Apache Spark Streaming 3 with Scala
Apache Spark Streaming 3 with Scala, available at $39.99, has an average rating of 4.7, with 21 lectures, based on 696 reviews, and has 6335 subscribers.
You will learn about Process data as it arrives Handle data of any scale in real time Use Structured Streaming and SQL on streaming data Use low-level, high-control APIs with DStreams Integrate Spark with Kafka, JDBC, Cassandra Master advanced concepts including window functions and watermarking This course is ideal for individuals who are Scala & Spark programmers who need to set up data pipelines in real time or Data scientists who need to work with streaming data It is particularly useful for Scala & Spark programmers who need to set up data pipelines in real time or Data scientists who need to work with streaming data.
Enroll now: Apache Spark Streaming 3 with Scala
Summary
Title: Apache Spark Streaming 3 with Scala
Price: $39.99
Average Rating: 4.7
Number of Lectures: 21
Number of Published Lectures: 21
Number of Curriculum Items: 21
Number of Published Curriculum Objects: 21
Original Price: $39.99
Quality Status: approved
Status: Live
What You Will Learn
- Process data as it arrives
- Handle data of any scale in real time
- Use Structured Streaming and SQL on streaming data
- Use low-level, high-control APIs with DStreams
- Integrate Spark with Kafka, JDBC, Cassandra
- Master advanced concepts including window functions and watermarking
Who Should Attend
- Scala & Spark programmers who need to set up data pipelines in real time
- Data scientists who need to work with streaming data
Target Audiences
- Scala & Spark programmers who need to set up data pipelines in real time
- Data scientists who need to work with streaming data
In this course, we will learn how to stream big data with Apache Spark 3. You’ll write 1500+ lines of Spark code yourself, with guidance, and you will become a rockstar.
This course is for Spark & Scala programmers who now need to work with streaming data, or who need to process data in real time.
Why Spark in Scala:
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it’s blazing fast for big data
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its demand has exploded
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it’s a highly marketable skill
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it’s well maintained, with dozens of high-quality extensions
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it’s a foundation for a data scientist
I like to get to the point and get things done. This course
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deconstructs all concepts into the critical pieces you need
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selects the most important ideas and separates them into what’s simple but critical and what’s powerful
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sequences ideas in a way that “clicks” and makes sense throughout the process of learning
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applies everything in live code
The end benefits are still much greater:
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a completely new mental model around data streaming
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significantly more marketable resume
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more enjoyable work – Spark is fun!
This course is for established programmers with experience with both Scala and Spark at least at the level of the Rock the JVM essential courses for Scala and Spark. I already assume a solid understanding of general programming fundamentals.
This course is NOT for you if
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you’ve never written Scala or Spark code before
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you don’t have some essential parallel programming background (e.g. what’s a process/a thread)
The course is comprehensive, but you’ll always see me get straight to the point. So make sure you have a good level of focus and commitment to become a badass programmer.
I believe both theory and practice are important. That’s why you’ll get lectures with code examples, real life code demos and assignments, plus additional resources, instructions, exercises and solutions. At the end of the course, you’ll have written thousands of lines of Spark.
I’ve seen that my students are most successful – and my best students work at Google-class companies – when they’re guided, but not being told what to do. I have exercises waiting for you, where I offer my (opinionated) guidance but otherwise freedom to experiment and improve upon your code.
Definitely not least, my students are most successful when they have fun along the way!
So join me in this course and let’s rock the JVM!
Course Curriculum
Chapter 1: Getting Started
Lecture 1: Welcome
Lecture 2: How to Make the Best out of This Course
Lecture 3: Scala Recap
Lecture 4: Spark Recap
Lecture 5: Spark Streaming First Principles
Chapter 2: Spark Structured Streaming
Lecture 1: Streaming DataFrames
Lecture 2: Streaming Aggregations
Lecture 3: Streaming Joins
Lecture 4: Streaming Datasets
Chapter 3: Low-Level Spark Streaming with DStreams
Lecture 1: DStreams
Lecture 2: DStreams Transformations
Chapter 4: Spark Streaming Integrations
Lecture 1: Kafka & Structured Streaming
Lecture 2: Kafka & DStreams
Lecture 3: JDBC with PostgreSQL
Lecture 4: Cassandra
Chapter 5: Advanced Spark Streaming
Lecture 1: Event Time Windows
Lecture 2: Event Time Windows: Exercises
Lecture 3: Processing Time Windows
Lecture 4: Watermarking
Lecture 5: Watermarking, part 2
Chapter 6: Epilogue
Lecture 1: You ROCK!
Instructors
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Daniel Ciocîrlan
Software Engineer & Best-Selling Instructor
Rating Distribution
- 1 stars: 4 votes
- 2 stars: 5 votes
- 3 stars: 37 votes
- 4 stars: 227 votes
- 5 stars: 423 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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