Hardwood Promises High-Speed JVM Apache Parquet Processing with Zero Mandatory Dependencies
Hardwood, the project Gunnar Morling kick-started handling of Parquet files in Java, reached version 1. Its multi-threaded approach and zero mandatory external dependencies promise a simpler, more efficient alternative to the Apache Parquet Java implementation. For now, the library supports just reading; writing support is expected in the upcoming versions. By Olimpiu Pop
The continuous growth of data-intensive applications, particularly in AI/ML, drives the need for more efficient data processing solutions like Hardwood's Parquet implementation.
Improved Parquet processing directly benefits big data and AI/ML ecosystems by offering higher performance and lower operational overhead, impacting data-driven decision-making and product development.
Data processing in Java environments for Parquet files can now be significantly faster and less resource-intensive, potentially lowering infrastructure costs and accelerating development cycles.
- · AWS (and other cloud providers)
- · Data engineers
- · Java developers
- · AI/ML companies
- · Inefficient data processing solutions
- · Companies relying on older, slower Parquet implementations
Faster data pipelines for AI/ML and big data applications.
Reduced operational costs for data-intensive cloud workloads.
Acceleration of research and development in fields heavily reliant on large datasets.
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