Real Time Data Stream Processing
Stream processing enables companies in every industry to drive intelligence and action in real-time by processing data as it comes in from sources such as IoT devices, customer interactions and order transactions, social media, etc. Use cases for stream processing can broadly be categorized into four areas: streaming analytics, monitoring, leaderboard, and real-time predictions. This course will cover stream processing paradigm, and streaming processing system architecture. Each week, students will build stream processing applications using widely adopted stream processing technologies, such as Apache Kafka, Apache Spark and Apache Flink.
Hien Luu
Head of Machine Learning Platform @ Doordash
Hien Luu is Head of Machine Learning Platform at DoorDash, author of Beginning Apache, and has been teaching at UCSC Extension School for more than 10 years. Previously, Hien was an Engineering Manager at LinkedIn where he helped build big data applications and infrastructure. And before that, Hien was at Uber, where he led the engineering team responsible for building a streaming processing platform to extract actionable business insights.
Stream processing enables companies in every industry to drive intelligence and action in real-time by processing data as it comes in from sources such as IoT devices, customer interactions and order transactions, social media, etc. Use cases for stream processing can broadly be categorized into four areas: streaming analytics, monitoring, leaderboard, and real-time predictions. This course will cover stream processing paradigm, and streaming processing system architecture. Each week, students will build stream processing applications using widely adopted stream processing technologies, such as Apache Kafka, Apache Spark and Apache Flink.
- Introduction to stream processing
- Streaming processing application architecture
- Stream processing techniques
- Stream processing technology landscape
- Overview of Apache Kafka architectures
- Understanding the Kafka programming model
- Setting up and interacting with Apache Kafka
- Apache Spark Structured Streaming Overview
- Interacting with Apache Spark Structured Streaming
- Implement streaming analytics and monitoring applications
- Apache Flink Overview
- Work with Flink streaming processing APIs
- Implement streaming leaderboard and monitoring applications
Hien is one of the best technical instructors that I have ever had. He is able to combine enthusiastic lectures with challenging homework projects, with a devotion to answer any and all questions asked of him with clear and precise responses. Most importantly he teaches a course that has real job market value. I would take further classes from Hien.
Hien is a brilliant, energetic, highly motivated, inspiring manager. He is among those hard to find people, who have technical expertise to tackle any problem in an optimal manner as well as manage people to deliver high impact results. He can easily step into the shoes of developer and solve the problems. His knowledgeable and perceptive insights has really helped me in my time at LinkedIn.
Hien is a rare breed of engineer, taking pride and passion in his work, always willing to branch out in his knowledge and bring that knowledge to bear on something the world has never seen before.
Data Engineers who want to build stream processing applications
Software Engineers who want to incorporate stream processing into their products to extract actionable insights
Familiar with Java programming language
Familiar with big data process, i.e SQL
Familiar with Intellij IDEA community edition, Docker
Able to install Java 11, maven, Docker Desktop
