This is a regular “data quiz”. Follow it on LinkedIn. Test your knowledge or learn something new.
Today Question:
Which format is most efficient for big data processing?
A) CSV
B) JSON
C) Parquet
D) XML
Correct Answer: C
Explanation
Apache Parquet is a columnar storage format designed specifically for analytical workloads and big data processing. Unlike row-based formats such as CSV, Parquet stores data by columns, which enables highly efficient compression and fast reading of specific columns without loading entire records. The format supports advanced compression algorithms such as Snappy, GZIP, LZO, and BROTLI, significantly reducing file sizes. Parquet has native support for complex data types including nested structures, arrays, and maps, making it ideal for modern analytical applications. Predicate pushdown and column pruning enable efficient filtering directly at the storage level. Parquet is widely supported in the Hadoop ecosystem (Spark, Hive, Impala) and cloud platforms (AWS, GCP, Azure). Its benefits are greatest in OLAP workloads, where queries often access only subsets of columns from large tables, making it the standard choice for data lakes and analytical systems.