Book Image

Applying and Extending Oracle Spatial

By : Siva Ravada, Simon Greener
Book Image

Applying and Extending Oracle Spatial

By: Siva Ravada, Simon Greener

Overview of this book

Spatial applications should be developed in the same way that users develop other database applications: by starting with an integrated data model in which the SDO_GEOMETRY objects are just another attribute describing entities and by using as many of the database features as possible for managing the data. If a task can be done using a database feature like replication, then it should be done using the standard replication technology instead of inventing a new procedure for replicating spatial data. Sometimes solving a business problem using a PL/SQL function can be more powerful, accessible, and easier to use than trying to use external software. Because Oracle Spatial's offerings are standards compliant, this book shows you how Oracle Spatial technology can be used to build cross-vendor database solutions. Applying and Extending Oracle Spatial shows you the clever things that can be done not just with Oracle Spatial on its own, but in combination with other database technologies. This is a great resource book that will convince you to purchase other Oracle technology books on non-spatial specialist technologies because you will finally see that "spatial is not special: it is a small, fun, and clever part of a much larger whole".
Table of Contents (20 chapters)
Applying and Extending Oracle Spatial
About the Authors
About the Reviewers
Table Comparing Simple Feature Access/SQL and SQL/MM–Spatial

Chapter 5. Partitioning of Data Using Spatial Keys

Spatial applications tend to generate large volumes of data, especially as the scale of observation of the world's surface extends to large parts of the Earth's surface. With the increasing data, database models have to adapt to deal with large volumes of spatial data that are not seen in traditional GIS applications. GIS applications expect all the related data in one feature layer, even if the feature layer contains millions of features. Oracle database supports a feature called partitioning that can break large tables at the physical storage level to smaller units while keeping the table as one object at the logical level. In this chapter, we cover the following five topics that are useful for managing large volumes of spatial data:

  • Introduction to partitioning

  • Time-based partitioning

  • Spatial key based partitioning

  • Implementing space curves based partitioning

  • High performance loading of the spatial data