Streaming Big Data with Spark Streaming & Scala

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.

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.

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.

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.

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.

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.

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.

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.

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.