Tuesday Apr 01, 2014

Upcoming Webinars: MapViewer at City of Toronto for Public Safety, Customers Achieve 300x Performance Gains with Oracle Spatial and Graph

A note to share information about two upcoming Directions Media webinars on April 23 and May 6.

City of Toronto Enhances Public Safety Using Real-time Big Data and Map Rendering with Oracle and AGSI, Wed., April 23, 2:00PM US EDT

Learn how the City of Toronto Police Services can search, review and map social media traffic in real time to quickly identify and respond to incidents, improving public safety. See live demos of their system using Oracle MapViewer's HTML5 capabilities, Oracle Spatial, and a social media mapping platform from partner AGSI. Carol Palmer of Oracle will co-present this webinar with Mike Jander of AGSI, and City of Toronto, hosted by Directions Media.

Learn more and register for this free webinar -
http://www.directionsmag.com/webinars/register/city-of-toronto-enhances-public-safety-using-real-time-big-data-and-ma/389356?DM_webinars_section&utm_medium=web&utm_campaign=389356


Learn How Customers Are Experiencing 300x Performance Gains with Oracle Spatial and Graph, Tues., May 6, 2:00PM US EDT (Free Webinar)

Nick Salem of Neustar and Steve Pierce of Think Huddle will share their realized performance benchmarks using Oracle Spatial and Graph. With Oracle Spatial and Graph in Database 12c, customers can address the largest geospatial workloads and experience performance increases of 50 to 300 times for vector operations, with minimal configuration changes. Jim Steiner of Oracle will also discuss performance gains from parallel raster processing and Exadata.

Learn more and register for this free webinar -
http://www.directionsmag.com/webinars/register/learn-how-customers-are-experiencing-300x-performance-gains-with-oracl/390239?DM_webinars_section&utm_medium=web&utm_campaign=390239

Monday Feb 24, 2014

Performance Boost with Aggregating Geometries - with 12c Spatial Vector Performance Acceleration

Nick Salem of Neustar recently shared some impressive performance gains realized using Oracle Spatial 12c Vector Performance Acceleration, in a Google+ post.   He observed performance gains of 40X to 300X -- with a use case aggregating all ZIP Code geographies in California using a SDO_AGGR_UNION operations (plain and with group by/mod functions as described in 11g documented best practices). 

Read more details of his test case and results here.  https://plus.google.com/114373574274269737617/posts/2caAypKxwff

Thanks for sharing, Nick!

Friday Jan 10, 2014

New Point-in-Polygon function in Oracle Spatial and Graph 12c

By: Jim Steiner, Siva Ravada, Rick Anderson

With the increased adoption of Exadata for spatial workloads, we have been looking at ways to exploit more and more of the capabilities of this architecture to address problems faced in large scale spatial analysis. The new point-in-polygon function in Spatial can result in 100s of times faster UPDATE and INSERT operations with no degradation in query performance for large scale point-in-polygon operations. Mask operations (DISJOINT, TOUCH, INSIDE, ANYINTERACT) can be performed with the point-in-polygon function.

When working with point data and performing point-in-polygon analysis the existing spatial operators to do a fast query on the data if there is a Spatial index on the point data. However, in many cases, the data volume is very high, so creating and maintaining the index becomes very expensive. With 12c, we exploit Exadata smartscan by implementing a different model to take advantage of all the CPUs to do point in polygon operations and not have the overhead of a Spatial index. The mdsys.PointInPolygon() function returns those rows that reside within a specified polygon geometry. This parallel-enabled Point-In-Polygon function takes an arbitrary set of rows whose first column is a point's x-coordinate value and the second column is a point's y-coordinate value.

The mdsys.PointInPolygon() function API is the following:

mdsys.sdo_PointInPolygon(cur SYS_REFCURSOR,
                         geom_obj IN SDO_GEOMETRY,
                         tol IN NUMBER,
                         params IN VARCHAR2 DEFAULT NULL);

The "cur" parameter is used to select an "x" and "y" point coordinate from a

user table. The two columns must be of type NUMBER; this is NOT a geometry

parameter.

