What should you recommend?

You are designing an Azure Data Lake Storage solution that will transform raw JSON files for use in an analytical workload.

You need to recommend a format for the transformed files.

The solution must meet the following requirements:

✑ Contain information about the data types of each column in the files.

✑ Support querying a subset of columns in the files.

✑ Support read-heavy analytical workloads.

✑ Minimize the file size.

What should you recommend?
A . JSON
B. CSV
C. Apache Avro
D. Apache Parquet

Answer: D

Explanation:

Parquet, an open-source file format for Hadoop, stores nested data structures in a flat columnar format.

Compared to a traditional approach where data is stored in a row-oriented approach,

Parquet file format is more efficient in terms of storage and performance.

It is especially good for queries that read particular columns from a “wide” (with many columns) table since only needed columns are read, and IO is minimized.

Reference: https://www.clairvoyant.ai/blog/big-data-file-formats