Unprocessed items handling in DynamoDB - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ query_result

intermediate

What is the output when BatchWriteItem returns unprocessed items?

You send a BatchWriteItem request to DynamoDB with 5 items. The response contains 2 unprocessed items. What does this mean?

A All 5 items were written successfully.

B 2 items were not written and need to be retried.

C The request failed and no items were written.

D Only 3 items were sent to DynamoDB.

💡 Hint

Unprocessed items are those DynamoDB could not write due to capacity limits.

When BatchWriteItem returns unprocessed items, it means those items were not saved and should be retried.

🧠 Conceptual

intermediate

Why does DynamoDB return unprocessed items in BatchWriteItem?

Which of the following is the main reason DynamoDB returns unprocessed items in a BatchWriteItem response?

A Because DynamoDB exceeded provisioned throughput limits.

B Because the request syntax was invalid.

C Because the items were duplicates.

D Because the table does not exist.

💡 Hint

Think about capacity and limits on writes per second.

DynamoDB returns unprocessed items when the write capacity is exceeded, so it cannot process all items immediately.

📝 Syntax

advanced

Which code snippet correctly retries unprocessed items in BatchWriteItem?

Given a BatchWriteItem response with unprocessed items, which code snippet correctly retries them until all are processed?

A

while response['UnprocessedItems'] is None:
    response = client.batch_write_item(RequestItems=response['UnprocessedItems'])

B

if response['UnprocessedItems']:
    client.batch_write_item(RequestItems=response['UnprocessedItems'])

C

for item in response['UnprocessedItems']:
    client.batch_write_item(RequestItems=item)

D

while 'UnprocessedItems' in response and response['UnprocessedItems']:
    response = client.batch_write_item(RequestItems=response['UnprocessedItems'])

💡 Hint

Retry while unprocessed items exist.

Option D loops while unprocessed items exist, retrying the batch write with those items.

❓ optimization

advanced

How to optimize handling of unprocessed items in BatchWriteItem?

Which approach best optimizes handling unprocessed items returned by BatchWriteItem to avoid throttling?

A Use exponential backoff with jitter when retrying unprocessed items.

B Immediately retry all unprocessed items in a tight loop without delay.

C Ignore unprocessed items and proceed without retrying.

D Split unprocessed items into single-item requests and retry sequentially.

💡 Hint

Think about how to reduce load and avoid repeated throttling.

Exponential backoff with jitter helps spread retries over time, reducing throttling and improving success.

🔧 Debug

expert

Why does this retry code cause infinite loop on unprocessed items?

Consider this Python code snippet retrying unprocessed items from BatchWriteItem:

while response['UnprocessedItems']:
    response = client.batch_write_item(RequestItems=response['UnprocessedItems'])

Why might this cause an infinite loop?

DynamoDB

while response['UnprocessedItems']:
    response = client.batch_write_item(RequestItems=response['UnprocessedItems'])

A Because the loop condition should check for None, not empty dict.

B Because 'UnprocessedItems' key is missing from response, causing KeyError.

C Because it retries immediately without delay, causing repeated throttling and unprocessed items never clear.

D Because batch_write_item does not accept 'RequestItems' parameter.

💡 Hint

Think about what happens if you retry too fast.

Retrying immediately without delay can cause repeated throttling, so unprocessed items remain and loop never ends.