Apache Spark with Java - Learn Spark from a Big Data Guru [Video]

More Information
  • An overview of the architecture of Apache Spark.
  • Work with Apache Spark's primary abstraction, resilient distributed datasets(RDDs) to process and analyze large datasets.
  • Develop Apache Spark 2.0 applications using RDD transformations and actions, and Spark SQL.
  • Scale up Spark applications on a Hadoop YARN cluster through Amazon's Elastic MapReduce service.
  • Analyze structured and semi-structured data using Datasets and DataFrames, and develop a thorough understanding of Spark SQL.
  • Share information across different nodes on an Apache Spark cluster by broadcast variables and accumulators.
  • Learn advanced techniques to optimize and tune Apache Spark jobs by partitioning, caching and persisting RDDs.
  • Learn best practices for working with Apache Spark in the field.

This course covers all the fundamentals of Apache Spark with Java and teaches you everything you need to know about developing Spark applications with Java. At the end of this course, you will have gained an in-depth knowledge pf Apache Spark, general big data analysis and manipulations skills. With these new skills you'll be able to help your company to adapt Apache Spark for building a big data processing pipeline and data analytics applications. This course covers 10+ hands-on big data examples. You will learn valuable knowledge on how to frame data analysis problems as Spark problems. Together we will learn examples such as aggregating NASA Apache web logs from different sources; we will explore the price trend by looking at the real estate data in California; we will write Spark applications to find out the median salary of developers in different countries through the Stack Overflow survey data; we will develop a system to analyze how maker spaces are distributed across different regions in the United Kingdom, and much more.

Style and Approach

This course is very hands-on, James has put in lots of effort to provide you with not only the theory but also real-life examples of developing Spark applications that you can try out on your own laptop.

  • You will gain an in-depth knowledge of Spark, general big data analysis, and data manipulation skills.
  • You'll be able to develop Spark application that analyzes gigabytes of data both on your laptop, and in the cloud using Amazon's Elastic MapReduce service.
Course Length 3 hours 20 minutes
ISBN 9781788994330
Date Of Publication 8 Apr 2018


James Lee

James Lee is a passionate software wizard working at one of the top Silicon Valley-based start-ups specializing in big data analysis. He has also worked at Google and Amazon. In his day job, he works with big data technologies, including Cassandra and Elasticsearch, and is an absolute Docker geek and IntelliJ IDEA lover. Apart from his career as a software engineer, he is keen on sharing his knowledge with others and guiding them, especially in relation to start-ups and programming. He has been teaching courses and conducting workshops on Java programming / IntelliJ IDEA since he was 21. James also enjoys skiing and swimming, and is a passionate traveler.

Tao W.

Tao W. is a passionate software engineer who works in a leading big data analysis company in Silicon Valley. Previously Tao worked in big IT companies such as IBM and Cisco. Tao has a MS degree in Computer Science from University of McGill and many years of experience as a teaching assistant for various computer science classes. When Tao is not working, Tao enjoys reading and swimming, and he is a passionate photographer. In Level up, they aim to teach technology the way it is used in the industrial world. The Level up Big Data program is established to deliver high-quality data analytics courses from industry experts and influencers. Level UP was founded by James Lee and Tao W.