Oracle Streamexplorer Simplifying Event/Stream Processing Vortrag an der DOAG 2015 von Guido Schmutz

1. BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA
HAMBURG COPENHAGEN LAUSANNE MUNICH STUTTGART VIENNA ZURICH
Oracle Stream Explorer
Simplifying Event/Stream Processing
Guido Schmutz

2. Guido Schmutz
Working for Trivadis for more than 18 years
Oracle ACE Director for Fusion Middleware and SOA
Co-Author of different books
Consultant, Trainer Software Architect for Java, Oracle, SOA and
Big Data / Fast Data
Member of Trivadis Architecture Board
Technology Manager @ Trivadis
More than 25 years of software development experience
Contact: guido.schmutz@trivadis.com
Blog: http://guidoschmutz.wordpress.com
Twitter: gschmutz

3. Unser Unternehmen.
© Trivadis – Das Unternehmen3 24.11.15
Trivadis ist führend bei der IT-Beratung, der Systemintegration, dem Solution
Engineering und der Erbringung von IT-Services mit Fokussierung auf -
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4. KOPENHAGEN
MÜNCHEN
LAUSANNE
BERN
ZÜRICH
BRUGG
GENF
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DÜSSELDORF
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STUTTGART
FREIBURG
BASEL
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© Trivadis – Das Unternehmen4 24.11.15
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pro Jahr bei über 800 Kunden.

5. Agenda
1. Motivation
2. Oracle Stream Explorer Overview
3. Oracle Stream Explorer Terminology
4. Demo

6. Motivation

7. “Streaming analytics is anything but a sleepy, rear
view mirror analysis of data.”

9. Oracle Stream Explorer Overview

10. Oracle Stream Explorer Platform
What it does
• Compelling, friendly and visually stunning real
time streaming analytics user experience for
Business users to dynamically create and
implement Instant Insight solutions
Key Features
• Analyze simulated or live data feeds to determine
event patterns, correlation, aggregation & filtering
• Pattern library for industry specific solutions
• Streams, References, Maps & Explorations
Benefits
• Accelerated delivery time
• Hides all challenges & complexities of underlying
real-time event-driven infrastructure

11. Oracle Stream Explorer - Connecting Everything &
Anything of Interest to the Business
Understanding of CQL Filtering, Correlation, Pattern: NOT NEEDED
Understanding of IT Deployment and Management: NOT NEEDED
Understanding of Development, Java, Best Practices: NOT NEEDED
Understanding of the Event Driven Platform: NOT NEEDED

12. Sensor patterns from physical and
environmental, Geospatial
movement, location based
• High Availability / Scalability
• Coherence Integration
• Geospatial, Geofencing
• Big Data Integration
• SOA infrastructure integration
• Business Event
Visualization
• Action!
OEA
• Filtering
• Correlation
• Aggregation
• Pattern
matching
Devices /
Gateways
Services
Computing Edge Enterprise
“Sea of data”
Macro-event
High-value
Actionable
In-context
EDGE
Analytics
Stream
Explorer
Exalogic
Single Node Performance
1+ Million Events/Second
Sparc T5
Performance
4 Million Events/Second
Cloud Service*
Stream Explorer
Enterprise
* Future planned Features
FOG
Evolving Self Aware, Self Discovery Elastic Fast
Data Streaming Infrastructure
• High Volume
• Continuous Streaming
• Extreme Low Latency
• Disparate Sources
• Temporal Processing
• Pattern Matching
• Machine Learning
Fast Data
Events Actions
1 2 3
Streams

13. Business accessibility to Geo-Streaming, Spatial Analytics
“ Real Time Streaming Solutions face an increasing need to track "assets of interest" and
initiate actions based on encroachment of boundary proximity to fixed and moving objects
and other geographic, temporal, or event conditions”
Geo-Fence, Fence, PolygonGeo-Streaming

14. Expression Builder enabling Column
manipulation, Calculation for the Business
User
“ Add value to your real time streaming data discovery and analytics by applying and including
mathematical, statistical analysis to the live output stream”
“These streaming “Excel spreadsheets” really do come to life”

15. Easily choose your Business Analytics paradigm : Streaming
Temporal Queries or Business Rule Semantics

16. Array of re-usable Real Time Insight Business Patterns
Oracle Stream Explorer provides a feature known as patterns.
1. A pattern provides you with the results displayed in a live
output stream based on common business scenarios
2. A pattern is a template of an Oracle Stream Explorer
Platform Application that already has the business logic
built into it
3. The visual representation of the event stream varies from
one pattern type to another based on the key fields you
choose

17. Stream Explorer Terminology

18. Stream Explorer – Terminology for Business Users
Explorer: The Application User Interface

19. Stream Explorer – Terminology for Business Users
Catalog: The repository for browsing resources

20. Stream Explorer – Terminology for Business Users
Shape: A blueprint of an event in a stream or data in a data source. How the business
data is represented in the selected stream

21. Stream Explorer – Terminology for Business Users
Reference: A connection to static data that is joined to a stream to enrich it and/or to be
used in business logic and output

22. Stream Explorer – Terminology for Business Users
Stream: An incoming flow of events that you want to analyze, for example a stream of
JMS, EDN events or simulated Business Events from an CSV file

23. Stream Explorer – Terminology for Business Users
Exploration: An application that correlates events from streams, data from data
sources, even other Explorations. It uses filters, groupings, summaries, ranges, and
more to Identify, Qualify and Expose a Real Time Business Solution

24. Relationship between Streams (Sources), References
and Explorations

25. Stream Explorer – Terminology for Business Users
Pattern: A pre-built Exploration that addresses a particular business scenario in a
focused and simplified User Interface

26. Demo

27. Summary

28. Summary
Stream Explorer leverages the capabilities found in Oracle Event Processing (OEP)
Empowering Business users to gain insight into real-time information and take
appropriate actions when needed => makes stream processing accessible
Makes Stream/Event Processing less technical => “Excel spread sheet” on Streams
Part of Oracle IoT Cloud Service
Will support Spark Streaming as a deployment platform in the future
Interesting road map: Rule Engine, Machine Learning, Extensible Patterns

29. © Trivadis – Das Unternehmen29 11/24/15
Trivadis an der DOAG 2015
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Wir freuen uns auf Ihren Besuch.
Denn mit Trivadis gewinnen Sie immer.

30. Guido Schmutz
Technology Manager
guido.schmutz@trivadis.com