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Cloud Native Geospatial Analytics with Apache Sedona: A Hands-On Guide for Working with Large-Scale Spatial Data
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Livraison entre le Vendredi 10 juillet 2026 et le Samedi 11 juillet 2026
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Marque : GENERIC
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Navigating the complexities of large-scale spatial data can be daunting. In order to unleash the power of massive and complex datasets, you'll need a cutting-edge tool like Apache Sedona. This innovative distributed computing system, designed specifically for spatial data, has diverse applications in fields such as mobility, telematics, agriculture...
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Description produit
- Marque
- GENERIC
- Titre principal
- Cloud Native Geospatial Analytics with Apache Sedona: A Hands-On Guide for Working with Large-Scale Spatial Data
- Editeur
- O'Reilly Media
- Type de produit
- paperback
- Présentation du livre
- paperback
- Release date
- 1/13/2026 12:00:00 AM
- Langue d'origine
- English
- ISBN
- 1098173996
- Dimensions
- 7 x 2 x 9.19 inches
- Nombre de pages de livre
- 336 pages
- Langue - Librairie
- English
- Résumé
- Navigating the complexities of large-scale spatial data can be daunting. In order to unleash the power of massive and complex datasets, you'll need a cutting-edge tool like Apache Sedona. This innovative distributed computing system, designed specifically for spatial data, has diverse applications in fields such as mobility, telematics, agriculture, climate science, and more. This book serves as your guide to leveraging this tool, along with other technologies, to unlock the potential of geospatial analytics.Authors Paweł Tokaj, Jia Yu, and Mo Sarwat provide practical solutions to the challenges of working with geospatial data at scale. Ideal for developers, data scientists, engineers, and analysts, this guide uses real-world examples to help you integrate Python data ecosystems, apply machine learning, build geospatial data lakehouses, and handle modern geospatial data formats like GeoParquet.Understand how Apache Sedona helps data practitioners address challenges with geospatial dataLearn how to run Apache Sedona, both locally and in cloud environmentsEfficiently load, query, and analyze geospatial datasets using spatial SQLEmploy machine learning techniques to derive strategy-defining insights from spatial dataManage and optimize large-scale geospatial data within a data lakehouse architecture Read more
- Auteur(s)
- Pawel Tokaj, Jia Yu, Mo Sarwat
- Date de parution
- 1/13/2026 12:00:00 AM









