YARN scheduling policies in Hadoop - Mini Project: Build & Apply

Understanding YARN Scheduling Policies

📖 Scenario: You are working as a data engineer managing a Hadoop cluster. You want to understand how YARN schedules resources for different applications to optimize cluster usage.

🎯 Goal: Learn how to represent and analyze YARN scheduling policies using Python dictionaries and loops to simulate resource allocation.

📋 What You'll Learn

Create a dictionary representing YARN scheduling policies with exact keys and values

Add a configuration variable to select a scheduling policy

Use a loop to simulate resource allocation based on the selected policy

Print the final allocation result

💡 Why This Matters

🌍 Real World

YARN scheduling policies help manage resources in big data clusters efficiently, ensuring fair and optimized use of computing power.

💼 Career

Understanding YARN scheduling is important for data engineers and Hadoop administrators to tune cluster performance and resource management.

1

Create YARN scheduling policies dictionary

Create a dictionary called yarn_policies with these exact entries: 'FIFO': 'First In First Out', 'Capacity': 'Capacity Scheduler', 'Fair': 'Fair Scheduler'.

Hadoop

# Your code here

Need a hint?

Use curly braces to create a dictionary with keys and values as strings.

2

Add selected scheduling policy variable

Create a variable called selected_policy and set it to the string 'Fair'.

Hadoop

yarn_policies = {
    'FIFO': 'First In First Out',
    'Capacity': 'Capacity Scheduler',
    'Fair': 'Fair Scheduler'
}
# Your code here

Need a hint?

Assign the string 'Fair' to the variable selected_policy.

3

Simulate resource allocation based on selected policy

Create a variable called allocation and set it to an empty dictionary. Then use a for loop with variables policy and description to iterate over yarn_policies.items(). Inside the loop, if policy equals selected_policy, set allocation[policy] to 'Resources allocated using ' + description.

Hadoop

yarn_policies = {
    'FIFO': 'First In First Out',
    'Capacity': 'Capacity Scheduler',
    'Fair': 'Fair Scheduler'
}
selected_policy = 'Fair'

# Your code here

Need a hint?

Use a for loop to check each policy and assign allocation only for the selected one.

4

Print the allocation result

Write a print statement to display the allocation dictionary.

Hadoop

yarn_policies = {
    'FIFO': 'First In First Out',
    'Capacity': 'Capacity Scheduler',
    'Fair': 'Fair Scheduler'
}
selected_policy = 'Fair'
allocation = {}
for policy, description in yarn_policies.items():
    if policy == selected_policy:
        allocation[policy] = 'Resources allocated using ' + description

# Your code here

Need a hint?

Use print(allocation) to show the final allocation dictionary.