Understanding MongoDB: An Introduction - Installation & Database Creation

MongoDB is a popular document-oriented NoSQL database that uses JSON-like documents with optional schemas. This session will demonstrate the practical implementation of installing MongoDB on Ubuntu and creating database.

Setup Instruction

Step 1: Update Your System

Before proceeding with the installation of any package on your Ubuntu system, it's recommended to update and upgrade the system packages. Execute the following command to do so:

sudo apt-get update
sudo apt-get upgrade

Step 2: Install MongoDB

Now you can install MongoDB by typing the following command:

sudo apt-get install mongodb

To verify if the MongoDB service started successfully, you can run:

systemctl status mongodb

Now, you can start MongoDB if it is not running by default.

sudo systemctl start mongodb

Step 3: MongoDB Shell

MongoDB shell is an interactive JavaScript interface to MongoDB. You can use it to query and update data as well as perform administrative operations. To start MongoDB shell, you can run the following command:

mongo

Creating a Database

Now that we have MongoDB setup, let's create a database.

Step 1: Start MongoDB Shell

As we step into creating database, considering you are in MongoDB Shell; if you aren't, you can start MongoDB shell by typing mongo in terminal.

Step 2: Create Database

In MongoDB, use DATABASE_NAME is used to create a database. Replace DATABASE_NAME with a name of your choice. Let's create a database called store.

use store

Creating Tables (Collections)

In MongoDB, collections are equivalent to tables in relational databases. BSON documents stored in a collection can have different sets of fields, but generally they will hold data for the same type of objects.

Create Users Table:

Assuming we are creating a users table with the fields name, email, and password, we can use the insert() function:

db.users.insert({name: "John Doe", email: "john@example.com", password: "123456"})

Repeat the above step to insert as many users as you want.

Create Orders Table:

Let's create an orders table, with fields such as productId, userId and quantity. Remember that MongoDB creates a new collection if it does not exist:

db.orders.insert({productId: "001", userId: "JD01", quantity: 5})

Create Products Table:

Let's create a products table, with fields productName, price and stock. This can be done as follows:

db.products.insert({productName: "Apple", price: 1.20, stock: 1000})

Note: In all of the above steps, MongoDB automatically creates a unique _id for each document if not provided.

Creating Pivot Tables

MongoDB does not support pivot tables directly as it is a NoSQL database and does not follow the fixed table schema of SQL databases. However, using multiple stages of aggregation commands, you can create a representation similar to the pivot table.

Assuming we need a pivot table that shows quantity of each product ordered by each user, we would use aggregation stages: $lookup, $unwind, $group and $project.

db.orders.aggregate([{
    $lookup:
           {
             from: "users",
             localField: "userId",
             foreignField: "_id",
             as: "user_detail"
           }
    },
    {
    $unwind: "$user_detail"
    }, 
    {
    $group: {"_id": "$user_detail.name", "Products Purchased": { $sum: "$quantity" } }
    }, 
    {
    $project: { "_id": 0, "User": "$_id", "Products Purchased": 1 }
    }])

This code will output a list of users and the total quantity of all products each user has purchased, emulating the pivot table functionality. You can adjust the fields and calculation to suit your needs.

This marks the end of the introduction to MongoDB focusing on MongoDB installation on Ubuntu, DB and collections creation, and a basic emulation of pivot table. The actual contents of your database would be more complex, and MongoDB provides capabilities for complex queries, indexing, and real-time aggregation to handle varied data use cases.

Setting Up MongoDB on Ubuntu: Step-by-Step Guide

Installing MongoDB

Before anything else, make sure you update your system's package list with:

sudo apt-get update

To install MongoDB on Ubuntu, you can use the apt command:

sudo apt-get install -y mongodb

This will install MongoDB and its required packages.

Starting and Verifying MongoDB

Start the MongoDB service using:

sudo systemctl start mongodb

You can verify that MongoDB has started successfully using:

sudo systemctl status mongodb

If MongoDB started successfully, you'll see an output that mentions that the mongodb service is active (running).

Creating a Database

MongoDB has a simple command to create a database. Connect to the MongoDB shell using mongo command:

mongo

Create a database named yourDbName with:

use yourDbName

Creating Tables or Collections

In MongoDB, tables are called collections. Inside your MongoDB shell, run the following commands to create collections for users, orders and products:

db.createCollection('users')
db.createCollection('orders')
db.createCollection('products')

Adding Documents

Below are examples of how to add documents to these collections.

db.users.insert({name:"John", email:"john@email.com", password:"securepassword"})
db.orders.insert({userId:"userId", productId:"productId", quantity:5})
db.products.insert({productName:"Product", productDescription:"Product Description", price:100.00})

Pivot Tables in MongoDB

MongoDB doesn't support pivot tables as is traditionally known in SQL databases. Instead, you can use the aggregation framework that MongoDB provides, or use visualization tools like MongoDB Compass that supports data exploration.

