ℹ️ You can test the queries online using tools such as MongoDB Playground or offline tool MongoDB Compass. To get a sample JSON data, please visit this link.
Description:
Users which have income lower than $5 USD and have a car of brand BMW or Mercedes-Benz.
Code:
Check here
db.collection.find({
$and: [
{ car: { $in: ["BMW", "Mercedes-Benz"] } }, // Query for users who have cars of brand BMW or Mercedes-Benz
{ income: { $lt: "5" } }, // Query for users with income less than $5 USD
],
});Explanation:
The query uses the $and operator to combine two conditions. The first condition searches for documents that have a car field that matches either "BMW" or "Mercedes-Benz" using the $in operator. The second condition searches for documents that have an income field that is less than "5" using the $lt operator.
When the two conditions are combined using $and, the resulting query returns all documents that satisfy both conditions. In this case, the query will return documents that represent users who have an income lower than $5 USD and have a car of brand BMW or Mercedes-Benz.
Description:
Male Users which have phone price greater than 10,000.
Code:
Check here
db.collection.find({
$and: [
{ gender: "Male" }, // Query for users with gender equal to "Male"
{ phone_price: { $gt: "10000" } }, // Query for users with phone_price greater than "10000"
],
});Explanation:
The query uses the $and operator to combine two conditions. The first condition searches for documents that have a gender field that matches "Male". The second condition searches for documents that have a phone_price field that is greater than "10000" using the $gt operator.
When the two conditions are combined using $and, the resulting query returns all documents that satisfy both conditions. In this case, the query will return documents that represent Male users with phone price greater than 10,000.
Description:
Users which have a car of brand BMW, Mercedes-Benz or Audi and whose email does not include any digit.
Code:
Check here
db.collection.find({
car: { $in: ["BMW", "Mercedes-Benz", "Audi"] }, // Query for users who have cars of brand BMW, Mercedes-Benz or Audi
email: { $not: { $regex: "\\d" } }, // Query for users whose email does not contain digits
});Explanation:
The query has two conditions separated by a comma. The first condition searches for documents that have a car field that matches any of the car brands "BMW", "Mercedes-Benz", or "Audi" using the $in operator.
The second condition searches for documents that have an email field that does not contain any digits using the $not and $regex operators. The $not operator negates the effect of the expression that follows it, so $not: { $regex: "\\d" } matches documents whose email field does not contain any digits. The $regex operator matches documents where the value of the email field matches the specified regular expression, which in this case is \d. The backslashes in the regular expression are used to escape the special character \d, which is a shorthand for matching digits.
Description:
Users whose last name starts with M and has a quote character length greater than 15 and email includes his/her last_name
Code:
Check here
db.collection.aggregate([
{
$addFields: {
last_name_regex: {
$regexMatch: {
input: "$email",
regex: {
$concat: [
".*",
{
$toLower: "$last_name"
},
".*@.*"
]
},
options: "i"
}
}
}
},
{
$match: {
last_name: {
$regex: "^M"
},
$expr: {
$gt: [
{
$strLenCP: "$quote"
},
15
]
},
last_name_regex: true
}
},
{
$project: {
last_name_regex: 0
}
}
])Explanation:
This query is used to find users whose last name starts with M, whose quote character length is greater than 15, and whose email includes their last name.
The query uses the aggregation pipeline, which allows for more complex querying using a series of operations or stages.
The first stage is $addFields, which adds a new field to the documents in the pipeline. In this case, it adds a field called last_name_regex, which uses the $regexMatch operator to match the email field with a regular expression that includes the user's last name. The regex expression is constructed using the $concat operator, which concatenates the following elements: .* (any characters zero or more times), the user's last name in lowercase, .*, and @.* (any characters followed by an @ symbol and any characters zero or more times). The options parameter is set to i to make the match case-insensitive.
The second stage is $match, which filters the documents in the pipeline based on certain criteria. The first condition in this stage is that the last_name field starts with the letter M, which is specified using the $regex operator with the regular expression ^M. The second condition is that the length of the quote field is greater than 15, which is specified using the $gt operator with the $strLenCP operator to get the length of the quote field in code points. The third condition is that the last_name_regex field is true, which means that the regular expression in the previous stage matched the email field.
The third stage is $project, which removes the last_name_regex field from the documents in the pipeline. This is done to clean up the output and remove unnecessary fields.
Description:
Show the data of top 10 cities which have the highest number of users and their average income.
Code:
Check here
db.collection.aggregate([
{
$group: {
_id: "$city",
count: { $sum: 1 },
avg_income: { $avg: "$income" },
},
},
{
$sort: {
count: -1,
avg_income: -1,
},
},
{
$limit: 10,
},
]);Explanation:
This MongoDB query is used to show the data of the top 10 cities which have the highest number of users and their average income. The aggregation pipeline has three stages:
-
$groupstage: This stage groups the data by thecityfield and calculates the count of users and average income in each city. The$sumand$avgaggregation operators are used to calculate these values respectively. The results of this stage are stored in thecountandavg_incomefields. -
$sortstage: This stage sorts the grouped data in descending order based on thecountandavg_incomefields. The-1value is used to sort the fields in descending order. -
$limitstage: This stage limits the output to the top 10 cities with the highest count of users and average income.