Apache Spark And Scala Training in Exeter

Apache Spark and Scala Training​ Course outline

Module 1: Introduction to Scala

• Introduction to Scala and Development of Scala for Big Data Applications
• Apache Spark

Module 2: Pattern Matching

• Introduction to Pattern Matching
• Uses of Scala
• Concept of REPL (Read Evaluate Print Loop)
• Deep Drive into Scala Pattern Matching
• Type Interface and Higher-Order Function
• Currying and Traits

Module 3: Executing the Scala Code

• Introduction to Scala Interpreter
• Creating Static Members with Companion Objects
• Implicit Classes in Scala
• Different Classes in Scala

Module 4: Classes Concepts in Scala

• Understanding the Constructor Overloading
• Different Abstract Classes
• Hierarchy Types in Scala
• Concept of Object Equality and Val and Var Methods in Scala​

Module 5: Concepts of Traits with Example

• Introduction to Traits in Scala ​
• When to Use Traits?​
• Linearisation of Traits and the Java Equivalent ​
• Boilerplate Code​

Module 6: Scala Java Interoperability and Scala Collection​

• Implementation of Traits in Scala and Java​
• Handling of Multiple Traits Extending​
• Introduction to Scala Collections​
• Classification of Collections ​
• Difference Between Iterator and Iterable in Scale
• List and Sequence in Scala

Module 7: Mutable Collections vs Immutable Collections

• Types of Collections in Scala
• Lists and Arrays in Scala
• List Buffer and Array Buffer
• Queue in Scala
• Stacks and Sets
• Maps and Tuples in Scala

Module 8: Introduction to Spark

• What are Spark and Spark Stack?
• Ways to Resolve Hadoop Drawbacks
• Interactive Operations on Map Reduce
• Spark Hadoop YARN
• HDFS and YARN Revision
• How it is Better Hadoop?
• Deploying Spark Without Hadoop
• Spark History Server
• Cloudera Distribution

Module 9: Spark Basics

• Spark Installation
• Memory Management
• Concept of Resilient Distributed Datasets (RDD)​
• Functional Programming in Spark​

Module 10: Working with RDDs in Spark​

• Creating RDDs ​
• Operations and Transformation in RDD ​
• RDD Partitioning ​
• FlatMap Method ​
• Scala Map Count ​
• Saveastextfiles
• Pair RDD Functions

Module 11: Aggregating Data with Pair RDDs ​

• Introduction to Key-Value Pair in RDDs ​
• How Spark Makes Map-Reduce Operations Faster?​

Module 12: Writing and Deploying Spark Applications​

• Difference Between Spark and Scala
• Set and Set Operations
• List and Tuple
• Concatenating List
• Install Apache Maven

Module 13: Parallel Processing

• Spark Parallel Processing
• Setup Spark Master Code
• Introduction to Spark Partitions
• Data Locality in Hadoop
• Comparing Repartition and Coalesce
• Actions of Spark

Module 14: Spark RDD Persistence

• Execution Flow in Spark
• RDD Persistence Overview
• Spark Terminology
• Distribution Shared Memory vs RDD
• ReduceByKey and SortByKey and AggregateByKey

Module 15: Spark Streaming and Mila

• Introduction to Spark Streaming
• What is Spark Streaming?
• Aspects of Spark Streaming
• How does Spark Streaming Work?
• Broadcast Variables
• Accumulator

Module 16: Spark Variables and RDD Operations

• Variables in Spark
• Numeric RDD Operations

Module 17: Scheduling or Partitioning

• Partitioning in Spark
• Hash Partition and Range Partition
• Scheduling within and Around Applications
• Map Partition with Index
• GroupByKey
• Spark Master High Availability
• Standby Masters with Zookeeper

Who should attend this Apache Spark and Scala Training Course?

The Apache Spark and Scala Training Course is a specialised  that helps professionals to gain expertise in the Big Data Analytics and Distributed Computing sector. This course can be beneficial for a wide range of professionals, including:

• Software Developer
• Data Scientists
• Data Engineers
• Business Analysts
• Systems Architects
• Database Administrators
• Data Journalists
• Project Managers

Prerequisites of the Apache Spark and Scala Training Course

For attending this Apache Spark and Scala Training Course, a basic knowledge of Java, Database, Query Language, and SQL would be beneficial for delegates.

Apache Spark and Scala Training Course Overview

Apache Spark and Scala have emerged as pivotal tools in the world of Big Data Processing and Analytics. Apache Spark is a robust open-source data processing framework combined with Scala, a high-performance programming language that offers a scalable solution. This course is designed for software developers and IT professionals who can benefit from understanding these technologies to build efficient data processing pipelines.

Proficiency in Apache Spark and Scala is crucial in today's data-driven landscape. It empowers data engineers, data scientists, and analysts to process and analyse large datasets swiftly, enabling data-driven decision-making. For professionals in fields like data science, machine learning, and big data analytics, mastering Spark and Scala is essential.

This intensive 2-day training is designed to provide delegates with a solid foundation in Apache Spark and Scala. Delegates will gain hands-on experience in working with these technologies, learning to develop efficient data processing pipelines, working with distributed datasets, and applying advanced analytics techniques. The course combines theoretical knowledge with practical exercises, ensuring that delegates can immediately apply what they learn in their professional roles.

Course Objectives

• To learn how to work with distributed data using Spark RDDs
• To explore Spark's DataFrame and Dataset APIs for structured data processing
• To master the art of data manipulation, transformation, and analysis with Spark
• To develop Spark applications and perform data processing tasks
• To discover the integration of Spark with popular data sources and tools
• To implement real-world use cases and best practices for Spark and Scala

Upon completing this course, delegates will benefit from a solid foundation in Apache Spark and Scala. They will possess the practical skills and knowledge required to handle and analyse big data effectively, enabling them to excel in their data analytics roles. This course is a valuable investment in their professional development and opens doors to various opportunities in the world of big data analytics.

What’s included in this Apache Spark and Scala Training Course?

• World-Class Training Sessions from Experienced Instructors
• Apache Spark and Scala Certificate
• Digital Delegate Pack