Batch limits and retries in DynamoDB - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the maximum number of items you can write in a single DynamoDB batch write operation?

You can write up to 25 items in a single batch write operation in DynamoDB.

intermediate

Why does DynamoDB batch write sometimes return unprocessed items?

DynamoDB may return unprocessed items when the request exceeds throughput limits or internal errors occur. These items need to be retried.

intermediate

How should you handle unprocessed items returned from a DynamoDB batch write?

You should retry the unprocessed items with exponential backoff until all items are successfully written.

beginner

What is the maximum number of items you can read in a single DynamoDB batch get operation?

You can read up to 100 items in a single batch get operation in DynamoDB.

beginner

Explain why batch operations in DynamoDB are more efficient than individual requests.

Batch operations reduce the number of network calls by grouping multiple requests, which lowers latency and improves throughput.

What is the maximum number of items allowed in a DynamoDB batch write request?

A 25

B 50

C 100

D 10

DynamoDB batch write supports up to 25 items per request.

If a batch write returns unprocessed items, what should you do?

A Ignore them

B Retry them with exponential backoff

C Retry them immediately without delay

D Delete the unprocessed items

Unprocessed items should be retried with exponential backoff to avoid overwhelming the service.

What is the maximum number of items you can request in a DynamoDB batch get operation?

A 200

B 50

C 25

D 100

Batch get operations can request up to 100 items at once.

Why might DynamoDB return unprocessed items in batch operations?

A Because the items are invalid

B Because the table is deleted

C Due to exceeding provisioned throughput or internal throttling

D Because the items are duplicates

Unprocessed items usually happen when throughput limits are exceeded or throttling occurs.

Which of the following is a benefit of using batch operations in DynamoDB?

A They reduce the number of network calls

B They guarantee transaction atomicity

C They increase item size limits

D They automatically retry failed requests

Batch operations reduce network calls by grouping multiple requests.

Describe the limits and retry strategy for DynamoDB batch write operations.

Think about how many items you can send at once and what to do if some fail.

Explain why batch operations are useful in DynamoDB and how to handle failures.

Consider efficiency and error handling.

Practice

1. What is the main reason DynamoDB enforces batch limits when using batch write operations?

easy

A. To allow unlimited retries automatically

B. To increase the size of each item stored

C. To prevent sending too many items at once and avoid throttling

D. To reduce the number of tables in the database

Solution

1. Step 1: Understand batch write limits

   DynamoDB limits batch write operations to a maximum of 25 items per request to avoid overloading the service.

2. Step 2: Reason about the purpose of limits

   These limits help prevent throttling and ensure stable performance by controlling request size.

3. Final Answer:

   To prevent sending too many items at once and avoid throttling -> Option C

4. Quick Check:

   Batch limits = prevent throttling [OK]

Hint: Batch limits protect DynamoDB from overloads [OK]

Common Mistakes:

• Thinking batch limits increase item size
• Assuming retries are automatic without checks
• Confusing batch limits with table count

2. Which of the following is the correct maximum number of items you can send in a single BatchWriteItem request in DynamoDB?

easy

A. 25 items

B. 50 items

C. 100 items

D. 10 items

Solution

1. Step 1: Recall DynamoDB batch write limits

   DynamoDB allows a maximum of 25 items per BatchWriteItem request.

2. Step 2: Compare options with the limit

   Only 25 items matches the correct limit of 25 items.

3. Final Answer:

   25 items -> Option A

4. Quick Check:

   BatchWriteItem max = 25 items [OK]

Hint: Remember 25 items max per batch write [OK]

Common Mistakes:

• Choosing 50 or 100 items which exceed the limit
• Confusing batch write with batch get limits
• Assuming 10 items is the max without checking docs

3. Consider this Python snippet using boto3 DynamoDB client:

response = client.batch_write_item(RequestItems={
  'MyTable': [
    {'PutRequest': {'Item': {'ID': {'S': '1'}}}},
    {'PutRequest': {'Item': {'ID': {'S': '2'}}}}
  ]
})
print(response.get('UnprocessedItems'))

If the response prints {}, what does it mean?

medium

A. The batch write failed completely

B. The request exceeded batch limits

C. Only the first item was processed

D. All items were processed successfully with no retries needed

Solution

1. Step 1: Understand UnprocessedItems meaning

   The UnprocessedItems key contains items that DynamoDB did not process and need retrying.

2. Step 2: Interpret empty dictionary response

   An empty dictionary {} means no unprocessed items, so all were processed successfully.

3. Final Answer:

   All items were processed successfully with no retries needed -> Option D

4. Quick Check:

   Empty UnprocessedItems = all processed [OK]

Hint: Empty UnprocessedItems means success [OK]

Common Mistakes:

• Assuming empty means failure
• Thinking only partial items processed
• Confusing batch limits with processing status

4. You wrote code to batch write 30 items to DynamoDB but got an error. Which fix will solve the problem?

medium

A. Split the 30 items into two batches of 25 and 5 items

B. Send all 30 items in one batch and increase timeout

C. Use batch get instead of batch write

D. Reduce each item size to half

Solution

1. Step 1: Identify batch write limit violation

   DynamoDB batch write limits max 25 items per request, so 30 items exceed this limit.

2. Step 2: Apply correct fix by splitting batches

   Splitting into two batches (25 and 5) respects the limit and avoids errors.

3. Final Answer:

   Split the 30 items into two batches of 25 and 5 items -> Option A

4. Quick Check:

   Split batches to respect 25 item limit [OK]

Hint: Split batches over 25 items to fix errors [OK]

Common Mistakes:

• Trying to send all items at once ignoring limits
• Using batch get which is for reads, not writes
• Reducing item size does not fix batch count limit

5. You have a batch write operation that returns some unprocessed items due to throttling. What is the best approach to ensure all items are eventually written?

hard

A. Retry the entire batch including processed items

B. Immediately retry only the unprocessed items with exponential backoff

C. Ignore unprocessed items and assume they are saved

D. Increase the batch size to include more items

Solution

1. Step 1: Understand unprocessed items cause

   Unprocessed items occur when DynamoDB throttles requests; these items need retrying.

2. Step 2: Apply best retry strategy

   Retry only unprocessed items with exponential backoff to avoid repeated throttling and ensure eventual success.

3. Final Answer:

   Immediately retry only the unprocessed items with exponential backoff -> Option B

4. Quick Check:

   Retry unprocessed items with backoff [OK]

Hint: Retry unprocessed items with backoff, not whole batch [OK]

Common Mistakes:

• Ignoring unprocessed items causing data loss
• Retrying entire batch wastes resources
• Increasing batch size worsens throttling