Apache Arrow
| Apache Arrow | |
|---|---|
| Developer | Apache Software Foundation |
| Initial release | October 10, 2016; 9 years ago (2016年10月10日) |
| Stable release | |
| Repository | github |
| Written in | C, C++, C#, Go, Java, JavaScript, MATLAB, Python, R, Ruby, Rust |
| Type | Data format, algorithms |
| License | Apache License 2.0 |
| Website | arrow |
Apache Arrow is a language-agnostic software framework for developing data analytics applications that process columnar data. It contains a standardized column-oriented memory format that is able to represent flat and hierarchical data for efficient analytic operations on modern CPU and GPU hardware.[2] [3] [4] [5] [6] This reduces or eliminates factors that limit the feasibility of working with large sets of data, such as the cost, volatility, or physical constraints of dynamic random-access memory.[7]
Interoperability
[edit ]Arrow can be used with Apache Parquet, Apache Spark, NumPy, PySpark, pandas and other data processing libraries. The project includes native software libraries written in C, C++, C#, Go, Java, JavaScript, Julia, MATLAB, Python (PyArrow[8] ), R, Ruby, and Rust. Arrow allows for zero-copy reads and fast data access and interchange without serialization overhead between these languages and systems.[2]
Applications
[edit ]Arrow has been used in diverse domains, including analytics,[9] genomics,[10] [7] and cloud computing.[11]
Comparison to Apache Parquet and ORC
[edit ]Apache Parquet and Apache ORC are popular examples of on-disk columnar data formats. Arrow is designed as a complement to these formats for processing data in-memory.[12] The hardware resource engineering trade-offs for in-memory processing vary from those associated with on-disk storage.[13] The Arrow and Parquet projects include libraries that allow for reading and writing data between the two formats.[14]
Governance
[edit ]Apache Arrow was announced by The Apache Software Foundation on February 17, 2016,[15] with development led by a coalition of developers from other open source data analytics projects.[16] [17] [6] [18] [19] The initial codebase and Java library was seeded by code from Apache Drill.[15]
References
[edit ]- ^ "Release 22.0.0". 24 October 2025. Retrieved 11 November 2025.
- ^ a b "Apache Arrow and Distributed Compute with Kubernetes". 13 Dec 2018.
- ^ Baer, Tony (17 February 2016). "Apache Arrow: Lining Up The Ducks In A Row... Or Column". Seeking Alpha .
- ^ Baer, Tony (25 February 2019). "Apache Arrow: The little data accelerator that could". ZDNet .
- ^ Hall, Susan (23 February 2016). "Apache Arrow's Columnar Layouts of Data Could Accelerate Hadoop, Spark". The New Stack .
- ^ a b Yegulalp, Serdar (27 February 2016). "Apache Arrow aims to speed access to big data". InfoWorld .
- ^ a b Tanveer Ahmad (2019). "ArrowSAM: In-Memory Genomics Data Processing through Apache Arrow Framework". bioRxiv 741843. doi:10.1101/741843 .
- ^ "Python — Apache Arrow v20.0.0".
- ^ Dinsmore T.W. (2016). "In-Memory Analytics: Satisfying the Need for Speed". Disruptive Analytics. Apress, Berkeley, CA. pp. 97–116. doi:10.1007/978-1-4842-1311-7_5. ISBN 978-1-4842-1312-4.
- ^ Versaci F, Pireddu L, Zanetti G (2016). "Scalable genomics: from raw data to aligned reads on Apache YARN" (PDF). IEEE International Conference on Big Data: 1232–1241.
- ^ Maas M, Asanović K, Kubiatowicz J (2017). "Return of the Runtimes: Rethinking the Language Runtime System for the Cloud 3.0 Era". Proceedings of the 16th Workshop on Hot Topics in Operating Systems. pp. 138–143. doi:10.1145/3102980.3103003 . ISBN 978-1-4503-5068-6.
- ^ Le Dem, Julien. "Apache Arrow and Apache Parquet: Why We Needed Different Projects for Columnar Data, On Disk and In-Memory". KDnuggets .
- ^ "Apache Arrow vs. Parquet and ORC: Do we really need a third Apache project for columnar data representation?". 2017年10月31日.
- ^ "PyArrow:Reading and Writing the Apache Parquet Format".
- ^ a b "The Apache® Software Foundation Announces Apache ArrowTM as a Top-Level Project". The Apache Software Foundation Blog. 17 February 2016. Archived from the original on 2016年03月13日.
- ^ Martin, Alexander J. (17 February 2016). "Apache Foundation rushes out Apache Arrow as top-level project". The Register .
- ^ "Big data gets a new open-source project, Apache Arrow: It offers performance improvements of more than 100x on analytical workloads, the foundation says". 2016年02月17日. Archived from the original on 2016年07月27日. Retrieved 2018年01月31日.
- ^ Le Dem, Julien (28 November 2016). "The first release of Apache Arrow". SD Times .
- ^ "Julien Le Dem on the Future of Column-Oriented Data Processing with Apache Arrow".
External links
[edit ]- Apache Arrow project web site
- Apache Arrow GitHub project source code