Apache Ranger for authorization in Hadoop - Mini Project: Build & Apply

Apache Ranger for Authorization

📖 Scenario: You are working in a company that uses Hadoop to store and process big data. To keep data safe, the company uses Apache Ranger to control who can access which data.Apache Ranger helps set rules so only the right people can see or change data.

🎯 Goal: You will create a simple setup to define user permissions using Apache Ranger concepts. You will create a list of users and their roles, set a permission level, check who can access data, and finally print the users who have access.

📋 What You'll Learn

Create a dictionary of users with their roles

Create a variable for minimum permission level required

Use a loop to find users with permission level equal or higher than the minimum

Print the list of users who have access

💡 Why This Matters

🌍 Real World

Apache Ranger is used in big data environments to control who can see or change data. This project shows a simple way to check user permissions.

💼 Career

Understanding authorization helps data engineers and security analysts protect sensitive data and comply with company policies.

1

Create a dictionary of users and their roles

Create a dictionary called user_roles with these exact entries: 'alice': 'admin', 'bob': 'user', 'carol': 'guest', 'dave': 'user', 'eve': 'admin'

Hadoop

# Create the dictionary user_roles with given users and roles
# Your code here

Need a hint?

Use curly braces {} to create a dictionary. Each entry has a username as key and role as value.

2

Set the minimum permission level required

Create a variable called min_permission and set it to the string 'user' to represent the minimum role needed to access data.

Hadoop

user_roles = {'alice': 'admin', 'bob': 'user', 'carol': 'guest', 'dave': 'user', 'eve': 'admin'}
# Set min_permission to 'user'
# Your code here

Need a hint?

Just assign the string 'user' to the variable min_permission.

3

Find users with permission level equal or higher than minimum

Create a list called allowed_users that contains usernames from user_roles whose role is either 'admin' or 'user'. Use a for loop with variables user and role to iterate over user_roles.items().

Hadoop

user_roles = {'alice': 'admin', 'bob': 'user', 'carol': 'guest', 'dave': 'user', 'eve': 'admin'}
min_permission = 'user'
# Create allowed_users list with users having role 'admin' or 'user'
# Your code here

Need a hint?

Use a for loop to check each user's role. If role is 'admin' or 'user', add the username to allowed_users list.

4

Print the list of users who have access

Write a print statement to display the allowed_users list.

Hadoop

user_roles = {'alice': 'admin', 'bob': 'user', 'carol': 'guest', 'dave': 'user', 'eve': 'admin'}
min_permission = 'user'
allowed_users = []
for user, role in user_roles.items():
    if role in ['admin', 'user']:
        allowed_users.append(user)
# Print the allowed_users list
# Your code here

Need a hint?

Use print(allowed_users) to show the list of users who have access.