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Mastering Geospatial Analysis with Python

You're reading from   Mastering Geospatial Analysis with Python Explore GIS processing and learn to work with GeoDjango, CARTOframes and MapboxGL-Jupyter

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788293334
Length 440 pages
Edition 1st Edition
Languages
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Authors (3):
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Silas Toms Silas Toms
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Silas Toms
Paul Crickard Paul Crickard
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Paul Crickard
Eric van Rees Eric van Rees
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Eric van Rees
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Toc

Table of Contents (18) Chapters Close

Preface 1. Package Installation and Management 2. Introduction to Geospatial Code Libraries FREE CHAPTER 3. Introduction to Geospatial Databases 4. Data Types, Storage, and Conversion 5. Vector Data Analysis 6. Raster Data Processing 7. Geoprocessing with Geodatabases 8. Automating QGIS Analysis 9. ArcGIS API for Python and ArcGIS Online 10. Geoprocessing with a GPU Database 11. Flask and GeoAlchemy2 12. GeoDjango 13. Geospatial REST API 14. Cloud Geodatabase Analysis and Visualization 15. Automating Cloud Cartography 16. Python Geoprocessing with Hadoop 17. Other Books You May Enjoy

Python Geoprocessing with Hadoop

Most of the examples in this book worked with relatively small datasets using a single computer. But as data gets larger, the datasets and even individual files may be spread out over a cluster of machines. Working with big data requires different tools. In this chapter, you will learn how to use Apache Hadoop to work with big data, and the Esri GIS tools for Hadoop to work with the big data spatially.

This chapter will teach you how to:

  • Install Linux
  • Install and run Docker
  • Install and configure a Hadoop environment
  • Work with files in HDFS
  • Basic queries using Hive
  • Install the Esri GIS tools for Hadoop
  • Perform spatial queries in Hive
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