How the .parquet format works
The .parquet file format is a columnar storage format optimized for large volumes of data, designed to provide efficient reading and effective compression.
1. Columnar Structure
- Columnar Storage: Unlike traditional file formats that store data in rows, Parquet stores data in columns. This allows for better compression and efficient reading, especially for queries that access only a few columns of a table.
2. Compression and Encoding
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Compression: Parquet supports several compression techniques, such as Snappy, GZIP, and LZO. Columnar compression is more efficient because similar data is grouped together, resulting in a better compression ratio.
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Encoding: In addition to compression, Parquet uses encoding techniques (such as run-length encoding) to reduce storage space.
3. Metadata
- Metadata: Each Parquet file includes metadata that contains information about the schema of the data, the distribution of data across columns, and statistics about the stored values. This allows query engines to perform optimizations without having to read the entire file.
4. Rigid Schema
- Schema Definition: The schema of the data is rigidly defined and stored along with the data. This ensures that any Parquet reader can understand and process the data correctly.
5. Support for Complex Data Types
- Data Types: Parquet supports a wide variety of data types, including primitive types (such as integers and strings) and complex types (such as lists and nested structures).
6. Optimization for Analytical Queries
- Performance: Because of its columnar storage and metadata structure, Parquet is highly optimized for analytical queries that scan large volumes of data but often access only a subset of columns.
Benefits
- Storage Efficiency: Reduces the storage space required thanks to effective compression.
- Read Speed: Queries are faster since only the necessary columns are read.
- Scalability: Ideal for large data sets due to its optimized structure.