Book Image

PostGIS Cookbook - Second Edition

By : Pedro Wightman, Bborie Park, Stephen Vincent Mather, Thomas Kraft, Mayra Zurbarán
Book Image

PostGIS Cookbook - Second Edition

By: Pedro Wightman, Bborie Park, Stephen Vincent Mather, Thomas Kraft, Mayra Zurbarán

Overview of this book

PostGIS is a spatial database that integrates the advanced storage and analysis of vector and raster data, and is remarkably flexible and powerful. PostGIS provides support for geographic objects to the PostgreSQL object-relational database and is currently the most popular open source spatial databases. If you want to explore the complete range of PostGIS techniques and expose related extensions, then this book is for you. This book is a comprehensive guide to PostGIS tools and concepts which are required to manage, manipulate, and analyze spatial data in PostGIS. It covers key spatial data manipulation tasks, explaining not only how each task is performed, but also why. It provides practical guidance allowing you to safely take advantage of the advanced technology in PostGIS in order to simplify your spatial database administration tasks. Furthermore, you will learn to take advantage of basic and advanced vector, raster, and routing approaches along with the concepts of data maintenance, optimization, and performance, and will help you to integrate these into a large ecosystem of desktop and web tools. By the end, you will be armed with all the tools and instructions you need to both manage the spatial database system and make better decisions as your project's requirements evolve.
Table of Contents (18 chapters)
Title Page
Packt Upsell
Contributors
Preface
Index

Geospatial sharding


Working with large datasets can be challenging for the database engine, especially when they are stored in a single table or in a single database. PostgreSQL offers an option to split the data into several external databases, with smaller tables, that work logically as one. Sharding allows distributing the load of storage and processing of a large dataset so that the impact of large local tables is reduced.

One of the most important issues to make it work is the definition of a function to classify and evenly distribute the data. Given that this function can be a geographical property, sharding can be applied to geospatial data.

Getting ready

In this recipe, we will use the postgres_fdw extension that allows the creation of foreign data wrappers, needed to access data stored in external PostgreSQL databases. In order to use this extension, we will need the combination of several concepts: server, foreign data wrapper, user mapping, foreign table and table inheritance. We...