Parquet is a columnar storage file format designed for efficiency with big data processing frameworks like Apache Hadoop and Spark.
Technical Details
Parquet organizes data by columns rather than rows, which enables better compression and more efficient queries for analytical workloads. It supports nested data structures and is optimized for handling complex data.
Advantages
- Highly efficient columnar storage and compression
- Excellent query performance for analytical workloads
- Support for nested data structures
- Schema evolution capabilities
Limitations
- Not human-readable like CSV or JSON
- Less suitable for row-oriented operations
- Requires specialized tools for viewing and editing
- More complex than simpler formats