For example, we can find the total quantity ordered per user with:

db.orders.aggregate([{$group: {_id: "$userId", total: {$sum: "$quantity"}}}])

This group the data by userId and calculates the sum of quantity for each userId.

In case of complex analytical needs, consider using data analysis tools like Pandas in Python.

Final Thoughts

This guide should have provided you with a basic understanding of how to set up MongoDB, create a database, collections, and documents in Ubuntu. Remember that as an NoSQL database, MongoDB differs from SQL databases and doesn't support traditional SQL features like joins and pivot tables. Instead, it provides other powerful features like embedded documents and the aggregation pipeline.

Creating a MongoDB Database

Assuming that MongoDB has been successfully installed and set on Ubuntu as per your project's first and second parts, let's jump straight to the practical implementation of creating a MongoDB database. MongoDB treats collections like tables and uses JSON-like field-value pair documents for data storing, which resembles the Python's dictionaries.

Step 1: Launch MongoDB Shell

First, open the terminal and launch the MongoDB Shell by running the following command:

mongo

This will take you to the MongoDB command interface.

Step 2: Create a Database

In MongoDB, creating a new database is as simple as switching to a non-existent one. We'll create a new database named ecommerce:

use ecommerce

Now, the current database is set to ecommerce.

Note: The newly created database ecommerce will not appear in the list of databases if it's empty.

Step 3: Create Collections (Tables)

We can create three collections - users, orders, and products:

db.createCollection('users')     
db.createCollection('orders')
db.createCollection('products')

Step 4: Insert Documents (Rows)

In MongoDB, tables or collections consist of documents, which can be inserted into the collections like this:

For Users:

db.users.insert({
   name: 'John Doe',
   email: 'johndoe@example.com',
   password: 'pass123',
})

For Products:

db.products.insert({
   name: 'Product 1',
   price: 100,
   category: 'Electronics',
   description: 'This is product 1'
})

For Orders:

db.orders.insert({
   userId: 'id_of_user',
   productId: 'id_of_product',
   quantity: 1
})

In MongoDB, a document is equivalent to a row of a table in SQL and each field in the document represents a column of the table in SQL.

Step 5: Creating a Pivot Table

MongoDB doesn't inherently support pivot tables like SQL databases. So you can implement them using MongoDB's Aggregation Framework with $group, $project operations, and manipulating data as per required pivot structure.

db.orders.aggregate([
   {
      $lookup: {
         "from": "users",
         "localField": "userId",
         "foreignField": "_id",
         "as": "user"
      }
   },
   {
      $lookup: {
         "from": "products",
         "localField": "productId",
         "foreignField": "_id",
         "as": "product"
      }
   },
   {
      $project: {
         "userId": 1,
         "productId": 1,
         "quantity": 1,
         "user.name": 1,
         "user.email": 1,
         "product.name": 1,
         "product.price": 1
      }
   }
])

The $lookup stage is equivalent to the JOIN in SQL and is used to combine data from two collections. The $project stage is used to modify the output document, including adding new fields, removing existing fields, or reshaping the fields.

With this, you have created a simple ecommerce database with users, products, and orders collections in MongoDB and also implemented a pivot table-like structure using the aggregation framework. Keep in mind that MongoDB has a flexible schema, so documents inside a collection can vary in the number of fields, content, and size. This provides high flexibility in adapting the data structure over time.

Building a 'Users' Table (Collection) in MongoDB: Procedures and Guidelines

Assuming you have MongoDB already installed and set up, let's proceed with creating a 'users' table, which in MongoDB is technically referred to as a 'collection'. We'll also establish how to make simple relationship representations akin to 'pivot tables' in SQL as MongoDB is a Non-Relational Database. This demonstration uses MongoDB's JavaScript-based shell: mongo.

1. Launch MongoDB Shell

Open your terminal application and connect to your MongoDB instance by typing mongo:

mongo

2. Select or Create the Database

Select your desired database where you want to create the 'users' collection. If it doesn't exist, this command will create it:

use YourDatabaseName;

Please replace YourDatabaseName with your actual database name.

3. Create the 'Users' Collection

In MongoDB, creating a collection is as straightforward as inserting a document. Let's insert a user document into a 'users' collection:

db.users.insert({
    username: "username1",
    email: "email1@example.com",
    password: "hashed_password1",
    fullName: "Full Name 1",
    createdAt: new Date(),
    updatedAt: new Date()
});

The 'users' collection is now created, and your first user is inserted. Note the 'password' is to be stored as a hashed value for security purposes.

