Stream and event processing using Apache Spark: Melbourne, 11–12 April 2019
April 11 @ 9:30 am - April 12 @ 5:00 pm
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Developed by Jeffrey Aven, author of SAMS Teach Yourself Apache Spark and Data and Analytics with Spark using Python, this course will provide the core knowledge and skills required to develop applications using Apache Spark.
The “Stream and Event Processing Using Apache Spark” module is the second of three modules in the “Big Data Development Using Apache Spark” series, following the “Data Transformation and Analysis using Apache Spark” module and preceding the “Advanced Analytics Using Apache Spark” module.
This course provides the conceptual and practical knowledge required to develop real time and event driven (or event oriented) processing applications using Apache Spark. The course covers using Spark with NoSQL systems as well as popular messaging platforms such as Apache Kafka and Amazon Kinesis.
The Spark streaming architecture is covered in depth using the DStream API as well as structured streaming in Spark. Practical hands-on exercises are provided to reinforce the usage of transformations and output operations in Spark streaming, as well as more advanced stream processing patterns such as stateful stream processing and sliding window operations using Spark.
Topics covered include:
- Introduction to NoSQL systems
- Using Spark with HBase
- Using Spark with DynamoDB
- Introducing spark streaming and the DStream API
- DStream sources
- DStream transformations and output operations
- Stateful stream processing
- Sliding window operations
- Using Spark with Apache Kafka
- Using Spark with Amazon Kinesis
- Event sourcing using Spark
- Structured streaming with Spark
Who should attend?
This course is suitable for developers and analysts who will be developing real time or event oriented applications using Spark; this could include IoT applications, real-time fraud applications and more. The course is designed for developers and analysts who have a basic level of competence with Spark programming using the RDD and DataFrame APIs.
- General programming skills
- Basic Python programming skills
- Basic Spark skills and knowledge (ability to program basic RDD and DataFrame applications in Spark)
Attendees should, by the end of the course:
- Understand the Spark streaming framework and runtime architecture
- Understand the fundamentals of stream programming in Spark using both DStreams and structured streaming
- Understand stream processing patterns including stateful and sliding window operations
- Be able to use messaging (such as Kafka) and NoSQL platforms (such as HBase) as a source or target for event/stream processing applications
The instructor: Jeffrey Aven
Jeffrey Aven is a big data, open source software, and cloud computing consultant, author and instructor based in Melbourne, Australia.
Jeffrey has extensive experience as a technical instructor, having taught courses on Hadoop and HBase for Cloudera (awarded Cloudera Hadoop Instructor of the Year for APAC in 2013) and courses on Apache Kafka for Confluent in addition to delivering his own courses.
Jeffrey is also the author of several Big Data related books including SAMS Teach Yourself Hadoop in 24 Hours, SAMS Teach Yourself Apache Spark in 24 Hours and Data Analytics with Spark using Python.
In addition to his credentials as an instructor and author, Jeff has over thirty years of industry experience and has been involved in key roles with several major big data and cloud implementations over the last several years.
Earlybird pricing is available until 14 March 2019.
Group discounts also apply during the earlybird period: 5% for 2–4 people, 10% for 5–6 people, 15% for 7–8 people, and 20% for 9 or more people. Select your desired quantity of tickets and click “Add to cart” to see the discount calculated before checkout.
About our training
Eugene Dubossarsky’s courses are unlike those offered in universities, online, or by private providers. His data-science classes, in particular, give clients not just knowledge of a process, but the real power of understanding the underlying concepts, allowing them to confidently practice, manage, promote and risk-assess data science.
Dr Dubossarsky says “the way many courses teach data science is like teaching people to memorise and recite poetry in a language they do not understand”. By contrast, he confers an understanding of that language, taught in an intuitive, accessible way that leaves trainees with an instinct for data science. Keeping formulae and mathematics to a bare minimum and taking an intuitive, visual approach, Eugene’s courses deliver a compressed mentoring experience as much as they do content. This is difficult for an average trainer to replicate. Trainees benefit from his extensive knowledge and over 20 years of commercial data-science experience, as well as his unique teaching style.
The resulting testimonials speak for themselves, and candidates come from all walks of life: CEOs, general managers, salespeople, IT professionals, marketing staff, public servants and of course people from many functions in the finance world. These testimonials are extensive, and many more are available on request. With specific regard to finance, Eugene has mentored and advised senior leaders and their teams in a number of major Australian banks.
Questions and further details
Meals and refreshments
Catered morning tea and lunch are provided on both days of the course. Please notify us at least a week ahead if you have any special dietary requirements.
Use email@example.com to email us any questions about the course, including requests for more detail, or for specific content you would like to see covered, or queries regarding prerequisites and suitability.
If you would like to attend but for any reason cannot, please also let us know.
Course material may vary from advertised due to demands and learning pace of attendees. Additional material may be presented, along with or in place of advertised.
Cancellations and refunds
You can get a full refund if you cancel 2 weeks or more before the course starts. No refunds will be issued for cancellations made less than 2 weeks before the course starts.
Frequently asked questions (FAQ)
Do I need to bring my own computer?
There’s no need to bring your own laptop or PC. Our courses take place in modern, professional training facilities that have all the computing equipment you’ll need.
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