Exam DP-203 topic 1 question 8 discussion

1. Merge Files 2. Parquet https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-performance-tuning-guidance

It should be 1)Merge Files - Question clearly says "initially ingested as 10 small json files". There is no hint on hierarchy or partition information. so clearly we need to merge these files for better performance 2) Parquet -> Always gives better performance for columnar based data

Copy Behavior → Merge Files Since there are 10 small JSON files, merging them into a single, optimized file will improve query performance. Azure Synapse Analytics serverless SQL pools perform better with fewer, larger files than many small files. Flatten hierarchy is not suitable since we are not restructuring directories. Preserve hierarchy is not needed because we want better query performance, not maintaining the folder structure. Sink File Type → Parquet Parquet is an efficient columnar format, designed for fast analytical queries. It supports schema inference, which is required for querying in Synapse serverless SQL pools. CSV and JSON are not optimal because they do not support columnar storage and would result in slower queries. TXT is not structured and would not allow schema inference. Thus, the best selections are "Merge files" for Copy behavior and "Parquet" for Sink file type to achieve the fastest query times

Azure Synapse serverless SQL pools perform best with fewer, larger files in Parquet format - so 1-Merge Files 2- Parquet

Q says "You need to move the files to a different folder". so preserve for sure

1. Copy Behavior: merge files 2. Sink file type: Paquet

1. Preserve Hierarchy 2. Parquet Since Merge Files behavior combines multiple files into a single output file. While this can be useful for reducing the number of files, it may introduce additional performance overhead due to the merging process. Since it ask to provide the fastest possible query time.

This question is somewhat confusing. The detail states "Each file contains the same data attributes and data from a subsidiary of your company". There is a possibility that each file is for a different subsidiary and would be stored in a different hierarchical folder, so the requirement to "preserve hierarchy" could be the right answer here.

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https://learn.microsoft.com/en-us/azure/data-factory/connector-file-system?tabs=data-factory

1. Flatten hierarchy - Performance: Fastest; Schema inference: Straightforward; 2. Parquet

Merge Files: This option combines the 10 JSON files into a single Parquet file, reducing overhead and improving query performance significantly. Parquet: This columnar format is optimized for fast queries, especially when dealing with large datasets and selective column reads. It also supports compression and schema inference.

My answer : Merge Since there is no mention of preserving the hierarchy, and the need is to make the process more efficient, merge is the way to go.

MERGE FILES since you need to make transformation and data have the same attributes PARQUET because is the most effcient file format

- Merge - Parquet

ChatGPT confirms it's 1. Merge, 2. Parquet

1. Merge Files 2. Parquet https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-performance-tuning-guidance