Azure Data Scientists Associate Practice Exam

In batch processing, which choice is best for continuously adding results to a singular output?

1. concat_files

2. summary_only

3. append_row

4. overwrite_output

The correct answer is: append_row

The choice of appending rows is ideal for continuously adding results to a singular output in batch processing. This method allows new data entries to be added to an existing dataset without altering or replacing the previously collected data. As data grows over time, using this approach ensures that all historical information remains intact, and new results are seamlessly integrated into the output file. In the context of batch processing, when results from different data batches are generated, appending rows enables users to build a comprehensive data set that reflects all past computations and analyses. This is particularly useful in scenarios like data aggregation, analysis, or reporting where maintaining a complete history is crucial. Other choices like overwriting output would replace existing data, negating the benefits of retaining previous information. Summary only would provide a high-level overview but not the granularity of data entry needed for continuous results. Concatenating files could imply more complex merging processes that do not directly support continuous additions in a straightforward manner. Therefore, appending rows stands out as the most effective choice for maintaining a growing dataset with a consistent output structure.