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Janani Ravi

The Complex Event Processing is built on top of the core Flink libraries. It allows you to detect and process patterns in an infinite stream of events, or within a time window. This course will teach you to handle complex event processing for streaming data using Apache Fink.

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The Complex Event Processing is built on top of the core Flink libraries. It allows you to detect and process patterns in an infinite stream of events, or within a time window. This course will teach you to handle complex event processing for streaming data using Apache Fink.

The Apache Flink library supports complex event processing using the Complex Event Processing or the CEP library which is built on top of the Flink core APIs.

In this course, Complex Event Processing Using Apache Flink, you'll learn about complex event processing involving defining patterns that you want to detect and identify in the input stream, either across the stream as a whole or within a certain time window.

First, you'll be introduced to the Pattern API which allows you to define patterns that you want to detect in input streams. You'll create patterns using singleton patterns that match only one event in the input stream, you'll also use looping patterns created using quantifiers that can match multiple events in the input stream.

Next, you'll see how you can specify different kinds of conditions to accept events into your pattern. Simple conditions only look at the properties of an event to perform matching, iterative conditions can look at the previous matched events and even compute statistics on the input stream to accept matching events. You'll see how more complex conditions can be created using combining operations with logical 'AND' and logical 'OR.' You'll also explore the contiguity constraints that we can define on patterns including strict contiguity, relaxed contiguity, and non-deterministic relaxed contiguity.

Finally, you'll see how you can control how many times a particular event matches a pattern using the after match skip strategy. You'll understand the differences between the no skip, skip to next, skip past last event, skip to first, and skip to last strategies. You'll also see how you can perform pattern matching within a time window, and handle partial timed-out matches.

When you're finished with this course, you'll have the skills and the ability to detect patterns in input streams using the pattern API in the Apache Flink Complex Event Processing library.

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What's inside

Syllabus

Course Overview
Getting Started with Complex Event Processing
Understanding and Applying Combining Patterns
Detecting and Processing Complex Patterns
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Good to know

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Develops foundational skills of pattern recognition in event streams using Apache Flink's Complex Event Processing library, which are applicable in data engineering settings
Useful for learners who want to build a foundation in handling complex event processing for streaming data using Apache Flink
Taught by Janani Ravi, who is experienced in teaching and working with the Complex Event Processing library in Apache Flink
Offers hands-on exercises and interactive materials that reinforce learning
Covers essential topics including pattern matching, conditions, and time constraints, providing a comprehensive foundation for working with complex event processing in Apache Flink
Designed for learners who have a basic understanding of Apache Flink's core libraries

