Apache DataFusion Comet Accelerates Spark | Generated by AI
Apache DataFusion Comet
Apache DataFusion Comet is an open-source project under the Apache Software Foundation that serves as a high-performance accelerator for Apache Spark. It’s built on top of the Apache DataFusion query engine and aims to boost Spark workload performance—such as faster data processing and quicker insights—while running on standard commodity hardware. No code changes are required for integration, and it also speeds up Apache Iceberg operations involving Parquet scans from Spark.
Key Features
- Performance Gains: Delivers significant speedups for queries. For example, benchmarks on 22 TPC-H queries against 100 GB of Parquet data show a 2.2x overall improvement (from 687 seconds to 302 seconds on a single 8-core executor). TPC-DS benchmarks are also available, with reproducible results via the project’s guides.
- Hardware Efficiency: Works with off-the-shelf hardware, avoiding the need for expensive GPUs or FPGAs.
- Seamless Compatibility: Fully compatible with supported Apache Spark versions, ensuring drop-in integration into existing setups.
- Tight DataFusion Integration: Leverages DataFusion’s execution engine for optimized efficiency.
- Community-Driven: Licensed under Apache License 2.0, with an active community for contributions, including bug fixes, features, and documentation.
The project is actively maintained, with resources for getting started, contributor guides, and community channels like Slack and Discord.
For more details, including installation (via docs at datafusion.apache.org) and benchmarking, check the repository.
Apache DataFusion Comet GitHub Repository