Apache Sedona

Last updated
Apache Sedona
Other namesGeoSpark
Original authors Jia Yu, Mohamed Sarwat
Developer Apache Software Foundation
Initial release December 10, 2017;8 years ago (2017-12-10)
Repository https://github.com/apache/sedona
Available in Scala, Java, SQL, Python, R,
License Apache 2.0
Website sedona.apache.org

Apache Sedona (formerly GeoSpark) is an open-source framework designed for processing and analyzing large-scale spatial data in a distributed computing environment. [1] [2] It originated as GeoSpark in 2010 by researchers at Arizona State University [3] and later entered incubation with the Apache Software Foundation in 2020. It graduated as a top-level project in February 2023. [4]

Contents

Overview

Sedona is a framework that facilities distributed geospatial data processing. It integrates with Apache Spark, Apache Flink, Snowflake [5] [6] and includes Spatial Datasets and Spatial SQL functions to loading, processing, and analyzing large-scale geospatial data across systems. [7] It supports spatial data formats, including GeoJSON, Well Known Text and Well-Known Binary [8] [9] as well as multiple coding languages, including Java, Python, R, Scala, and SQL. [10] [11]

History

The project was initiated as GeoSpark by Jia Yu and Mohamed "Mo" Sarwart at Arizona State University in 2010. [12] In 2020, the project was submitted to the Apache Software Foundation [13] and graduated in 2023.

See also

References

  1. ↑ Yu, Jia; Wu, Jinxuan; Elsayed, Mohamed (2015-11-03). "GeoSpark: A cluster computing framework for processing large-scale spatial data". In Huang, Yan; Ali, Mohamed; Sankaranarayanan, Jagan; Renz, Matthias; Gertz, Michael (eds.). Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems. GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems. pp. 1–4. doi:10.1145/2820783.2820860. ISBN   978-1-4503-3967-4.
  2. ↑ Johnson, Robert (2025-01-06). Apache Sedona Essentials: A Practical Guide to Spatial Data Processing. HiTeX Press.
  3. ↑ Woodie, Alex (2025-07-22). "Apache Sedona: Putting the 'Where' In Big Data". BigDATAwire. Retrieved 2025-09-18.
  4. ↑ ASF, The (2023-02-08). "The Apache Software Foundation Announces New Top-Level Project Apache® Sedona". The ASF Blog. Retrieved 2025-09-18.
  5. ↑ "Introduction to GeoSpatial streaming with Apache Spark and Apache Sedona". getindata.com. Retrieved 2025-09-18.
  6. ↑ Pruden, Ben (2024-02-06). "SedonaSnow: Apache Sedona On Snowflake, Accelerating Your GIS Pipeline, Exploring Global Fishing Watch Data With GeoParquet, and Apache Sedona 1.5.1 Release". Wherobots. Retrieved 2025-09-18.
  7. ↑ Armir, Bujari; Alessandro, Calvio; Luca, Foschini; Andrea, Sabbioni; Antonio, Corradi (2021-12-13). "A Digital Twin Decision Support System for the Urban Facility Management Process". Sensors. 21 (24): 8460. Bibcode:2021Senso..21.8460B. doi: 10.3390/s21248460 . ISSN   1424-8220. PMC   8709487 . PMID   34960550.
  8. ↑ García-García, Francisco; Corral, Antonio; Iribarne, Luis; Vassilakopoulos, Michael (2023-04-03). "Efficient distributed algorithms for distance join queries in spark-based spatial analytics systems". International Journal of General Systems. 52 (3): 206–250. Bibcode:2023IJGS...52..206G. doi:10.1080/03081079.2023.2173750. hdl: 10835/17848 . ISSN   0308-1079.
  9. ↑ Rout, Rashmi Ranjan; Ghosh, Soumya Kanti; Jana, Prasanta K.; Tripathy, Asis Kumar; Sahoo, Jyoti Prakash; Li, Kuan-Ching (2022-07-27). Advances in Distributed Computing and Machine Learning: Proceedings of ICADCML 2022. Springer Nature. ISBN   978-981-19-1018-0.
  10. ↑ "Working with Apache Sedona | Delta Lake". delta.io. Retrieved 2025-09-18.
  11. ↑ "Introduction to Apache Sedona (incubating)". getindata.com. Retrieved 2025-09-18.
  12. ↑ Woodie, Alex (2025-07-22). "Apache Sedona: Putting the 'Where' In Big Data". BigDATAwire. Retrieved 2025-09-18.
  13. ↑ Sally (2021-01-01). "Apache in 2020 - By The Digits". The ASF Blog. Retrieved 2025-09-18.
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