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

Learn analyzing large data sets with Apache Spark by 10+ hands-on examples. Take your big data skills to the next level.

Created by: Tao W.
Software engineer

Created by: James Lee
Silicon Valley Software Engineer

Created by: Level Up
Your Professional Learning Partner

Created by: Jiarui Zhou
Instructor at Udemy, top 10% in Euclid Contest

What Will I Learn?

• An overview of the architecture of Apache Spark.
• Work with Apache Spark's primary abstraction, resilient distributed datasets(RDDs) to process and analyze large data sets.
• 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 about Spark SQL.
• Share information across different nodes on a Apache Spark cluster by broadcast variables and accumulators.
• Advanced techniques to optimize and tune Apache Spark jobs by partitioning, caching and persisting RDDs.
• Best practices of working with Apache Spark in the field.

Requirements

• A computer running Windows, OSX or Linux
• Previous Java programming skills
• Java 8 experience is preferred but NOT required

Target audience

• Anyone who want to fully understand how Apache Spark technology works and learn how Apache Spark is being used in the field.
• Software engineers who want to develop Apache Spark 2.0 applications using Spark Core and Spark SQL.
• Data scientists or data engineers who want to advance their career by improving their big data processing skills.