Six functions of Oracle Spatial in practical application

In practical applications, Oracle Spatial not only has all the characteristics related to traditional GIS, but also has the characteristics related to relational databases, these features extend the scope of work of developers in applications and provide their productivity, so as to support a wider range of applications and improve performance, the following are the main characteristics of these features:

1) geometric structure and spatial reference

Oracle Spatial supports three basic geometric shapes that can be used to represent the features that normally constitute a Spatial database, such as roads, administrative boundaries, and public facilities. These basic spatial elements include:
Vertices and clusters: Points can represent locations such as buildings, fire hydrants, utility poles, drilling, freight cars, or moving vehicles.

Line and line string: a line can represent a road, a railway line, a utility line, or a faulty line.

Polygon and complex polygon with holes: polygon can represent the outlines of cities, blocks, river mantan or oil fields and natural gas fields. A polygon with holes can represent a small area of land surrounded by a swamp. To effectively integrate and represent Spatial information, Oracle Spatial provides a wide range of tools to manage coordinate system and projection.

Supports more than 950 commonly used coordinate system for plotting, and you can also define a new coordinate system. Oracle Spatial also supports arbitrary data conversion between different coordinate systems. These conversions can be performed at a geometric level or on the entire layer at a time.

2) Spatial Index: R-tree

To optimize the performance of spatial queries, Oracle Locator provides spatial indexes for relational databases. Oracle Locator provides the R-tree index creation function, which generates and stores approximate values of geometric structures as indexes. R-tree indexes are easy to create and use-you can achieve optimal performance with almost no adjustment required. You can create an R-tree index on two, three, or four dimensions of spatial data.

3) Spatial Operators

Interaction between various geometric features can be determined by using comparison operators, such as contains, covers, and anyinteract ). In this way, you can reply to a request similar to the following: "list all the campuses that this line passes" or "find all the flower shops in this city"

4) function-based index support

Now, you do not need to explicitly store the location information as a column of the SDO_GEOMETRY type to perform a space query on the Link property. You can create spatial indexes on spatial data stored in relational columns such as longitude and latitude. Then, you can call the space operator on these relational columns without creating an SDO_GEOMETRY column.

5) support for Earth coordinates

In terms of surface measurements, no matter what the coordinate system is, spatial functions, operators, and utilities provide correct results. Distance, area, angle, and other units are fully supported.

6) Partition support for spatial indexes

Spatial indexes can be partitioned Based on partitioned tables. Partitioning spatial data and using the local index of the partition can provide performance gains for queries on large datasets and concurrent queries and updates. It also makes index maintenance easier.

7) create spatial indexes in parallel

Index creation can be subdivided into smaller tasks that can be executed in parallel to take advantage of unused hardware (CPU) resources. For some spatial databases, as well as index types and data, parallel index creation can fully improve index building performance and significantly save time.

The above is an introduction to the Oracle Spatial-related content. I hope you will gain some benefits.