Tables, items, and attributes in AWS - Mini Project: Build & Apply

Create and Populate a DynamoDB Table

📖 Scenario: You are setting up a simple database to store information about books in a library. You will create a DynamoDB table, define its key structure, and add some book items with attributes.

🎯 Goal: Build a DynamoDB table named LibraryBooks with a primary key and add three book items with specific attributes.

📋 What You'll Learn

Create a DynamoDB table named LibraryBooks with BookID as the partition key (string type).

Define a variable books containing three book items with attributes: BookID, Title, and Author.

Use a loop to add each book item to the LibraryBooks table.

Add a final configuration to enable point-in-time recovery on the table.

💡 Why This Matters

🌍 Real World

DynamoDB tables are used to store structured data for applications like libraries, e-commerce, and user profiles.

💼 Career

Understanding how to create tables, add items, and configure recovery is essential for cloud engineers and developers working with AWS databases.

1

Create the DynamoDB table definition

Create a variable called table_definition that defines a DynamoDB table named LibraryBooks with a partition key named BookID of type string.

AWS

# Your code here

Hint

Use a dictionary with keys TableName, KeySchema, AttributeDefinitions, and ProvisionedThroughput.

2

Define the book items data

Create a variable called books that is a list of dictionaries. Each dictionary represents a book with keys BookID, Title, and Author. Add these exact books: {'BookID': 'B1', 'Title': '1984', 'Author': 'George Orwell'}, {'BookID': 'B2', 'Title': 'To Kill a Mockingbird', 'Author': 'Harper Lee'}, and {'BookID': 'B3', 'Title': 'The Great Gatsby', 'Author': 'F. Scott Fitzgerald'}.

AWS

table_definition = {
    'TableName': 'LibraryBooks',
    'KeySchema': [
        {'AttributeName': 'BookID', 'KeyType': 'HASH'}
    ],
    'AttributeDefinitions': [
        {'AttributeName': 'BookID', 'AttributeType': 'S'}
    ],
    'ProvisionedThroughput': {
        'ReadCapacityUnits': 5,
        'WriteCapacityUnits': 5
    }
}

# Your code here

Hint

Use a list with three dictionaries exactly matching the book details.

3

Add the book items to the table

Write a for loop using variables book to iterate over the books list and add each book to the LibraryBooks table using a method call table.put_item(Item=book).

AWS

table_definition = {
    'TableName': 'LibraryBooks',
    'KeySchema': [
        {'AttributeName': 'BookID', 'KeyType': 'HASH'}
    ],
    'AttributeDefinitions': [
        {'AttributeName': 'BookID', 'AttributeType': 'S'}
    ],
    'ProvisionedThroughput': {
        'ReadCapacityUnits': 5,
        'WriteCapacityUnits': 5
    }
}

books = [
    {'BookID': 'B1', 'Title': '1984', 'Author': 'George Orwell'},
    {'BookID': 'B2', 'Title': 'To Kill a Mockingbird', 'Author': 'Harper Lee'},
    {'BookID': 'B3', 'Title': 'The Great Gatsby', 'Author': 'F. Scott Fitzgerald'}
]

# Assume 'table' is the DynamoDB Table resource object

# Your code here

Hint

Use a for loop with variable book and call table.put_item(Item=book) inside the loop.

4

Enable point-in-time recovery on the table

Add a configuration line to enable point-in-time recovery on the LibraryBooks table by calling table.update_point_in_time_recovery(PointInTimeRecoverySpecification={'PointInTimeRecoveryEnabled': True}).

AWS

table_definition = {
    'TableName': 'LibraryBooks',
    'KeySchema': [
        {'AttributeName': 'BookID', 'KeyType': 'HASH'}
    ],
    'AttributeDefinitions': [
        {'AttributeName': 'BookID', 'AttributeType': 'S'}
    ],
    'ProvisionedThroughput': {
        'ReadCapacityUnits': 5,
        'WriteCapacityUnits': 5
    }
}

books = [
    {'BookID': 'B1', 'Title': '1984', 'Author': 'George Orwell'},
    {'BookID': 'B2', 'Title': 'To Kill a Mockingbird', 'Author': 'Harper Lee'},
    {'BookID': 'B3', 'Title': 'The Great Gatsby', 'Author': 'F. Scott Fitzgerald'}
]

# Assume 'table' is the DynamoDB Table resource object
for book in books:
    table.put_item(Item=book)

# Your code here

Hint

Call table.update_point_in_time_recovery with the correct dictionary to enable recovery.

