Apache Spark and Scala Online Course
Apache Spark and Scala Online Exam
About Apache Spark and Scala Online Course
This online course provides comprehensive training on Apache Spark with Scala, equipping you with the skills to develop Spark applications for big data processing and analytics. By the end, you'll have in-depth knowledge of Spark fundamentals and be able to apply it to real-world scenarios. The course includes hands-on projects, such as analyzing NASA Apache web logs, exploring real estate price trends, calculating median salaries from Stack Overflow data, and mapping maker spaces in the UK. Scala, a popular language for Spark applications, will be the primary tool for learning how to model big data problems effectively.
Key Benefits
- Apache Spark offers unparalleled capabilities for building advanced applications, positioning it as one of the most transformative technologies of the past decade within the big data landscape.
- Spark leverages in-memory cluster computing, significantly enhancing the performance of iterative algorithms and interactive data mining tasks, making it the next-generation processing engine for handling large-scale data.
- A growing number of organizations are adopting Apache Spark to derive insights from vast datasets, and now you have the opportunity to harness this powerful big data technology directly on your desktop. As a result, Apache Spark has become an essential tool for data engineers and data scientists alike.
Target Audience
This course is ideal for individuals seeking a comprehensive understanding of how Apache Spark technology operates and how it is applied in real-world scenarios. It is particularly beneficial for software engineers aiming to develop Apache Spark 2.0 applications using Spark Core and Spark SQL. Additionally, data scientists and data engineers looking to enhance their career prospects by advancing their big data processing skills will find this course highly valuable.
Learning Objectives
- Gain a comprehensive understanding of the architecture of Apache Spark.
- Learn to work with Spark’s core abstraction, resilient distributed datasets (RDDs), to process and analyze large data sets.
- Develop Apache Spark 2.0 applications using RDD transformations, actions, and Spark SQL.
- Scale Spark applications on a Hadoop YARN cluster using Amazon's Elastic MapReduce service.
- Analyze structured and semi-structured data with Datasets and DataFrames, gaining a deep understanding of Spark SQL.
- Learn to share data across different nodes in a Spark cluster using broadcast variables and accumulators.
- Master advanced techniques to optimize and tune Apache Spark jobs, including partitioning, caching, and persisting RDDs.
- Understand the best practices for effectively using Apache Spark in real-world applications.
Course Topics
The Apache Spark and Scala Online Course covers the following topics -
Domain 1 - Getting Started with Apache Spark
- Overview of the Course
- Introduction to Apache Spark
- Install Java and Git
- Setting up a Spark Project with IntelliJ IDEA
- Running Your First Apache Spark Job
- Troubleshooting: Running Your First Apache Spark Job
Domain 2 - RDD (Resilient Distributed Datasets)
- Introduction to RDDs in Apache Spark
- Creating RDDs
- Map and Filter Transformations in Apache Spark
- Solution to the Airports by Latitude Problem
- FlatMap Transformation in Apache Spark
- Set Operations in Apache Spark
- Solution to the Same Hosts Problem
- Actions in Apache Spark
- Solution to the Sum of Numbers Problem
- Key Considerations for RDDs
- Summary of RDD Operations in Apache Spark
- Caching and Persistence in Apache Spark
Domain 3 - Spark Architecture and Components
- Overview of Spark Architecture
- Key Components of Spark
Domain 4 - Pair RDD in Apache Spark
- Introduction to Pair RDDs in Spark
- Creating Pair RDDs in Spark
- Filter and MapValue Transformations on Pair RDDs
- ReduceByKey Aggregation in Apache Spark
- Solution for the Average House Problem
- GroupByKey Transformation in Spark
- SortByKey Transformation in Spark
- Sample Solution for Sorted Word Count Problem
- Data Partitioning in Apache Spark
- Join Operations in Spark
Domain 5 - Advanced Spark Topics
- Introduction to Accumulators
- Solution to StackOverflow Survey Follow-up Problem
- Introduction to Broadcast Variables
Domain 6 - Apache Spark SQL
- Overview of Apache Spark SQL
- Spark SQL in Action
- Spark SQL Practice: House Price Problem
- Spark SQL Joins
- Strongly Typed Datasets
- Using Datasets or RDDs
- Dataset and RDD Conversion
- Performance Tuning for Spark SQL
Domain 7 - Running Spark in a Cluster
- Introduction to Running Spark in a Cluster
- Packaging Spark Applications and Using spark-submit
- Running Spark Applications on Amazon EMR (Elastic MapReduce) Cluster