4. Validate Creation of 'Users' Collection

Verify if the 'users' collection exists and if the user data was inserted successfully:

db.users.find();

5. Add More Users

Insert more users as necessary:

db.users.insertMany([
    {
        username: "username2",
        email: "email2@example.com",
        password: "hashed_password2",
        fullName: "Full Name 2",
        createdAt: new Date(),
        updatedAt: new Date()
    },
    {
        username: "username3",
        email: "email3@example.com",
        password: "hashed_password3",
        fullName: "Full Name 3",
        createdAt: new Date(),
        updatedAt: new Date()
    }
]);

6. Create Relationships (Pivot Tables Analogy)

As MongoDB is a NoSQL database, relationships are handled differently than in SQL databases. Unlike SQL, MongoDB supports in-built joins and multi-dimensional data types like arrays and sub-documents. You can embed related data in a single document structure which might often eliminate the need for joins.

However, referencing (similar to SQL foreign keys and pivot tables) can be used when embedding is not feasible. Here's an example creating a reference in an 'orders' collection pointing to a 'users' document:

db.orders.insert({
    orderNumber: "001",
    userId: db.users.findOne({username: "username1"})._id,
    productIds: [db.products.findOne({productName: "Product 1"})._id, db.products.findOne({productName: "Product 2"})._id],
    orderDate: new Date(),
    updatedAt: new Date()
});

This inserts an order document to the 'orders' collection. Here, userId references a user in the 'users' collection, and productIds is an array holding references to products in the 'products' collection.

Note: Ensure you have the 'products' collection and relevant documents available before executing this.

Conclusion

In conclusion, we have covered the creation of a 'users' collection and populating it with user documents. Also, an example of creating relationships was highlighted. The MongoDB JavaScript-based shell was used for execution, but all commands can be converted to and from other MongoDB-supported languages as necessary.

Always remember to use hashed values or another form of encryption for passwords and other sensitive data in a production-level database, as shown with the 'hashed_password' placeholder.

Constructing 'Orders' Table: Practices and Approaches

In this section, we will illustrate the process of constructing the 'Orders' table in a MongoDB database. We will assume that MongoDB has been installed in Ubuntu and the database has already been created based on your previous instructions.

Please take note that we will implement this guide using MongoDB shell. Here is the step-by-step process:

Step 1: Opening MongoDB shell.

mongo

Step 2: Accessing the Database.

Use the database that was created in the previous sections by using the use command. For instance, if the database name is "MyDatabase":

use MyDatabase

Step 3: Creating the 'Orders' Collection.

In MongoDB, a table is equivalent to a collection. Now, let's create an 'Orders' collection:

db.createCollection("orders")

You should receive a response saying { "ok" : 1 } which means the collection is created successfully.

Step 4: Inserting Documents (Rows) to 'Orders' Collection.

To carry out this task, the insert() method will be used. Each document would include fields such as orderID, userID, productID, and quantity.

Please note that here we assume the existence of foreign keys 'userID' and 'productID' linking to documents in the 'Users' and 'Products' collections respectively, as per a typical e-commerce database would be structured.

db.orders.insertMany([
   { orderID: 1, userID: 1, productID: 101, quantity: 3 },
   { orderID: 2, userID: 2, productID: 102, quantity: 1 },
   { orderID: 3, userID: 3, productID: 103, quantity: 2 }
   // more entries as per your data
])

This insertMany() function allows multiple documents to be inserted at once inside [].

Step 5: Verifying the 'Orders' Collection.

Let's check if the 'Orders' collection was created properly.

db.orders.find().pretty()

By running the above command, you will see the entire 'Orders' collection. It takes the elements from 'orders' and display them in a readable format.

Step 6: Creating Indexes for Faster Queries

It's good practice to create indexes on fields you often query. Let's say you frequently need to retrieve orders based on 'userID', create index like this:

db.orders.createIndex({ userID: 1})

The '1' means ascending order, you could use '-1' for descending.

Creating Pivot Tables for Enhanced Data Analysis in MongoDB

Pivot tables for MongoDB are made by generating aggregation pipelines. The $group, $project, and $unwind stages are often helpful tools. Here is a simple example that groups orders by 'userID' and sums the 'quantity' for a basic order analysis:

db.orders.aggregate([
   { $group : 
       { 
           _id : "$userID", 
           totalQuantity : { $sum: "$quantity" } 
       } 
   }
])

This command will spit out a list of 'userID's along with the cumulative total 'quantity' they ordered.

That's all there is to creating an 'Orders' table in MongoDB. Just remember that MongoDB is a NoSQL database, and the depiction of a 'table' is primarily conceptual.

