Implementing Best Practices for DynamoDB

Answer - B.

When you scan your table in Amazon DynamoDB, you should follow the DynamoDB best practices for avoiding sudden bursts of read activity.

You can use the following technique to minimize the impact of a scan on a table's provisioned throughput.

Reduce page size.

Because a Scan operation reads an entire page (by default, 1 MB), you can reduce the scan operation's impact by setting a smaller page size.

The Scan operation provides a Limit parameter that you can use to set the page size for your request.

Each Query or Scan request with a smaller page size uses fewer read operations and creates a "pause" between each request.

For example, suppose that, each item is 4 KB, and you set the page size to 40 items.

A Query request would then consume only 20 eventually consistent read operations or 40 strongly consistent read operations.

A larger number of smaller Query or Scan operations would allow your other critical requests to succeed without throttling.

Option A is incorrect because the page size should be reduced rather than enlarged.

Option C is incorrect because a parallel scan with many workers can easily consume all of the provisioned read capacity.

Option D is incorrect because the sequential scan processes data sequentially.

It does not help to avoid the throttling errors.

For more information, please check below AWS Docs-

https://aws.amazon.com/blogs/developer/rate-limited-scans-in-amazon-dynamodb/ https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/bp-query-scan.html

The correct answer is C. Parallel Scans.

Explanation:

DynamoDB is a NoSQL database that can handle large datasets and provide consistent, low-latency performance. However, when the size of the table grows beyond a certain point, scans on the table can cause throttling errors.

To understand how to solve the problem, we need to know how DynamoDB scans work. DynamoDB scans operate on partitions, which are the basic unit of data distribution in DynamoDB. Each partition contains a subset of the table's data. When a scan is performed, DynamoDB reads all the items in a partition sequentially until it has scanned all the items in the partition.

So, what can cause throttling errors? DynamoDB provides a certain level of read and write capacity for each table or partition. If the scan operation consumes more capacity than is available, DynamoDB will throttle the operation. Throttling can cause delays in accessing data and can affect the performance of the application.

Now, let's look at the answer options:

A. Large Page size: This option is not relevant to the problem. Page size is a parameter that determines how many items DynamoDB reads at a time during a scan operation. Increasing page size can reduce the number of requests needed to scan a table, but it will not solve the throttling problem.

B. Reduced page size: This option is also not relevant. As mentioned above, reducing page size can increase the number of requests needed to scan a table, which can actually make the throttling problem worse.

C. Parallel Scans: This option is the correct answer. Parallel scans involve dividing the table into multiple partitions and scanning them simultaneously. This allows for more efficient use of read capacity and can reduce the chance of throttling errors. Parallel scans can be implemented by using multiple threads in the application or by using the parallel scan feature in the AWS SDK.

D. Sequential scans: This option is not recommended. As mentioned earlier, DynamoDB scans operate on partitions, and scanning a partition sequentially can consume a lot of read capacity. Sequential scans can cause throttling errors and should be avoided whenever possible.

In conclusion, the correct answer is C. Parallel Scans. This will help avoid throttling errors by distributing the read capacity across multiple partitions, allowing for more efficient use of DynamoDB resources.