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My Mongo DB Note

mongodb, database7 min read


  • VS Code extension:
  • Compass:



Retrieve all documents in the collection

The find() method in MongoDB Node.js driver returns a cursor to the documents, not the documents themselves. To retrieve all documents from a query, you need to iterate over the cursor or convert it to an array.


Find a single document

findOne() for a single document or find() for multiple documents

const users = await usersCollection
.sort({ updateDateIso: -1})

Find with nested attributes

{ "": 'Mrs Livingston'}

Find documents with property’s value with trailing spaces

// Compass
{"jobNo": {"$regex": ".+\\s+$"}}
// Code
const results = await yourCollection.find({
jobNo: { $regex: /\s+$/, $options: 'i' }

Find if a property has Int32 type value

Sometimes, your property has incorrect type value. In my case, gasSafeNumber is supposed to have string value but some documents had Int32 values.

find({ gasSafeNumber: { $type: ['int']}})

Find if the field exists

find({ postCode: { $exists: true } })

FInd if email contains skyline

find({"email": {"$regex": "skyline"}})


Use .sort({})

1 for ascending order and -1 for descending order

const users = await usersCollection
.sort({ updateDateIso: -1})


Removing Duplications

In one use-case, I had to retrieve companyId and companyName from users collection. As the collection is about users, those retrieved results contained duplicates. To return distinct results without duplicates, I useed the aggregation framework with $group stage to group the documents by the specified fields, companyId and companyName and then project the fields I was interested in. Here's how I wrote the MongoDB query:

$group: {
_id: { companyId: "$companyId", companyName: "$companyName" },
$project: {
_id: 0, // Exclude the _id field from the results
companyId: "$_id.companyId", // Project the companyId
companyName: "$_id.companyName" // Project the companyName

Here's what this aggregation does:

  1. $group: This stage groups documents by both companyId and companyName. Each unique combination of companyId and companyName becomes a single document in the resulting output of this stage.
  2. $project: This stage then reshapes each document to include only the companyId and companyName. The _id: 0 excludes the _id field from the output, and the values are set to the corresponding parts of the $_id object created in the $group stage.


Update a field

{ email: { $in: [
{ $set: { 'status': 'ACTIVE' } }

Upsert a document

Use the key(s) as filter expression and set upsert to true.

import { MongoClient } from 'mongodb'
const user: User = {
companyId: companyId.trim(),
companyName: companyName.trim(),
firstname: firstname.trim(),
lastname: lastname.trim(),
email: email.trim().toLowerCase(),
gasSafetyNumber: gasSafetyNumber?.trim(),
oftecNumber: oftecNumber?.trim(),
const database = client.db('service-agent')
const users = database.collection('users')
const result = await users.updateOne(
{ companyId: user.companyId, email: },
{ $set: { ...user } },
{ upsert: true }
await client.close()

Remove a field that’s not used any more

You can use $unset

const query = { postCode: { $exists: true } };
const updateResult = db.getCollection('registrations').updateMany(
{ $unset: { postCode: "" } }
console.log(`Documents updated: ${updateResult.modifiedCount}`);


When creating an index in MongoDB, you are defining the way MongoDB organizes and traverses the data when performing queries. Choosing the correct index type is crucial for query performance. Here's what each of the index types you mentioned means:

1 (Ascending): This is an ascending order index. When you index a field with a value of 1, MongoDB will sort the indexed field in ascending order. This is beneficial for queries that sort ascendingly through the field.

1 (Descending): This is a descending order index. When you index a field with a value of -1, MongoDB sorts the indexed field in descending order. This is useful for queries that sort descendingly through the field.

2dsphere: This index type supports queries that calculate geometries on an earth-like sphere. It's the index of choice for storing geographical location data and performing complex location-based queries like finding the nearest points of interest, calculating distances, and querying within specified regions or boundaries.

Text: A text index is used to support text search queries on string content. A text index will tokenize the string into words, filter out common stop words, and perform case-insensitive matching. It's useful for full-text search in applications, such as searching through article contents, comments, posts, etc.

When deciding which index to use, consider the following:

  • For fields where you'll perform range queries or sort operations, a standard ascending (1) or descending (-1) index would be appropriate.
  • If you're working with geospatial data and need to run queries that consider the Earth's curvature, use a 2dsphere index.
  • If you need to search for text within string fields, then a text index is the right choice.

Indexes are not just limited to these types; there are other index types in MongoDB for specific use cases, such as hashed indexes for hash-based sharding and compound indexes that index multiple fields together. When creating a compound index, each field can be indexed as either ascending or descending, which you would decide based on how you query those fields.


use $skip, $limit, and countDocuments.

export const selectUsersMongo = async (
page: number,
pageSize: number,
searchCondition: string,
searchValue: string
: Promise<[User[], number]> => {`selecting users by page: ${page} and pageSize: ${pageSize}`)
await client.connect()
try {
const skip = (page - 1) * pageSize
const filter = getFilter(searchCondition, searchValue)
const total = await usersCollection.countDocuments(filter)
const users = await usersCollection
return [users, total]
} catch (error) {
logger.error('error selecting users:', error)
} finally {
await client.close()

Removing _id from retrieved data

Mongo DB uses _id as an identity attribute that’s unique. Yet, I don’t use it as I have another key that’s unique to the domain. Often it’s unnecessary to have the attribute and the value in the retrieved data set.

To remove the _id field from the documents returned by a MongoDB query in your JavaScript application, you have a couple of options:

Use MongoDB's $project in Aggregation Pipeline

If you're using an aggregation pipeline, you can add a $project stage to your pipeline to exclude the _id field:

// ... (your other aggregation stages)
$project: {
_id: 0, // Exclude the _id field
// Include other fields you want

Modify the Result in JavaScript

If you're not using an aggregation pipeline or prefer to handle this in JavaScript, you can simply delete the _id property from each object after you've fetched the results:

const results = await db.collection.find().toArray();
results.forEach(doc => {
delete doc._id; // Remove the _id property
// Now 'results' doesn't have the _id field

Specify Fields in find() or findOne()

If you are using find() or findOne(), you can specify which fields to include or exclude in the second argument (projection):

const results = await db.collection.find({}, { projection: { _id: 0 } }).toArray();

In this code, { projection: { _id: 0 } } is used to exclude the _id field from the results.

Choose Based on Use Case

  • Use the $project stage in the aggregation pipeline if you are already using an aggregation pipeline for other reasons.
  • Modify the result in JavaScript if you want more flexibility or need to perform other transformations on the data.
  • Use projection in find() or findOne() for a straightforward query without an aggregation pipeline.

Remember, the _id field is a unique identifier for each document in MongoDB. If you remove it, make sure that it's not needed for any other operations (like updates or deletes) later in your application.

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