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Geospatial Data Analytics on AWS

You're reading from   Geospatial Data Analytics on AWS Discover how to manage and analyze geospatial data in the cloud

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Product type Paperback
Published in Jun 2023
Publisher Packt
ISBN-13 9781804613825
Length 276 pages
Edition 1st Edition
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Authors (3):
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Scott Bateman Scott Bateman
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Scott Bateman
Jeff DeMuth Jeff DeMuth
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Jeff DeMuth
Janahan Gnanachandran Janahan Gnanachandran
Author Profile Icon Janahan Gnanachandran
Janahan Gnanachandran
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Table of Contents (23) Chapters Close

Preface 1. Part 1: Introduction to the Geospatial Data Ecosystem
2. Chapter 1: Introduction to Geospatial Data in the Cloud FREE CHAPTER 3. Chapter 2: Quality and Temporal Geospatial Data Concepts 4. Part 2: Geospatial Data Lakes using Modern Data Architecture
5. Chapter 3: Geospatial Data Lake Architecture 6. Chapter 4: Using Geospatial Data with Amazon Redshift 7. Chapter 5: Using Geospatial Data with Amazon Aurora PostgreSQL 8. Chapter 6: Serverless Options for Geospatial 9. Chapter 7: Querying Geospatial Data with Amazon Athena 10. Part 3: Analyzing and Visualizing Geospatial Data in AWS
11. Chapter 8: Geospatial Containers on AWS 12. Chapter 9: Using Geospatial Data with Amazon EMR 13. Chapter 10: Geospatial Data Analysis Using R on AWS 14. Chapter 11: Geospatial Machine Learning with SageMaker 15. Chapter 12: Using Amazon QuickSight to Visualize Geospatial Data 16. Part 4: Accessing Open Source and Commercial Platforms and Services
17. Chapter 13: Open Data on AWS 18. Chapter 14: Leveraging OpenStreetMap on AWS 19. Chapter 15: Feature Servers and Map Servers on AWS 20. Chapter 16: Satellite and Aerial Imagery on AWS 21. Index 22. Other Books You May Enjoy

Architectural considerations

When working with raw datasets that have large amounts of data, performance can be slower than desired as some basic queries can take 30 seconds or longer. A simple tactic for speeding up performance is to simply create an Athena table from the query results. You can limit your query to a bounding box of latitude and longitude values to refine the results further:

CREATE TABLE "skilifts-wasatch" AS
SELECT * FROM skilifts_vw
WHERE lat between 40 and 41
    AND lon between -112 and -111

This will capture a snapshot of the data from the view within the specified bounding box for fast querying. Any table that is created using this method should be managed and refreshed at the appropriate intervals. Using this approach can result in stale tables if not organized effectively. Despite the cautions, using this technique to search for a specific ski lift speeds up the query from around 20 seconds to well under a second.

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