Bird
Raised Fist0
DynamoDBquery~30 mins

Unprocessed items handling in DynamoDB - Mini Project: Build & Apply

Choose your learning style10 modes available
LearnWhyDeepVisualTryChallengeProjectRecallTime
Handling Unprocessed Items in DynamoDB Batch Write
📖 Scenario: You are managing a DynamoDB table for an online bookstore. You want to batch write multiple book records at once. Sometimes, DynamoDB returns unprocessed items due to throttling or capacity limits. You need to handle these unprocessed items by retrying the batch write until all items are processed.
🎯 Goal: Build a DynamoDB batch write operation that retries unprocessed items until all are successfully written.
📋 What You'll Learn
Create a list of book items to write to DynamoDB
Set a maximum retry count for handling unprocessed items
Write a loop that performs batch write and retries unprocessed items
Complete the batch write operation ensuring no unprocessed items remain
💡 Why This Matters
🌍 Real World
Batch writing is common when inserting many records efficiently into DynamoDB. Handling unprocessed items ensures data consistency and reliability.
💼 Career
Understanding unprocessed items handling is essential for backend developers and cloud engineers working with AWS DynamoDB to build scalable and fault-tolerant applications.
Progress0 / 4 steps
1
Create the list of book items to write
Create a variable called book_items that is a list containing these exact dictionaries: {'PutRequest': {'Item': {'BookId': {'S': 'B001'}, 'Title': {'S': 'Learn DynamoDB'}}}}, {'PutRequest': {'Item': {'BookId': {'S': 'B002'}, 'Title': {'S': 'Master AWS'}}}}, and {'PutRequest': {'Item': {'BookId': {'S': 'B003'}, 'Title': {'S': 'Cloud Basics'}}}}.
DynamoDB
Hint

Use a list with dictionaries exactly as shown for each book item.

2
Set the maximum retry count
Create a variable called max_retries and set it to 5 to limit the number of retry attempts for unprocessed items.
DynamoDB
Hint

Just assign the number 5 to max_retries.

3
Write the retry loop for batch write
Write a while loop that continues while book_items is not empty and max_retries is greater than 0. Inside the loop, call response = dynamodb.batch_write_item(RequestItems={'Books': book_items}). Then update book_items to response.get('UnprocessedItems', {}).get('Books', []). Decrease max_retries by 1 each loop.
DynamoDB
Hint

Use a while loop with the conditions and update book_items and max_retries inside.

4
Complete the batch write operation
Add a final check after the loop: if book_items is not empty, set a variable failed_items to book_items. Otherwise, set failed_items to an empty list [].
DynamoDB
Hint

Use an if-else statement to assign failed_items based on whether book_items is empty.

Practice

(1/5)
1. What does DynamoDB return when some items in a batch write are not processed immediately?
easy
A. An error stopping the entire batch operation
B. A partial success with no retry information
C. A success message without details
D. A list of unprocessed items to retry later

Solution

  1. Step 1: Understand batch write behavior

    DynamoDB may not process all items in a batch due to throttling or limits.

  2. Step 2: Identify returned data for unprocessed items

    It returns unprocessed items so the client can retry sending them.

  3. Final Answer:

    A list of unprocessed items to retry later -> Option D

  4. Quick Check:

    Unprocessed items = retry list [OK]
Hint: Unprocessed items mean retry those items later [OK]
Common Mistakes:
  • Thinking DynamoDB throws an error instead
  • Assuming all items are processed without feedback
  • Ignoring unprocessed items in code
2. Which of the following is the correct way to check for unprocessed items in a DynamoDB BatchWriteItem response in Python?
easy
A. if 'UnprocessedItems' in response and response['UnprocessedItems']:
B. if response['UnprocessedItems'] == None:
C. if response['UnprocessedItems'] is False:
D. if 'UnprocessedItems' not in response:

Solution

  1. Step 1: Understand response structure

    The response includes 'UnprocessedItems' key if any items were not processed.

  2. Step 2: Correctly check for unprocessed items

    Check if 'UnprocessedItems' exists and is not empty to retry those items.

  3. Final Answer:

    if 'UnprocessedItems' in response and response['UnprocessedItems']: -> Option A

  4. Quick Check:

    Check key exists and is not empty [OK]
Hint: Check key exists and is not empty to find unprocessed items [OK]
Common Mistakes:
  • Checking for None instead of empty dict
  • Using 'not in' which misses unprocessed items
  • Checking for False which is incorrect
3. Given this Python snippet handling DynamoDB batch write: 
response = client.batch_write_item(RequestItems=batch)
if response.get('UnprocessedItems'):
    retry_items = response['UnprocessedItems']
else:
    retry_items = None
print(retry_items)
What will be printed if all items were processed successfully?
medium
A. List of all items
B. {}
C. None
D. An error

Solution

  1. Step 1: Understand response when all items processed

    If all items are processed, 'UnprocessedItems' key is empty or missing.

  2. Step 2: Analyze code behavior

    response.get('UnprocessedItems') returns None or empty dict; if empty dict is falsy, else branch sets retry_items to None.

  3. Final Answer:

    None -> Option C

  4. Quick Check:

    No unprocessed items means retry_items = None [OK]
Hint: If no unprocessed items, retry_items is None [OK]
Common Mistakes:
  • Expecting empty dict instead of None
  • Assuming an error is raised
  • Thinking retry_items contains all items
4. You wrote this code to resend unprocessed items but it never stops retrying: 
while True:
    response = client.batch_write_item(RequestItems=items)
    items = response.get('UnprocessedItems', {})
    if not items:
        break
What is the likely bug causing infinite retries?
medium
A. Missing a delay between retries causing throttling
B. Using 'break' inside the loop incorrectly
C. Not updating 'items' with the new unprocessed items correctly
D. Not checking for empty dictionary properly

Solution

  1. Step 1: Analyze the retry loop

    The code updates items correctly but retries immediately without delay.

  2. Step 2: Identify the cause of infinite retries

    Missing delay or exponential backoff leads to rapid retries, causing persistent throttling. DynamoDB continually returns the same unprocessed items.

  3. Final Answer:

    Missing a delay between retries causing throttling -> Option A

  4. Quick Check:

    Add sleep/backoff between retries [OK]
Hint: Add delay or backoff between batch retries to avoid throttling [OK]
Common Mistakes:
  • Blaming item update logic instead of throttling
  • Assuming empty dict check prevents infinite loops
  • Overlooking need for backoff in tight retry loops
5. You want to ensure all items in a large batch are saved in DynamoDB without loss. Which approach best handles unprocessed items efficiently?
hard
A. Split items into single writes to avoid unprocessed items
B. Check for unprocessed items after each batch write and retry them until none remain
C. Send all items once and ignore unprocessed items since they are rare
D. Use batch write once and log unprocessed items without retrying

Solution

  1. Step 1: Understand batch write limitations

    DynamoDB batch writes can return unprocessed items due to throttling or limits.

  2. Step 2: Best practice for data safety

    Retry unprocessed items repeatedly until all are saved to avoid data loss.

  3. Final Answer:

    Check for unprocessed items after each batch write and retry them until none remain -> Option B

  4. Quick Check:

    Retry unprocessed items until empty for safe writes [OK]
Hint: Always retry unprocessed items until all are saved [OK]
Common Mistakes:
  • Ignoring unprocessed items causing data loss
  • Writing items one by one causing inefficiency
  • Logging without retrying unprocessed items
Recommended

Ready to prove it?

Pass the test and this pattern moves unknown strong while earning +1 Grip toward your certificate.

10 questions~5 mineasy hard