MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 3.5 Hours | Lec: 51 | 437 MB
Genre: eLearning | Language: English
Learn Apache Spark and Scala by 12+ hands-on examples of analyzing big data
What is this course about:
This course covers all the fundamentals about Apache Spark with Scala and teaches you everything you need to know about developing Apache Spark applications with Scala Spark. At the end of this course, you will gain in-depth knowledge about Apache Spark Scala and general big data analysis and manipulations skills to help your company to adapt Apache Scala Spark for building big data processing pipeline and data analytics applications.
This course covers 10+ hands-on big data examples involving Apache Spark. You will learn valuable knowledge about how to frame data analysis problems as Scala 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
Scala 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 Scala 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 Apache 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 Apache Spark SQL.
Share information across different nodes on an Apache Spark cluster by broadcast variables and accumulators.
Best practices of working with Apache Spark Scala 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.
Apache Scala 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.
What programing language is this course taught in?
This course is taught in Scala. Scala is the next generation programming language for functional programing that is growing in popularity and it is one of the most widely used languages in the industry to write Apache Spark programs.