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You're reading from Mastering Geospatial Analysis with Python

Product typeBook

Published inApr 2018

Reading LevelBeginner

PublisherPackt

ISBN-139781788293334

Edition1st Edition

Languages

Python

Concepts

Geospatial Analysis

Authors (3):

Silas Toms

Paul Crickard

Eric van Rees

View More author details

Chapter 10. Geoprocessing with a GPU Database

With the emergence of multi-core GPUs, new database technologies have been developed to take advantage of this improved technology. MapD, a startup based in San Francisco, is one example of these companies. Their GPU-based database technology was made open source in 2017 and is available for use on cloud services, such as Amazon Web Services (AWS) and Microsoft Azure. By combining the parallelization potential of GPUs with a relational database, the MapD database improves the speed of database queries and visualizations based on the data.

MapD has created a Python 3 module, pymapd, that allows users to connect to the database and automate queries. This Python binding allows geospatial professionals to integrate the speed of a GPU database into an existing geospatial architecture, adding speed improvements to analysis and queries. Both of MapD's core offerings (the open source community version and the commercial enterprise version) are supported...

Cloud geodatabase solutions

Cloud storage of geospatial data has become a common part of many GIS architectures. Whether it is used as a backup to an on-premises solution, replaces an on-premises solution, or is combined with a local solution to provide internet support for an intranet-based system, the cloud is a big part of the future of GIS.

With ArcGIS Online, CARTO, MapBox, and now MapD, the options for a cloud data store that support geospatial data are more numerous than ever. Each offers a visualization component and a different type of data storage and each will integrate with your data and software in different ways.

ArcGIS Online, while also offering stand-alone options (that is, direct data upload), integrates with ArcGIS Enterprise (formerly ArcGIS Server) to consume enterprise REpresentational State Transfer (REST) web services that are stored on a local geodatabase. ArcGIS Online is built on top of Amazon Web Services (AWS) and all of the server architecture is hidden from...

Summary

Using a cloud-based GPU database like MapD Core, and the Immerse visualization studio will pay dividends when designing and implementing a GIS. It offers speed and cloud reliability to both tabular and spatial queries and allows the data to be shared in interactive dashboards (which rely on JavaScript technologies such as D3.js and MapBox GL JavaScript) that are simple to create and publish.

With the MapD Python module, pymapd, cloud data can become an integrated part of a query engine. Data can be pushed to the cloud or pulled down to use locally. Analyses can be performed rapidly, using the power of GPU parallelization. It's worth installing MapD on a virtual server in the cloud, or even locally, to test out the potential of the software.

In the next chapter, we will explore the use of Flask, SQLAlchemy, and GeoAlchemy2 to create an interactive web map with a PostGIS geodatabase backend.

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Authors (3)

Silas Toms

Silas Toms is a long-time geospatial professional and author who has previously published ArcPy and ArcGIS and Mastering Geospatial Analysis with Python. His career highlights include developing the real-time common operational picture used at Super Bowl 50, building geospatial software for autonomous cars, designing computer vision for next-gen insurance, and developing mapping systems for Zillow. He now works at Volta Charging, predicting the future of electric vehicle adoption and electric charging infrastructure.
Read more about Silas Toms

Paul Crickard

Paul Crickard authored a book on the Leaflet JavaScript module. He has been programming for over 15 years and has focused on GIS and geospatial programming for 7 years. He spent 3 years working as a planner at an architecture firm, where he combined GIS with Building Information Modeling (BIM) and CAD. Currently, he is the CIO at the 2nd Judicial District Attorney's Office in New Mexico.
Read more about Paul Crickard

Eric van Rees

Eric van Rees was first introduced to Geographical Information Systems (GIS) when studying Human Geography in the Netherlands. For 9 years, he was the editor-in-chief of GeoInformatics, an international GIS, surveying, and mapping publication and a contributing editor of GIS Magazine. During that tenure, he visited many geospatial user conferences, trade fairs, and industry meetings. He focuses on producing technical content, such as software tutorials, tech blogs, and innovative new use cases in the mapping industry.
Read more about Eric van Rees

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