OVERVIEW •  “Big Data” and its impact on Spatial performance •  Testing configurations •  Use cases / techniques for improving performance •  Performance improvement data

CHALLENGES / OPPORTUNITIES •  With 11g, performance sometimes limited interactions with

Big Data •  Making improvements was time-consuming

SOLUTIONS •  Oracle Database 12c Enterprise Edition

•  Spatial Option with GeoRaster, Network Data Model •  Partitioning

•  Oracle Fusion Middleware 11.1.1.7 •  MapViewer

•  Oracle Business Intelligence Enterprise Edition

RESULTS •  Achieving at least 2x performance improvement – in

some cases up to 300x improvement •  Only small configuration changes are needed •  Time to develop and maintain these solutions is reduced

Think Huddle and Neustar Performance Gains with 12c /

0 500

1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000

11g 12c 12c SVA

6.5x faster performance 11m 53s vs 1hr 17m 26s

May 2014 Oracle Spatial Summit

May 21, 2014 Walter E. Washington Convention Center

Washington, DC USA

Steve Pierce CEO

Nick Salem Distinguished Engineer

Performance Gains with Spatial & Graph Using Oracle Database 12c

•  Big Data: What’s the big deal? •  Testing configurations • Use cases and performance data on:

–  Geometry aggregation –  Point in polygon –  Joins

• Q&A

Program Agenda

Think Huddle Corporate Overview

• Our company –  Oracle Spatial and MapViewer –  Big Data and BI for Spatial –  Fortune 500 clients

•  Steve Pierce –  Chair – Oracle Spatial SIG –  15 years Oracle

What’s the Big Deal?

• Data growing –  Big Data systems for spatial processing

•  Fundamental changes in 12c –  Faster vector algorithms –  Better caching –  Improved memory management

•  12c works for Big Data –  (and maintains data integrity –  … and keeps data secure –  … and supports relational integrity –  … and your users can access it)

BIG DATA

Test Environment

Environment Oracle 11g Oracle 12c

OS Oracle Linux 6.5 Oracle Linux 6.5

Processor E5 Xeon 2.9Ghz x 2

E5 Xeon 2.9Ghz x 2

Disk Intel SSD s Intel SSD s

Memory 32GB 32GB

Huge Pages Yes Yes

SGA/PGA 8GB/2GB 8GB/2GB

Source data Census / Generated

Census / Generated

•  1 Server – 2 Oracle Databases

•  Trusted company serving the internet, telco, information services, retail, media and advertising industries

•  Publicly held - $902M+ Company •  1,600+ employees worldwide – HQ’d in Sterling, VA •  Extensive data assets (4 billion global phone numbers,

2.8 billion global IP addresses, 6.4 million global domain names and 13.1 US business listings)

•  20 billion requests a day (DNS, text messages, phone)

Neustar Corporate Overview Real Intelligence. Better Decisions.

Neustar’s ElementOne Platform Geospatial Analytics in the Cloud

•  Highly flexible and high performance mapping

•  Rich market and trade area capability •  Road network / drive time analysis •  Heat themes •  GeoRaster images •  Aerials / terrain map overlays •  Scalable and high performance data

retrieval •  Centralized secure data repository

• Oracle VM Server 3.0 (Xen version 4.1 PVM) • Created 2 identical VMs with Oracle Linux 6.5

–  Installed Oracle 11g on one and 12c on the other

• Database configuration –  8G of SGA / 2G of PGA –  4 x 8 Core CPUs (Intel Xeon 2.70GHz)

•  Loaded core ElementOne database on each • Compare 11g to 12c w/ & w/o spatial vector acceleration

Neustar’s ElementOne Platform 11g vs 12c Test Benchmark Environment

Use Case – Geometry Aggregation

Aggregation of census tracts into larger geometries based on neighbor relationships

INTERACT UNION

•  Each Census tract in Virginia –  Aggregate Union of Neighbors

•  SDO_ANY_INTERACT + SDO_AGGR_UNION

–  2,000 Aggregations –  Tracts have 7 neighbors = 14,000 tracts –  280 tracts processed per second 0

50

100

150

200

250

300

350

11g 12c 12c SVA

Elapsed Time (s)

Use Case – Geometry Aggregation

Neustar’s ElementOne on 12c SDO_AGGR_UNION – CA ZIPs

•  Use case consisted of aggregating all ZIP Codes in California using plain SDO_AGGR_UNION and with mod/group by functions

•  Achieved up to 300x faster performance w\ SDO_AGGR_UNION and 40x faster with mod/group by method in12c with SVA enabled vs 11g

