Book Image

Applying and Extending Oracle Spatial

Book Image

Applying and Extending Oracle Spatial

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
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Table Comparing Simple Feature Access/SQL and SQL/MM–Spatial
Index

Spatial partitioning of tables


Tables with geometry can also be partitioned with a spatial key that is, the partitioning is done such that the rows that are close to each other in space will likely be placed in the same partition. There are several methods for using the spatial key to partition the data, and these methods vary depending on the type (point, line, or polygon) of spatial data. One of the main advantages of using a spatial partitioning key is the spatial pruning that comes into play during the query execution. In this section, we explain this concept and show how spatial pruning can help reduce query runtimes. First we look at tables with point data and explain the spatial partitioning of tables.

Single column key

Range-based partitioning requires a scalar (number, character, date, and so on) value as the partitioning key. From the geometry value, we can use either X or Y as this scalar value as the partitioning key. If the table has non-point geometry data, we need to map the...