Exam AWS Certified Data Engineer - Associate DEA-C01 topic 1 question 29 discussion

Clearly is mapping state

The Map state allows you to define a single execution path for processing a collection of data items in parallel. This aligns perfectly with the data engineer's requirement of parallel processing a large collection of data files

to execute in parallel

C is Correct To meet the requirement of parallel processing a large collection of data files and applying a specific transformation to each file, the data engineer should use the Map state in AWS Step Functions. The Map state is specifically designed to run a set of tasks in parallel for each element in a collection or array. Each element (in this case, each data file) is processed independently and in parallel, allowing the workflow to take advantage of parallel processing.

C, Map state is correct

With Step Functions, you can orchestrate large-scale parallel workloads to perform tasks, such as on-demand processing of semi-structured data. These parallel workloads let you concurrently process large-scale data sources stored in Amazon S3. For example, you might process a single JSON or CSV file that contains large amounts of data. Or you might process a large set of Amazon S3 objects. To set up a large-scale parallel workload in your workflows, include a Map state in Distributed mode.

C is correct. Map state is designed precisely for the requirement described. It allows you to iterate over a collection of items, processing each item individually. The Map state can automatically manage the iteration and execute the specified transformation on each item in parallel, making it the perfect choice for parallel processing of a large collection of data files.

The Map state is specifically designed for processing a collection of items (like data files) in parallel. It allows you to apply a transformation or a set of steps to each item in the input array independently. The Map state automatically iterates over each item in the array and performs the defined steps. This makes it ideal for scenarios where you need to process a large number of files in a similar manner, as in your requirement.