Data I/O is an open source project that provides a flexible and scalable framework for data input and output operations in Spark applications. It offers a set of powerful tools and abstractions to simplify and streamline data processing pipelines.
- Easy-to-use API for defining data processors and transformations
- Seamless integration with popular data storage systems and formats
- Support for batch and streaming data processing
- Extensible architecture for custom data processors and pipelines
- Scalable and fault-tolerant processing using Apache Spark
To get started with Data I/O, please refer to the documentation for installation instructions, usage examples, and API references.
Comprehensive documentation for Data I/O can be found at the Data I/O documentation website. The documentation provides detailed information on installation, usage, and configuration of the framework. It also includes examples and guides to help you get started with building data processing pipelines using Data I/O.
If you encounter any issues or require support, please create a new issue on the GitHub repository.
Contributions to Data I/O are welcome! To contribute, please follow the guidelines outlined in our contribution guide.
This project is licensed under the Apache License 2.0 license. See the LICENSE file for more information.