•  Reduced elapsed time from 1 hour 54 seconds to just 12 seconds

0 500

1,000 1,500 2,000 2,500 3,000 3,500 4,000

11g 12c 12c SVA

Elapsed Time In Seconds

Using SDO AGGR UNION

SDO AGGR UNION + Mod/Group

Neustar’s ElementOne on 12c SDO_AGGR_SET_UNION – CA ZIPs

0 20 40 60 80

100 120 140 160 180 200

11g 12c 12c SVA

14x faster performance 12s vs 2m 51s

SDO AGGR SET UNION

Neustar’s ElementOne on 12c SDO_TOUCH – CA ZIPs touch BGs

•  For all California ZIP codes, retrieve the block groups that they touch

0

50

100

150

200

250

11g 12c 12c SVA

8x faster performance 25s vs 3m 23s

SDO_TOUCH

Neustar’s ElementOne on 12c Spatial Relationships

•  Determine spatial relationships and interactions –  Inside, touch, anyinteract, overlap, disjoint

•  SDO_UTIL and SDO_GEOM for various geography creation and manipulation

•  Shape intersection, XOR, union, difference, point at bearing, radian, distance, convex hull, polygon smoothing and more

•  ElementOne Trade Areas (customer threshold, non-overlapping radii + component geos, donuts, square + hex grids, drive time, heat regions)

•  Thematic overlays and extents

Neustar’s ElementOne on 12c SDO_WITHIN_DISTANCE Benchmarks

•  For 544 super regional shopping centers, retrieve all businesses with a 10 mile radius

0 100 200 300 400 500 600 700 800 900

1,000

11g 12c 12c SVA

6x faster 2m 17s vs 14m 32s

SDO WITHIN DISTANCE

Neustar’s ElementOne on 12c SDO_GEOM.RELATE – CA ZIPs & BGs

•  Determine spatial topological relationship for California ZIP codes and surrounding block groups

0 50

100 150 200 250 300 350 400 450

11g 12c 12c SVA

3x faster performance 2m 16s vs 7m 2s

SDO_GEOM RELATE (mask = determine)

Neustar’s ElementOne on 12c SDO_GEOM.DISTANCE Benchmarks

•  Calculate distances between a single site and 112,610 surrounding sites

0

50

100

150

200

250

11g 12c 12c SVA

2.6x faster performance 1m 13s vs 3m 11s

SDO_GEOM DISTANCE

Neustar’s ElementOne on 12c SDO_INSIDE – Businesses inside NY BGs

•  Retrieve all businesses inside New York state block groups

0 20 40 60 80

100 120 140 160 180 200

11g 12c 12c SVA

2.1x faster performance 1m 22s vs 2m 53s

SDO_INSIDE

Use Case – Point in Polygon

Point in polygon calculations for finding houses within an area of interest

What’s in there?

Use Case – Point in Polygon 11g

•  In 11g there were ways to do this SELECT lon, lat FROM (SELECT SDO_GEOMETRY(2001, 8307,

SDO_POINT_TYPE(lon, lat, NULL), NULL, NULL) geom FROM large) c,

states s WHERE SDO_ANYINTERACT(s.geom,c.geom) = 'TRUE' AND s.state_abrv='CA'

Use Case – Point In Polygon 12c

0

50

100

150

200

250

300

11g Relate

12c SVA PiP

12c SVA PiP (8)

Elapsed Time (s)

SELECT lon, lat FROM TABLE(mdsys.sdo_PointInPolygon( CURSOR(select lon, lat from large),

(select geom from states where state_abrv='CA‘ ) , .05))

•  /*+ PARALLEL(#) */ –  Near linear performance boost

•  Sdo_PointInPolygon

Use Case – Joins

Which objects are in which region?

And there?

What’s in there? And here?

Use Case – Joins

•  SDO_JOIN – For bulk joins –  sdo_join('LARGE', 'GEOM', 'STATES',

'GEOM', 'mask=anyinteract'

• Works in 11g

•  Faster in 12c 0

100

200

300

400

500

600

700

11g 12c 12c SVA

Elapsed Time (s)

Neustar’s ElementOne on 12c SDO_JOIN – ZIP & Block Group Tables

•  Join using mask=anyinteract

0 500

1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000

11g 12c 12c SVA

6.5x faster performance 11m 53s vs 1hr 17m 26s

SDO_JOIN

Neustar’s ElementOne on 12c SDO_CS.TRANSFORM – US block groups

0 200 400 600 800

1,000 1,200 1,400 1,600

11g 12c 12c SVA

10x faster performance 2m 10s vs 22m 26s

SDO CS Coordinate Transform

Neustar’s ElementOne on 12c SDO_GEOM.VALIDATE_GEOM Benchmarks

•  Validate all US county geometries

0

5

10

15

20

25

30

35

11g 12c 12c SVA

1.9x faster performance 15s vs 29s

SDO_GEOM Validate Geometry with Context

• Reduction in redo/undo generation using global temporary tables resulting in 1.7x performance boost

•  2x performance gains with inline PL/SQL functions • Up to 10x faster processing time with constructing large

CLOBs / BLOBs •  Faster response times with cross session result set

cache

Neustar’s ElementOne on 12c Miscellaneous Features

Q&A