Generating 'Products' Table: Process and Detailed Instructions

In this part of the series, we are going to create a 'Products' table in MongoDB. Here, 'table' refers to 'collections' in MongoDB nomenclature. MongoDB stores documents, which are similar to records in a relational database, in collections. This section will walk through the necessary process of generating our 'Products' collection.

Before proceeding, make sure MongoDB is installed and the MongoDB service is running on your Ubuntu environment. Also, you should have already created your database where the 'Products' collection will reside.

Let's assume that each product will have a product_id, product_name, price, and quantity fields.

Connect to MongoDB

First of all, connect to MongoDB using the MongoDB shell. Open your terminal and write the following command:

mongo

Select the Database

After you have connected to MongoDB, select your database (the one you created earlier) using the use command.

use YOUR_DATABASE_NAME

Create the 'Products' Collection

To creating a collection named 'products', you can utilize the createCollection command.

db.createCollection('products')

The above command will create a new collection named 'products' in the current database.

Inserting Data into the 'Products' Collection

After creating the products collection, we can insert documents into the collection. In MongoDB, each record is referred to as a document.

Let us assume we have four different products. We will insert them into the products collection as below:

db.products.insert([
    {
        product_id: 'P01', 
        product_name: 'Product 1', 
        price: 50, 
        quantity: 100
    },
    {
        product_id: 'P02', 
        product_name: 'Product 2', 
        price: 75, 
        quantity: 200
    },
    {
        product_id: 'P03', 
        product_name: 'Product 3', 
        price: 30, 
        quantity: 150
    },
    {
        product_id: 'P04', 
        product_name: 'Product 4', 
        price: 120, 
        quantity: 300
    }
])

Please note that in MongoDB, _id attribute is a 12 bytes hexadecimal number which assures the uniqueness of every document. You can generate ObjectId using ObjectId() function in MongoDB. If you do not provide _id attribute, MongoDB provides a unique id for each document.

Through this article, we have successfully created a 'products' collection (a table in SQL), and inserted product data into it.

In the upcoming parts of the series, we will focus on reading, updating, deleting, and conducting enhanced data analysis using our newly created collection.

Creating Pivot Tables in MongoDB

MongoDB, being a NoSQL database, doesn't directly support the creation of Pivot Tables like in a SQL database. However, with the use of MongoDB's powerful aggregation pipeline, we can effectively create pivot tables. In this guide, we will create a pivot table for the Users, Orders, and Products collections.

Prerequisite

Make sure you have already created Users, Orders, and Products collections.

---

Implementation

1. Create a Joint Collection

First, we need to create a joined collection which includes all data from the Users, Orders, and Products collections. With MongoDB, we use the $lookup stage to perform a left outer join to an unsharded collection in the same database.

Let's consider an example collection structure where Users collection has user_id and Orders collection has fields: order_id, product_id and user_id and Products collection has fields: product_id.

db.Orders.aggregate([
   {
      $lookup:
        {
          from: "Users",
          localField: "user_id",
          foreignField: "user_id",
          as: "user_order"
        }
   },
   {
       $unwind: "$user_order"
   },
   {
      $lookup:
        {
          from: "Products",
          localField: "product_id",
          foreignField: "product_id",
          as: "user_order_product"
        }
   },
   {
       $unwind: "$user_order_product"
   },
   {
       $out: "JointCollection"
   }
])

2. Create a Pivot Table

Given, UserOrdersProducts collection derived from Step 1 has the following document structure:

{
  order_id: ObjectId(...),
  user_id: ObjectId(...),
  product_id: ObjectId(...),
  user_order: { user_id: ObjectId(...), ... },
  user_order_product: { product_id: ObjectId(...), ... }
}

To create a pivot table, we use MongoDB's aggregation pipeline stages such as $group, $project and $unwind.

db.JointCollection.aggregate([
  {
    $group: {
      _id: "$user_id",
      orders: {
          $push: {
            order_id: "$order_id",
            product_details: "$user_order_product"
          }
      }
    }
  },
  {
    $project: {
      _id: 1,
      orders: {
        $reduce: {
            input: "$orders",
            initialValue: [],
            in: {
              $concatArrays: ["$$value", ["$$this"]]
            }
        }
      }
    }
  },
  {
    $unwind: "$orders"
  },
  {
    $group: {
      _id: "$_id",
      orders: {
        $push: "$orders"
      }
    }
  },
])

This $group stage groups the result by user_id. The $push operator in the orders field creates an array of order_id and product_details for each order. Then, the $project, $reduce, $concatArrays, and $unwind stages transform this array into the desired pivot table format, i.e., an array of orders for each user.

That's it! You now have a pivot table with users and their orders and the details of the products ordered.

Please replace the user_id, order_id, and product_id with the actual fields you used in your collections.