});
While i access schemaA using find query, i want to have fields/property
of SchemaA along with SchemaB and SchemaC in the same way as we apply join operation in SQL database.
This is my approach:
SchemaA.find({})
.populate('fieldB')
.exec(function (err, result){
SchemaB.populate(result.fieldC,{path:'fieldB'},function(err, result){
.............................
});
});
The above code is working perfectly, but the problem is:
I want to have information/properties/fields of SchemaC through SchemaA, and i don't want to populate fields/properties of SchemaB.
The reason for not wanting to get the properties of SchemaB is, extra population will slows the query unnecessary.
Long story short:
I want to populate SchemaC through SchemaA without populating SchemaB.
Can you please suggest any way/approach?
As an avid mongodb fan, I suggest you use a relational database for highly relational data - that's what it's built for. You are losing all the benefits of mongodb when you have to perform 3+ queries to get a single object.
Buuuuuut, I know that comment will fall on deaf ears. Your best bet is to be as conscious as you can about performance. Your first step is to limit the fields to the minimum required. This is just good practice even with basic queries and any database engine - only get the fields you need (eg. SELECT * FROM === bad... just stop doing it!). You can also try doing lean queries to help save a lot of post-processing work mongoose does with the data. I didn't test this, but it should work...
SchemaA.find({}, 'field1 fieldB', { lean: true })
.populate({
name: 'fieldB',
select: 'fieldC',
options: { lean: true }
}).exec(function (err, result) {
// not sure how you are populating "result" in your example, as it should be an array,
// but you said your code works... so I'll let you figure out what goes here.
});
Also, a very "mongo" way of doing what you want is to save a reference in SchemaC back to SchemaA. When I say "mongo" way of doing it, you have to break away from your years of thinking about relational data queries. Do whatever it takes to perform fewer queries on the database, even if it requires two-way references and/or data duplication.
For example, if I had a Book schema and Author schema, I would likely save the authors first and last name in the Books collection, along with an _id reference to the full profile in the Authors collection. That way I can load my Books in a single query, still display the author's name, and then generate a hyperlink to the author's profile: /author/{_id}. This is known as "data denormalization", and it has been known to give people heartburn. I try and use it on data that doesn't change very often - like people's names. In the occasion that a name does change, it's trivial to write a function to update all the names in multiple places.
SchemaA.find({})
.populate({
path: "fieldB",
populate:{path:"fieldC"}
}).exec(function (err, result) {
//this is how you can get all key value pair of SchemaA, SchemaB and SchemaC
//example: result.fieldB.fieldC._id(key of SchemaC)
});
why not add a ref to SchemaC on SchemaA? there will be no way to bridge to SchemaC from SchemaA if there is no SchemaB the way you currently have it unless you populate SchemaB with no other data than a ref to SchemaC
As explained in the docs under Field Selection, you can restrict what fields are returned.
.populate('fieldB') becomes populate('fieldB', 'fieldC -_id'). The -_id is required to omit the _id field just like when using select().
I think this is not possible.Because,when a document in A referring a document in B and that document is referring another document in C, how can document in A know which document to refer from C without any help from B.