Apache Spark 2.0 with Java -Learn Spark from a Big Data Guru

What is this course about:

This course covers all the fundamentals about 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 gain in-depth knowledge about Apache Spark and general big data analysis and manipulations skills to help your company to adapt Apache Spark for building big data processing pipeline and data analytics applications.

This course covers 10+ hands-on big data examples. You will learn valuable knowledge about 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 much more.

What will you learn from this lecture:

In particularly, you will learn:

• An overview of the architecture of Apache Spark.

• Develop Apache Spark 2.0 applications with Java using RDD transformations and actions and Spark SQL.

• Work with Apache Spark's primary abstraction, resilient distributed datasets(RDDs) to process and analyze large data sets.

• Deep dive into advanced techniques to optimize and tune Apache Spark jobs by partitioning, caching and persisting RDDs.

• 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.

• Best practices of working with Apache Spark in the field.

• Big data ecosystem overview.

Why shall we learn Apache Spark:

Apache Spark gives us unlimited ability to build cutting-edge applications. It is also one of the most compelling technologies of the last decade in terms of its disruption to the big data world.

Spark provides in-memory cluster computing which greatly boosts the speed of iterative algorithms and interactive data mining tasks.

Apache Spark is the next-generation processing engine for big data.

Tons of companies are adapting Apache Spark to extract meaning from massive data sets, today you have access to that same big data technology right on your desktop.

Apache Spark is becoming a must tool for big data engineers and data scientists.

About the author:

Since 2015, James has been helping his company to adapt Apache Spark for building their big data processing pipeline and data analytics applications.

James' company has gained massive benefits by adapting Apache Spark in production. In this course, he is going to share with you his years of knowledge and best practices of working with Spark in the real field.

Why choosing this course?

This course is very hands-on, James has put lots 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.

James has uploaded all the source code to Github and you will be able to follow along with either Windows, MAC OS or Linux.

In the end of this course, James is confident that you will gain in-depth knowledge about Spark and general big data analysis and data manipulation skills. You'll be able to develop Spark application that analyzes Gigabytes scale of data both on your laptop, and in the cloud using Amazon's Elastic MapReduce service!

30-day Money-back Guarantee!

You will get 30-day money-back guarantee from Udemy for this course.

 If not satisfied simply ask for a refund within 30 days. You will get a full refund. No questions whatsoever asked.

Are you ready to take your big data analysis skills and career to the next level, take this course now!

You will go from zero to Spark hero in 4 hours.

--- **Overview of Course Ratings:** The global course rating stands at an impressive **4.63**. This suggests that the majority of students have found the course to be valuable and engaging. With all recent reviews being positive, it's clear that the course has been well-received among learners with various backgrounds and skill levels. **Pros:** - **Clear Instruction and Examples:** Many users have praised the clarity of the voice narration, the narrative tempo, and the short but representative examples provided in the course. These elements make learning Apache Spark for beginners particularly effective. - **Practical Application:** The ability to see code examples during the course has been highlighted as a significant advantage by several students. This practical approach helps in understanding the concepts better. - **Comprehensive Coverage:** The course material is considered excellent for setting up a basic foundation and leaping ahead in learning Apache Spark, with a strong emphasis on core concepts and RDDs. - **Detailed Explanation:** The step-by-step explanation of topics, particularly for Java8 or other functional programming languages like Scala, has been found to be very helpful for understanding code readability and hands-on application. - **Real-World Relevance:** The course is praised for its high-level overview of Spark operations and for being a quick and efficient learning tool for both newcomers and experienced professionals looking to brush up on their skills. - **Variety of Examples:** The examples provided are diverse enough to relate to business scenarios and spark interest in further exploration of the framework. **Cons:** - **Outdated Content:** Some users have pointed out that the course needs updating to cover recent versions of Spark (3.1 and beyond) and includes new features and goodies that have been introduced. - **Missing Topics:** There are requests for additional topics, particularly in the areas of Spark Streaming and Spark Structured Streaming, to be included in the course. - **Lack of Machine Learning Focus:** A few users suggest that a basic introduction to machine learning with Spark would make the course more complete. - **Presentation Style:** Some users have expressed a preference for a human voice or a third person speaker over the computer-generated voice used in the course, which some found to be less engaging. - **Technical Updates:** There are recommendations for the course to incorporate testing of the Java script used and to provide more practical exercises, especially in the SQL section. - **Course Difficulty Misalignment:** One user mentioned that the course is advanced and not suitable for beginners, indicating that the course description might be misaligned with the actual difficulty level. --- **Final Assessment:** The course has been highly praised for its educational value, practical examples, and comprehensive coverage of Apache Spark for Java users. However, to remain relevant and beneficial for learners at all levels, updates and the inclusion of additional topics such as Spark Streaming, Structured Streaming, and machine learning are recommended. Addressing these concerns would likely enhance the overall learning experience and increase the course's utility for both beginners and experienced professionals in the field of data processing with Apache Spark.