Error handling and retries in DynamoDB - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to catch a DynamoDB exception.

DynamoDB

try {
  // some DynamoDB operation
} catch ([1] e) {
  console.log('Error:', e.message);
}

Drag options to blanks, or click blank then click option'

AError

BException

CDynamoDBError

DDynamoDBException

Attempts:

3 left

💡 Hint

Common Mistakes

Using a non-existent error class like DynamoDBException.

Using Exception which is not a JavaScript error type.

The standard error type to catch exceptions in JavaScript is Error. DynamoDB client errors are instances of Error.

2fill in blank

medium

Complete the code to retry a DynamoDB operation after catching a throttling error.

DynamoDB

if (error.code === [1]) {
  // retry logic here
}

Drag options to blanks, or click blank then click option'

A"InternalServerError"

B"ProvisionedThroughputExceededException"

C"ResourceNotFoundException"

D"ThrottlingException"

Attempts:

3 left

💡 Hint

Common Mistakes

Using ProvisionedThroughputExceededException which is older and less common.

Using unrelated error codes like ResourceNotFoundException.

The error code ThrottlingException indicates the request was throttled and can be retried.

3fill in blank

hard

Fix the error in the retry logic to wait before retrying.

DynamoDB

async function retryOperation() {
  try {
    await dynamoDbClient.send(command);
  } catch (error) {
    if (error.code === 'ThrottlingException') {
      await new Promise(resolve => setTimeout([1]));
      return retryOperation();
    }
    throw error;
  }
}

Drag options to blanks, or click blank then click option'

A() => resolve(), 1000

Bresolve, 1000

C() => resolve(), 1000)

Attempts:

3 left

💡 Hint

Common Mistakes

Passing resolve directly without wrapping in a function.

Missing parentheses or commas in setTimeout arguments.

The setTimeout function expects a callback and a delay in milliseconds. The correct syntax is setTimeout(() => resolve(), 1000).

4fill in blank

hard

Fill both blanks to implement exponential backoff in retry delay.

DynamoDB

async function retryWithBackoff(attempt) {
  try {
    await dynamoDbClient.send(command);
  } catch (error) {
    if (error.code === 'ThrottlingException' && attempt < 5) {
      const delay = [1] * Math.pow(2, [2]);
      await new Promise(resolve => setTimeout(() => resolve(), delay));
      return retryWithBackoff(attempt + 1);
    }
    throw error;
  }
}

Drag options to blanks, or click blank then click option'

A100

Battempt

C1000

Dattempt - 1

Attempts:

3 left

💡 Hint

Common Mistakes

Using too large base delay causing long waits.

Using attempt - 1 which delays less on retries.

Exponential backoff uses a base delay (e.g., 100 ms) multiplied by 2 to the power of the attempt number.

5fill in blank

hard

Fill all three blanks to log error details and retry with a max attempt limit.

DynamoDB

async function safeRetry(attempt) {
  try {
    await dynamoDbClient.send(command);
  } catch (error) {
    console.error('Error code:', [1]);
    console.error('Error message:', [2]);
    if (error.code === 'ThrottlingException' && [3] < 3) {
      await new Promise(resolve => setTimeout(() => resolve(), 200));
      return safeRetry(attempt + 1);
    }
    throw error;
  }
}

Drag options to blanks, or click blank then click option'

Aerror.code

Berror.message

Cattempt

Derror.statusCode

Attempts:

3 left

💡 Hint

Common Mistakes

Logging wrong error properties like statusCode.

Using a wrong variable for retry count.

Use error.code and error.message to log error details. The retry limit is controlled by the attempt variable.

Practice

1. What is the main purpose of using retries in DynamoDB error handling?

easy

A. To ignore all errors and continue processing

B. To permanently stop the operation when an error occurs

C. To automatically try the operation again after a temporary failure

D. To delete the data causing the error

Solution

1. Step 1: Understand retries in DynamoDB

   Retries are used to handle temporary errors like throttling by trying the operation again.

2. Step 2: Identify the purpose of retries

   Retries help keep the app stable by not failing immediately on temporary issues.