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Complex Event Processing Using Apache Flink with these activities:
Review Java fundamentals
Strengthen your Java skills to ensure a solid foundation for the CEP course.
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  • Review basic syntax
  • Practice object-oriented programming
Gather CEP resources
Build a comprehensive resource library by collecting articles, tutorials, and documentation on CEP.
Show steps
  • Search for relevant materials
  • Organize and annotate resources
Review streaming data technologies.
This course heavily utilizes streaming data technologies in the Flink library. Reviewing streaming data technologies will prepare you for the course.
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  • Gather notes and materials from your past courses on streaming data technologies.
  • Review online resources on streaming data technologies, such as articles and tutorials.
  • Practice exercises and examples related to streaming data technologies.
12 other activities
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Show all 15 activities
Connect with CEP professionals
Build a network of CEP experts by reaching out to professionals in the field.
Show steps
  • Identify potential mentors
  • Craft a personalized message
Complete Flink beginner tutorials.
Apache Flink is the primary focus of this course. Completing beginner tutorials on Flink will solidify your understanding of how it works.
Browse courses on Apache Flink
Show steps
  • Identify reputable online resources that provide Flink tutorials for beginners.
  • Follow along with the tutorials, completing all exercises and examples.
  • Document any questions or areas where you need further clarification.
Analyze event sequences
Sharpen CEP analysis skills by identifying and interpreting patterns in event sequences.
Show steps
  • Identify events of interest
  • Detect and extract patterns
  • Interpret the results
Walkthrough Pattern API examples
Enhance understanding of the Pattern API by following interactive tutorials that demonstrate its practical applications.
Show steps
  • Explore pattern creation
  • Apply conditions
  • Manage contiguity
Solve exercises to grasp pattern detection
Solving exercises will help enhance your understanding and strengthen your problem-solving skills in pattern detection using Apache Flink.
Show steps
  • Set aside dedicated practice time.
  • Work through practice problems from various sources, such as online resources or textbooks.
  • Focus on understanding the problem statement and identifying key patterns.
  • Validate your solutions to ensure accuracy.
Solve complex event scenarios
Reinforce CEP fundamentals by solving a variety of realistic complex event scenarios using the Pattern API.
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  • Define the event patterns
  • Identify the conditions
  • Handle contiguity constraints
Develop a simple Flink application.
Developing a simple Flink application allows you to gain hands-on experience and apply concepts from the course.
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Show steps
  • Identify a problem or task that can be solved with a streaming data application.
  • Design a Flink application to address the problem, including data sources, transformations, and outputs.
  • Implement the Flink application in Java or Scala.
  • Test and debug the application to ensure it meets requirements.
Design a CEP application
Solidify CEP concepts by designing and implementing a practical CEP application using Apache Flink.
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  • Define the application requirements
  • Model the input data
  • Create patterns and conditions
  • Handle time windows
  • Implement the CEP logic
Enter a CEP design competition
Challenge your CEP abilities and showcase your skills by participating in a CEP design competition.
Show steps
  • Research competition requirements
  • Develop a unique concept
  • Implement your solution
  • Submit your entry
Contribute to an open source Flink project.
Contributing to an open source Flink project provides you with valuable real-world experience and deepens your understanding of the Flink ecosystem.
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  • Identify an open source Flink project that aligns with your interests and skill level.
  • Familiarize yourself with the project's codebase and contribution guidelines.
  • Discuss your contribution ideas with project maintainers.
  • Implement your contribution and submit a pull request.
  • Address feedback and iterate on your contribution until it is accepted.
Mentor a junior student in Flink.
Mentoring a junior student reinforces your understanding of Flink and enables you to share your knowledge with others.
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Show steps
  • Identify a junior student who is interested in learning about Flink.
  • Establish clear goals and expectations for the mentoring relationship.
  • Regularly meet with the student to provide guidance, support, and feedback.
  • Help the student develop and refine their Flink skills through hands-on projects.
Create or contribute to Flink documentation.
Contributing to Flink documentation improves the resources available to the community and deepens your understanding of the technology.
Show steps
  • Identify areas in the Flink documentation that could be improved or expanded.
  • Create or update documentation content according to the Flink documentation standards.
  • Submit your contribution as a pull request to the Flink documentation repository.

Career center

Learners who complete Complex Event Processing Using Apache Flink will develop knowledge and skills that may be useful to these careers:
Data Engineer
A Data Engineer is responsible for managing, storing, analyzing, and securing large volumes of data for a variety of uses, including data mining, machine learning, and business intelligence. This course covers the fundamentals of complex event processing techniques used in the field of Data Engineering. These techniques are important for quickly detecting patterns in real-time data streams, which allows Data Engineers to build powerful applications.
Data Scientist
Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course covers the fundamentals of complex event processing, particularly how to detect and interpret patterns in large data streams. This is a useful skill for Data Scientists who work with the analysis of real-time data, such as social media feeds or financial transactions.
Software Engineer
Software Engineers apply engineering principles to develop software, which eventually becomes the foundation for products and services. This course gives Software Engineers a foundation in using complex event processing within Apache Flink to enhance the features and efficiency of their software products.
Data Analyst
Data Analysts use data to identify trends and patterns, solve problems, and make recommendations to improve business outcomes. This course covers the fundamentals of complex event processing, which is useful for Data Analysts who work with time-series data, such as financial data or customer behavior data.
Database Administrator
Database Administrators are responsible for managing and maintaining database systems, including data storage, access, and security. This course may be useful for Database Administrators who want to learn more about complex event processing for managing and maintaining databases.
IT Architect
IT Architects design, build, and maintain IT infrastructure for organizations. IT Architects use their knowledge of complex event processing to design systems that can handle high volumes of data in real time.
Information Security Analyst
Information Security Analysts are responsible for protecting an organization's computer systems and networks from unauthorized access, use, disclosure, disruption, modification, or destruction. This course may be useful for Information Security Analysts who want to learn more about complex event processing for detecting and responding to security threats.

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Complex Event Processing Using Apache Flink.
Provides a comprehensive guide to complex event processing (CEP) with distributed stream processing. It covers the basics of CEP and distributed stream processing, as well as more advanced topics such as pattern matching and time windowing. It valuable resource for anyone who wants to learn more about CEP with distributed stream processing.

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