Google Cloud Professional Data Engineer Exam

If you experience a "hot key" error in your Dataflow logs, what should you do to improve performance?

1. Disable Dataflow shuffle.

2. Increase the data with the hot key.

3. Ensure that your data is evenly distributed.

4. Add more compute instances for processing.

The correct answer is: Ensure that your data is evenly distributed.

A "hot key" error indicates that a specific key (or a small number of keys) in your data is being accessed much more frequently than others, leading to imbalanced workload and potentially causing performance bottlenecks. To improve performance when this situation occurs, ensuring that your data is evenly distributed is essential. By achieving a more even distribution of data, you can minimize the likelihood that certain keys will become a bottleneck. This means that no single worker will be overwhelmed by an excessive amount of data or calls to a specific key, which allows the processing workload to be shared more evenly among all available resources. This approach helps in scaling the workload effectively and allows for more parallel processing, thereby improving overall performance and efficiency of your Dataflow job. Other options provided do not directly address the problem of uneven key distribution. For example, simply increasing the data with the hot key may worsen the situation, and disabling Dataflow shuffle can limit the ability to redistribute data effectively. Adding more compute instances might address performance but will not resolve the underlying issue of data imbalance. Therefore, ensuring even data distribution is the most effective strategy in this case.