parquet-tools

Parquet-tools is a command-line tool used for working with Apache Parquet files, which is a columnar storage file format. It provides various functionalities to inspect, analyze, and manipulate Parquet files directly from the command line interface.

The tool allows you to view the metadata of a Parquet file, including the schema, compression type, and column statistics. It provides detailed information like number of rows, total file size, and relevant file metadata.

You can use parquet-tools to convert Parquet files to other formats such as CSV or JSON. This feature comes in handy when you want to convert the columnar storage format into a more readable and flexible format for further analysis.

The tool also allows you to execute interactive queries against Parquet files using a subset of the Apache Drill SQL syntax. You can filter, aggregate, and project specific columns of data right from the command line.

Parquet-tools supports data encryption and decryption operations on Parquet files to ensure data security. It provides options to encrypt and decrypt files using symmetric encryption algorithms.

The tool offers efficient memory handling, allowing you to work with large Parquet files without overwhelming your system's memory resources.

You can use parquet-tools to optimize Parquet files for better query performance. It supports operations like column pruning and predicate pushdown to reduce disk I/O and improve query execution time.

The tool provides options to compare two Parquet files and identify differences in schema, metadata, or data.

You can also use parquet-tools to merge multiple Parquet files into a single file, which can be useful for data consolidation or ETL (Extract, Transform, Load) processes.

Parquet-tools is written in Java and can be easily installed and run on Windows, macOS, and Linux systems. It requires Java Runtime Environment (JRE) to be installed on the system.

Overall, parquet-tools is a versatile and powerful command-line tool for working with Parquet files, providing a range of functionalities to inspect, manipulate, and optimize columnar storage data.