DynamoDB: Hot Partitions and Throttling

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Questions and Answers

Which strategy is LEAST effective in mitigating throttling issues caused by hot partitions in a database?

Employing adaptive capacity to automatically rebalance throughput across partitions.
Using DAX to cache frequently accessed data, reducing load on the table.
Consistently writing all new data to a single, designated 'hot' partition to streamline operations. (correct)
Implementing exponential backoff in the application's retry logic.

A table is experiencing intermittent throttling despite having provisioned throughput. Which combination of factors is MOST likely contributing to this issue?

Uneven data distribution with poorly designed partition keys and traffic spikes. (correct)
Consistent read requests and disabled adaptive capacity.
Low request rates with enabled burst capacity.
Uniform data access patterns and well-distributed partition keys.

An application using a database experiences a surge in traffic. How does burst capacity help maintain performance during this surge?

By immediately rejecting excess requests to prevent system overload.
By automatically redistributing data across partitions to prevent hot spots.
By permanently increasing the provisioned throughput of the table.
By utilizing saved, unused capacity to accommodate short spikes for up to 5 minutes. (correct)

Why is it important to monitor throughput using CloudWatch within a database environment?

<p>To proactively identify and address potential throttling issues before they impact application performance. (B)</p> Signup and view all the answers

What is the primary benefit of adaptive capacity in a database system?

<p>It automatically balances throughput across partitions to mitigate hot partition issues. (C)</p> Signup and view all the answers

Flashcards

HOT Partition

A partition receiving a disproportionately high volume of read/write requests.

Throttling

Occurs when requests exceed table/index throughput limits, leading to higher latencies or request failures.

Even Data Distribution

Use well-designed partition keys to distribute data evenly.

Exponential Backoff

Retry logic that waits before resending a request after it has been denied to avoid throttling.

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Burst Capacity

Allows tables to handle short traffic spikes using saved, unused capacity for up to 5 minutes.

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Study Notes

Performance optimization focuses on preventing disproportionately high read or write requests to certain partitions.

Hot Partitions

Hot partitions occur when some partitions get a disproportionately high volume of requests.
Uneven data distribution leads to overloaded partitions.
Hot partitions are often caused by poorly chosen partition keys.

Throttling

Throttling occurs when requests exceed table or index throughput limits.
Higher latencies or request failures result from throttling.

Best Practices to Avoid Throttling

Use well-designed partition keys to ensure even data distribution.
Employ exponential backoff in retry logic after a request has been denied.
Monitor throughput using CloudWatch.
Implement DAX to cache reads and reduce table load.

Burst Capacity

Burst capacity allows tables to handle short traffic spikes without throttling.
Unused capacity is saved and can be used for up to 5 minutes.

Adaptive Capacity

Adaptive capacity automatically balances throughput across partitions.
It helps maintain performance, but key design remains important to avoid hot partitions.

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Description

Learn about hot partitions and throttling issues in DynamoDB, including causes such as uneven data distribution and poorly chosen partition keys. Explore best practices like using well-designed partition keys, exponential backoff, CloudWatch monitoring, and DAX caching. Discover how burst and adaptive capacity can help manage traffic spikes.