Error handling and retries in DynamoDB

Introduction

Error handling and retries help your program keep working even when something goes wrong with the database. It makes your app more reliable and user-friendly.

When your app tries to save data but the network is slow or unstable.

When you read data but the database temporarily refuses the request.

When you update records but there is a conflict or timeout.

When you want to avoid losing data due to temporary errors.

When you want to give your app a chance to fix small problems automatically.

Syntax

DynamoDB

try {
  // Your DynamoDB operation here
} catch (error) {
  if (shouldRetry(error)) {
    // Retry the operation
  } else {
    // Handle the error (log, alert, etc.)
  }
}

function shouldRetry(error) {
  // Check error type or code to decide if retry is needed
  return error.name === 'ProvisionedThroughputExceededException';
}

Use try-catch blocks to catch errors from DynamoDB operations.

Decide to retry only for temporary errors like throttling or timeouts.

Examples

This example retries only when DynamoDB says you sent too many requests.

DynamoDB

try {
  const result = await dynamoDbClient.get(params).promise();
  console.log('Data:', result.Item);
} catch (error) {
  if (error.name === 'ProvisionedThroughputExceededException') {
    console.log('Too many requests, retrying...');
    // retry logic here
  } else {
    console.error('Error:', error.message);
  }
}

This example handles throttling errors during data saving.

DynamoDB

try {
  await dynamoDbClient.put(params).promise();
  console.log('Data saved');
} catch (error) {
  if (error.name === 'ProvisionedThroughputExceededException') {
    console.log('Request throttled, retrying...');
    // retry logic here
  } else {
    console.error('Failed to save data:', error.message);
  }
}

This example does not retry for unknown errors to avoid infinite loops.

DynamoDB

try {
  const result = await dynamoDbClient.update(params).promise();
  console.log('Update successful');
} catch (error) {
  console.error('Update failed:', error.message);
  // No retry for unknown errors
}

Sample Program

This program tries to get an item from DynamoDB. If it gets a throttling error, it waits and retries up to 3 times. It prints messages to show what is happening.

DynamoDB

import { DynamoDBClient, GetItemCommand } from '@aws-sdk/client-dynamodb';

const dynamoDbClient = new DynamoDBClient({ region: 'us-east-1' });

async function getItemWithRetry(params, maxRetries = 3) {
  let attempt = 0;
  while (attempt < maxRetries) {
    try {
      const command = new GetItemCommand(params);
      const result = await dynamoDbClient.send(command);
      return result.Item;
    } catch (error) {
      if (error.name === 'ProvisionedThroughputExceededException') {
        attempt++;
        console.log(`Attempt ${attempt} failed due to throttling. Retrying...`);
        await new Promise(resolve => setTimeout(resolve, 1000 * attempt));
      } else {
        console.error('Non-retryable error:', error.message);
        throw error;
      }
    }
  }
  throw new Error('Max retries reached. Could not get item.');
}

(async () => {
  const params = {
    TableName: 'MyTable',
    Key: {
      'Id': { S: '123' }
    }
  };

  try {
    console.log('Trying to get item...');
    const item = await getItemWithRetry(params);
    console.log('Item received:', item);
  } catch (error) {
    console.error('Failed to get item:', error.message);
  }
})();

Important Notes

Retrying helps handle temporary errors but too many retries can slow your app.

Use exponential backoff (waiting longer between retries) to be polite to the database.

Always limit retries to avoid infinite loops.

Summary

Error handling keeps your app stable when problems happen.

Retries let your app try again after temporary errors like throttling.

Use try-catch and check error codes to decide when to retry.

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