In the fast-evolving world of big data, the ability to process streaming data in real time is essential. This course is meticulously designed to take you from the basics of Spark and Scala to advanced real-time data processing with Spark Streaming. We begin with a foundational setup of your development environment, ensuring you are equipped to run Spark and Scala on your desktop. A hands-on activity will introduce you to the excitement of live data by streaming and analyzing real-time Tweets.
Streaming Big Data with Spark Streaming, Scala, and Spark 3!
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Streaming Big Data with Spark Streaming, Scala, and Spark 3!
Instructor: Packt - Course Instructors
Included with 
Gain insight into a topic and learn the fundamentals.
Advanced level
Recommended experience
8 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Identify key components of the Spark and Scala development environment.
Explain the core concepts of Scala and Spark, including Resilient Distributed Datasets (RDDs) and windowing mechanisms.
Differentiate between various data integration techniques with Spark Streaming, such as Kafka, Flume, and Cassandra.
Assess the performance and reliability of Spark Streaming applications in production environments.
Skills you'll gain
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Recently updated!
October 2024
Assessments
4 assignments
Taught in English
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There are 9 modules in this course
In this module, we will introduce you to the course, guide you through setting up your development environment, and ensure that Spark and Scala are installed correctly on your system. You will also dive into a hands-on activity where you will stream live Tweets using Spark Streaming.
What's included
2 videos1 reading
In this module, we will dive into the fundamentals of Scala, starting with the basics like variables and flow control. You’ll then progress to functions and essential data structures, equipping you with the Scala knowledge necessary to work effectively with Spark.
What's included
4 videos
In this module, we will build upon your knowledge of Spark and introduce you to Spark Streaming in detail. You'll explore key concepts like RDDs, windowing, and fault tolerance while running hands-on activities that solidify your understanding of real-time data processing.
What's included
7 videos1 assignment
In this module, we will apply Spark Streaming to real-world scenarios using Twitter data. You'll progress from saving tweets to disk, to computing tweet statistics like average length, and finally, tracking trending hashtags in real-time, providing practical insights into Spark Streaming's capabilities.
What's included
3 videos
In this module, we will dive into practical examples of Spark Streaming with Apache access logs and clickstream data. You'll learn to track popular URLs, monitor errors, integrate Spark Streaming with SQL, and explore Structured Streaming to analyze logs in real time, giving you a robust toolkit for handling streaming data.
What's included
5 videos
In this module, we will explore how to integrate Spark Streaming with various external systems like Apache Kafka, Apache Flume, Amazon Kinesis, and Cassandra. You’ll also learn how to create custom data receivers for proprietary systems, giving you the skills to connect Spark Streaming with almost any data source.
What's included
5 videos1 assignment
In this module, we will delve into advanced Spark Streaming concepts, focusing on stateful information processing and the integration of machine learning techniques like K-means clustering and linear regression. You'll gain hands-on experience with these powerful tools, enabling you to build sophisticated real-time data processing applications.
What's included
3 videos
In this module, we will take your Spark Streaming applications to production, covering the essentials of packaging, deploying, and running your code on real clusters. You'll learn how to manage dependencies with SBT, deploy on Amazon EMR, and troubleshoot and optimize your jobs for reliable, high-performance operation in a production environment.
What's included
4 videos1 assignment
In this module, we will offer you guidance on how to continue your learning journey with Spark Streaming, including valuable resources and next steps. You'll also reflect on your progress and plan how to integrate your newfound knowledge into real-world applications.
What's included
1 video1 assignment
Instructor
Offered by
Recommended if you're interested in Data Analysis
Coursera Project Network
University of California San Diego
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Frequently asked questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.