3. Final Answer:

   To automatically try the operation again after a temporary failure -> Option C

4. Quick Check:

   Retries = automatic retry after temporary failure [OK]

Hint: Retries mean trying again after temporary errors [OK]

Common Mistakes:

• Thinking retries stop all errors permanently
• Ignoring the need to check error types before retrying
• Assuming retries delete data

2. Which of the following is the correct way to catch a throttling exception in DynamoDB using Python?

easy

A. try:
# operation
except ThrottlingException:
# retry logic

B. try:
# operation
except Exception:
pass

C. if error == 'ThrottlingException':
retry()

D. catch ThrottlingException {
retry();
}

Solution

1. Step 1: Identify Python error handling syntax

   Python uses try-except blocks to catch exceptions, with except specifying the exception type.

2. Step 2: Match correct exception handling for throttling

   try: # operation except ThrottlingException: # retry logic correctly uses try-except with ThrottlingException to handle retries.

3. Final Answer:

   try: # operation except ThrottlingException: # retry logic -> Option A

4. Quick Check:

   Python try-except with specific exception = try: # operation except ThrottlingException: # retry logic [OK]

Hint: Python uses try-except to catch specific exceptions [OK]

Common Mistakes:

• Using incorrect syntax like catch instead of except
• Catching all exceptions without handling specific ones
• Using if statement instead of try-except for exceptions

3. Given this Python code snippet for DynamoDB, what will be the output if a throttling error occurs on the first attempt?

import boto3
from botocore.exceptions import ClientError

client = boto3.client('dynamodb')

try:
    response = client.put_item(TableName='MyTable', Item={'id': {'S': '123'}})
    print('Success')
except ClientError as e:
    if e.response['Error']['Code'] == 'ThrottlingException':
        print('Retrying...')
    else:
        print('Failed')

medium

A. Success

B. Retrying...

C. Failed

D. No output

Solution

1. Step 1: Understand the try-except block behavior

   If a ClientError occurs, the code checks the error code inside the except block.

2. Step 2: Check error code for throttling

   If the error code is 'ThrottlingException', it prints 'Retrying...'. Otherwise, it prints 'Failed'.

3. Final Answer:

   Retrying... -> Option B

4. Quick Check:

   Error code 'ThrottlingException' triggers 'Retrying...' [OK]

Hint: Check error code in except to decide output [OK]

Common Mistakes:

• Assuming success despite error
• Ignoring error code check and printing 'Failed'
• Expecting no output on error

4. Identify the error in this retry logic snippet for DynamoDB in Python:

try:
    response = client.get_item(TableName='MyTable', Key={'id': {'S': '123'}})
except ClientError as e:
    if e.response['Error']['Code'] == 'ThrottlingException':
        client.get_item(TableName='MyTable', Key={'id': {'S': '123'}})
    else:
        raise e

medium

A. No error, code retries correctly

B. Should not raise exception in else block

C. Error code check is incorrect

D. Retry call is not inside a try-except block

Solution

1. Step 1: Analyze retry call placement

   The retry call is made without a try-except block, so if it fails again, it will raise an unhandled exception.

2. Step 2: Understand proper retry handling

   Retries should be wrapped in try-except to handle repeated failures gracefully.

3. Final Answer:

   Retry call is not inside a try-except block -> Option D

4. Quick Check:

   Retry without try-except risks unhandled errors [OK]

Hint: Always wrap retries in try-except to catch repeated errors [OK]

Common Mistakes:

• Not wrapping retry calls in error handling
• Mischecking error codes
• Avoiding raising exceptions on unknown errors

5. You want to implement a retry mechanism for DynamoDB writes that retries up to 3 times with exponential backoff when a throttling error occurs. Which approach correctly combines error handling and retries?

hard

A. Use a loop with try-except catching throttling errors, sleep doubling wait time each retry, stop after 3 attempts

B. Call put_item once, then retry infinitely without delay on any error

C. Ignore errors and assume writes always succeed

D. Use try-except but do not check error codes before retrying

Solution

1. Step 1: Understand retry with exponential backoff

   Retries should be limited in number and wait time should increase to reduce load.

2. Step 2: Combine error handling and retry logic

   Use a loop with try-except to catch throttling errors, sleep with increasing delay, and stop after max retries.

3. Final Answer:

   Use a loop with try-except catching throttling errors, sleep doubling wait time each retry, stop after 3 attempts -> Option A

4. Quick Check:

   Retry loop + exponential backoff + error check = Use a loop with try-except catching throttling errors, sleep doubling wait time each retry, stop after 3 attempts [OK]

Hint: Retry with limited attempts and increasing delay on throttling [OK]

Common Mistakes:

• Retrying infinitely without delay
• Not checking error codes before retrying
• Ignoring errors completely