The "geom_obj" parameter is either a polygon geometry from a table, or a

Transient instance of a polygon geometry, against which all of the selected points from "cur" will be validated.

The "tol" parameter is the desired tolerance value, which must be greater than the value "0.0".



The following examples show the performance benefits of this new approach:

Here we select all rows from the "weather_sensor" table and query those rows against a transient polygon geometry instance. Only 1 weather_sensor row (out of 4) resides within the specified polygon.

SQL> SELECT *

2 FROM TABLE(mdsys.sdo_PointInPolygon(

3 CURSOR(select * from weather_sensor),

4 MDSYS.SDO_GEOMETRY(

5 2003,

6 NULL,

7 NULL,

8 MDSYS.SDO_ELEM_INFO_ARRAY(1, 1003, 1),

9 MDSYS.SDO_ORDINATE_ARRAY(5, 1, 8, 1, 8, 6, 5, 7, 5, 1)),

10 0.05));

In order to utilize parallel query servers, you must either specify the

"/*+ PARALLEL(4) */" optimizer hint, or enable parallel query execution,

using the command:

alter session force parallel query;

Below is the same as above, but uses 4 parallel query servers:

SQL> SELECT /*+ PARALLEL(4) */ *

2 FROM TABLE(mdsys.sdo_PointInPolygon(

3 CURSOR(select * from weather_sensor),

4 MDSYS.SDO_GEOMETRY(

5 2003,

6 NULL,

7 NULL,

8 MDSYS.SDO_ELEM_INFO_ARRAY(1, 1003, 1),

9 MDSYS.SDO_ORDINATE_ARRAY(5, 1, 8, 1, 8, 6, 5, 7, 5, 1)),

10 0.05));

There can be a huge performance benefit to using parallel query servers.

The following "worst-case" example queries 1-million rows against a transient

polygon geometry instance, using the non-parallel query execution:

SQL> -- instead of the actual data...

SQL>

SQL> -- Test "non-parallel" execution first

SQL> timing start "sdo_PointInPolygon()"

SQL> SELECT COUNT(*)

2 FROM TABLE(mdsys.sdo_PointInPolygon(

3 CURSOR(select * from pip_data),

4 MDSYS.SDO_GEOMETRY(

5 2003,

6 NULL,

7 NULL,

8 MDSYS.SDO_ELEM_INFO_ARRAY(1, 1003, 1),

9 MDSYS.SDO_ORDINATE_ARRAY(5, 1, 8, 1, 8, 6, 5, 7, 5, 1)),

10 0.05));

timing for: sdo_PointInPolygon()

Elapsed: 00:05:00.73

Enabling the parallel query servers dramatically reduces the query execution time:

SQL> -- Now test using 4 parallel query servers

SQL> timing start "sdo_PointInPolygon()"

SQL> SELECT /*+ PARALLEL(4) */ COUNT(*)

2 FROM TABLE(mdsys.sdo_PointInPolygon(

3 CURSOR(select * from pip_data),

4 MDSYS.SDO_GEOMETRY(

5 2003,

6 NULL,

7 NULL,

8 MDSYS.SDO_ELEM_INFO_ARRAY(1, 1003, 1),

9 MDSYS.SDO_ORDINATE_ARRAY(5, 1, 8, 1, 8, 6, 5, 7, 5, 1)),

10 0.05));

SQL> timing stop

timing for: sdo_PointInPolygon()

Elapsed: 00:02:18.18

For more information about this new feature, link to the documentation URL:
SDO_PointInPolygon


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The official blog for the spatial features of Oracle Spatial and Graph, an option of Oracle Database - brought to you by the product managers and developers. Get technical tips, product information, and the latest news here. Visit our official product website at http://www.oracle.com/technetwork/database/options/spatialandgraph/overview/spatialfeatures-1902020.html

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