Presented By O'Reilly and Cloudera
Make Data Work
Feb 17–20, 2015 • San Jose, CA

Scalable Realtime Analytics with declarative SQL like Complex Event Processing Scripts

2:20pm–3:00pm Thursday, 02/19/2015
Location: 210 D/H
Average rating: **...
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Slides:   1-PPT 

We hear about lot of success stories with batch processing ranging from business analytics to urban planning. There are many use cases like traffic, patient monitoring, surveillance where it is much more useful have oversight over developments as they happen. With more and more people realizing the value of Realtime analytics, the race to build realtime middleware has begun. Among the contenders are Stream Processing systems like Apache Storm and Samza, Complex Event Processing (CEP) Systems like WSO2 CEP and Esper, and Micro Batch systems like Spark.

Currently, most implementations focus on programming set of processing nodes and connecting them with a framework like Storm, which forces users to write code, and re-implement tricky concepts like time windows and stream joins. If you look for batch processing world, MapReduce is exactly like that. In Batch world there is an alternative in the form of Hive, where users write SQL like scripts that get processed as MapReduce jobs, and Hive let you write and wire up complex queries in few lines.

Complex Event Processing plays the same role for realtime analytics, where it provides SQL like declarative queries and high level operators like time window, stream joining, temporal patterns. Its adoption can let users write complex queries in few lines and wire them up easily.

Historically CEP has focused on ultra fast response times and execution on one or few nodes as oppose to Stream processing systems that focus on large scale executions. In this talk first we will see how CEP languages can handle Realtime Analytics and how they let you express complex queries in few lines. Then we will discuss a scalable CEP engine that let users write their queries using declarative SQL like CEP query language, but let them execute those queries using a graph of CEP nodes deployed on top of Apache Storm, which give us the best of both worlds.

This session is sponsored by WSO2

Photo of Srinath Perera

Srinath Perera


Dr Srinath Perera, is a Director of Research at WSO2 Inc., where he overlooks the overall WSO2 platform architecture with the CTO. He is a co-founder of Apache Axis2, a member
of the Apache Software foundation, and a member of the Apache Web Service Project Management Committee. Srinath also serves as a research scientist at the Lanka Software Foundation and teaches as visiting faculty at the Department of Computer Science and
Engineering, University of Moratuwa. He is a frequent technical speaker and author of many academic and technical publications. He has authored two books “Hadoop Cookbook” and “Instant MapReduce Patterns.”