Partition key distribution in DynamoDB - Mini Project: Build & Apply

Partition Key Distribution in DynamoDB

📖 Scenario: You are building a simple DynamoDB table to store user orders for an online store. To keep the database fast and balanced, you need to choose a good partition key that spreads the data evenly.

🎯 Goal: Create a DynamoDB table with a partition key that distributes user orders evenly across partitions. You will define the table schema, set a partition key, and add sample items to see how the key affects data distribution.

📋 What You'll Learn

Create a DynamoDB table named Orders with a partition key called OrderID of type string.

Add a variable sample_orders containing 5 orders with unique OrderID values.

Write a query to retrieve all orders with a specific OrderID.

Add a secondary index on CustomerID to allow queries by customer.

💡 Why This Matters

🌍 Real World

Good partition key design helps DynamoDB distribute data evenly, improving speed and scalability for real online stores or apps.

💼 Career

Understanding partition keys and indexes is essential for database roles working with NoSQL databases like DynamoDB.

1

Create the DynamoDB table schema

Create a DynamoDB table named Orders with a partition key called OrderID of type string. Use the AWS SDK syntax to define the table schema in a variable called table_schema.

DynamoDB

table_schema = {
    # Your code here
}

Need a hint?

Define table_schema as a dictionary with keys TableName, KeySchema, AttributeDefinitions, and ProvisionedThroughput. The partition key is OrderID of type string.

2

Add sample orders data

Create a list called sample_orders with 5 dictionaries. Each dictionary should have keys OrderID (string), CustomerID (string), and Amount (number). Use these exact OrderID values: "O1001", "O1002", "O1003", "O1004", "O1005".

DynamoDB

table_schema = {
    'TableName': 'Orders',
    'KeySchema': [
        {'AttributeName': 'OrderID', 'KeyType': 'HASH'}
    ],
    'AttributeDefinitions': [
        {'AttributeName': 'OrderID', 'AttributeType': 'S'}
    ],
    'ProvisionedThroughput': {
        'ReadCapacityUnits': 5,
        'WriteCapacityUnits': 5
    }
}

sample_orders = [
    # Your code here
]

Need a hint?

Make a list of 5 dictionaries with the exact OrderID values given. Each dictionary must also have CustomerID and Amount keys.

3

Write a query to get orders by OrderID

Write a function called get_order_by_id that takes a parameter order_id. Inside the function, write a query expression to get the order from sample_orders where OrderID matches order_id. Use a for loop with variables order to find the matching order and return it.

DynamoDB

table_schema = {
    'TableName': 'Orders',
    'KeySchema': [
        {'AttributeName': 'OrderID', 'KeyType': 'HASH'}
    ],
    'AttributeDefinitions': [
        {'AttributeName': 'OrderID', 'AttributeType': 'S'}
    ],
    'ProvisionedThroughput': {
        'ReadCapacityUnits': 5,
        'WriteCapacityUnits': 5
    }
}

sample_orders = [
    {'OrderID': 'O1001', 'CustomerID': 'C001', 'Amount': 250},
    {'OrderID': 'O1002', 'CustomerID': 'C002', 'Amount': 450},
    {'OrderID': 'O1003', 'CustomerID': 'C001', 'Amount': 150},
    {'OrderID': 'O1004', 'CustomerID': 'C003', 'Amount': 300},
    {'OrderID': 'O1005', 'CustomerID': 'C004', 'Amount': 500}
]

def get_order_by_id(order_id):
    # Your code here

Need a hint?

Define a function get_order_by_id that loops through sample_orders. Return the order where OrderID matches order_id. Return None if not found.

4

Add a secondary index on CustomerID

Update the table_schema dictionary to add a global secondary index named CustomerIndex. The index should have CustomerID as the partition key of type string. Add CustomerID to the AttributeDefinitions list as well.

DynamoDB

table_schema = {
    'TableName': 'Orders',
    'KeySchema': [
        {'AttributeName': 'OrderID', 'KeyType': 'HASH'}
    ],
    'AttributeDefinitions': [
        {'AttributeName': 'OrderID', 'AttributeType': 'S'}
    ],
    'ProvisionedThroughput': {
        'ReadCapacityUnits': 5,
        'WriteCapacityUnits': 5
    }
}

sample_orders = [
    {'OrderID': 'O1001', 'CustomerID': 'C001', 'Amount': 250},
    {'OrderID': 'O1002', 'CustomerID': 'C002', 'Amount': 450},
    {'OrderID': 'O1003', 'CustomerID': 'C001', 'Amount': 150},
    {'OrderID': 'O1004', 'CustomerID': 'C003', 'Amount': 300},
    {'OrderID': 'O1005', 'CustomerID': 'C004', 'Amount': 500}
]

def get_order_by_id(order_id):
    for order in sample_orders:
        if order['OrderID'] == order_id:
            return order
    return None

# Add a global secondary index on CustomerID below

Need a hint?

Add a GlobalSecondaryIndexes key to table_schema. Define an index named CustomerIndex with CustomerID as the partition key. Also add CustomerID to AttributeDefinitions.