Practice

1. What is the main purpose of a table in AWS DynamoDB?

easy

A. To store items, which are records

B. To run code functions

C. To manage user permissions

D. To host websites

Solution

1. Step 1: Understand the role of a table in DynamoDB

   A table is a container that holds items, which are like rows in a database.

2. Step 2: Identify the correct purpose

   Since tables store items (records), this matches To store items, which are records.

3. Final Answer:

   To store items, which are records -> Option A

4. Quick Check:

   Table = container for items [OK]

Hint: Tables hold records called items [OK]

Common Mistakes:

• Confusing tables with code functions
• Thinking tables manage permissions
• Assuming tables host websites

2. Which of the following is the correct way to define an item attribute in DynamoDB?

easy

A. ("Name", "John", "Age", 30)

B. {"Name": "John", "Age": 30}

C. ["Name", "John", "Age", 30]

D. "Name": "John", "Age": 30

Solution

1. Step 1: Recognize the attribute format

   Attributes are key-value pairs, best represented as JSON objects with keys and values.

2. Step 2: Match the correct syntax

   {"Name": "John", "Age": 30} shows a JSON object with keys "Name" and "Age" and their values, which is correct.

3. Final Answer:

   {"Name": "John", "Age": 30} -> Option B

4. Quick Check:

   Attributes = key-value pairs in JSON [OK]

Hint: Attributes are key-value pairs in JSON format [OK]

Common Mistakes:

• Using arrays instead of key-value pairs
• Using tuples instead of objects
• Omitting braces for JSON objects

3. Given a DynamoDB table with primary key "UserID", what happens if you try to add two items with the same UserID but different attributes?

medium

A. Both items are stored separately

B. The table creates a duplicate primary key

C. An error is thrown and no item is added

D. The second item overwrites the first item

Solution

1. Step 1: Understand primary key uniqueness

   In DynamoDB, the primary key must be unique for each item in the table.

2. Step 2: Effect of duplicate primary key

   If you add an item with an existing primary key, it replaces the old item with the new one.

3. Final Answer:

   The second item overwrites the first item -> Option D

4. Quick Check:

   Duplicate key = overwrite existing item [OK]

Hint: Duplicate primary keys overwrite existing items [OK]

Common Mistakes:

• Thinking both items are stored separately
• Expecting an error on duplicate keys
• Assuming duplicates are allowed

4. You try to insert an item into a DynamoDB table but get an error. The item has no primary key attribute. What is the most likely cause?

medium

A. Missing required primary key attribute in the item

B. Table is full and cannot accept new items

C. Attributes have invalid data types

D. You exceeded the maximum number of attributes

Solution

1. Step 1: Recall primary key requirement

   Every item must have the primary key attribute to be uniquely identified in the table.

2. Step 2: Identify cause of error

   If the item lacks the primary key attribute, DynamoDB rejects it with an error.

3. Final Answer:

   Missing required primary key attribute in the item -> Option A

4. Quick Check:

   Primary key missing causes insert error [OK]

Hint: Every item must include the primary key attribute [OK]

Common Mistakes:

• Assuming table capacity causes insert errors
• Blaming attribute data types without checking keys
• Thinking attribute count limits cause this error

5. You want to design a DynamoDB table to store user profiles. Each user has a unique UserID and may have multiple email addresses. How should you structure the table and items to handle this?

hard

A. Use email as the primary key and ignore UserID

B. Use UserID as the primary key and create a separate item for each email

C. Use UserID as the primary key and store emails as a list attribute inside each item

D. Create multiple tables, one per email address

Solution

1. Step 1: Identify unique identifier

   UserID uniquely identifies each user, so it should be the primary key.

2. Step 2: Store multiple emails

   Since a user can have multiple emails, store them as a list attribute inside the user item.

3. Step 3: Evaluate other options

   Creating separate items per email duplicates UserID or loses uniqueness; using email as key ignores UserID; multiple tables is inefficient.

4. Final Answer:

   Use UserID as the primary key and store emails as a list attribute inside each item -> Option C

5. Quick Check:

   Primary key + list attribute for multiple values [OK]

Hint: Use primary key for user, list attribute for multiple emails [OK]

Common Mistakes:

• Using email as primary key instead of UserID
• Creating multiple items for one user
• Making multiple tables unnecessarily