Apache Spark with Scala Certification Training

✔ Introducing Scala
✔ Use of java virtual machine in Scala
✔ What is object-oriented programming language
✔ What is a functional language
✔ Scala Basics terms
✔ Things to note about Scala
✔ Java Vs Scala

✔ JDK Installation
✔ Scala Installation
✔ Eclipse Installation and Setup
✔ First Spark / Scala application using Eclipse

✔ Advantages of Scala
✔ Data Types in Scala
✔ What all are the companies using Scala
✔ Access Modifiers in Scala

✔ Private
✔ Protected
✔ No-Access Modifier

✔ Hello Word Program
✔ What is class
✔ What is Object
✔ Class Vs Object
✔ Types of variables in Scala (Mutable, Immutable and Final)
✔ Val Vs Var
✔ Operations on Variables

✔ Learning about the classes concept
✔ Understanding the parameters passing
✔ Understanding the overloading
✔ Understanding the overriding
✔ Names Arguments
✔ Class Constructors
✔ Inheritance
✔ Field Override
✔ Method Overriding

✔ Introduction to Scala collections
✔ Classification of collections
✔ The difference between iterator and iterable in Scala
✔ Example of list sequence in Scala

✔ Two types of collections in Scala
✔ Mutable and immutable collections
✔ Understanding lists and arrays in Scala
✔ The list buffer and the array buffer

✔ Types of threads creation
✔ multi-tasking in threads
✔ Threads priority

✔ Introduction to Exceptions
✔ How to define Try / Catch / Finally blocks
✔ Throw Vs Throws

✔ Introduction to Spark
✔ The overview of Spark and how it is better than Hadoop
✔ Spark history server and Cloudera distribution
✔ Features of Spark
✔ Components of Spark

✔ Memory management
✔ Executor memory vs driver memory
✔ Working with Spark Shell
✔ The concept of resilient distributed datasets (RDD)
✔ The architecture of Spark
✔ Introduction to Spark Core
✔ Introduction to Spark SQL
✔ Introduction to Spark Streaming
✔ Modes of Apache spark deployment

✔ Spark RDDs
✔ Creating RDDs
✔ RDD partitioning
✔ Features of RDD
✔ Operations and transformations in RDDs
✔ Narrow Transformations (Map, Flat Map, Map Partition, Filter, Sample, Union)
✔ Wide Transformations (Intersection, Distinct, ReduceByKey, GroupByKey, Joins, Cartesian, Repartition, Coalesce, Subtract)

✔ Various operations of RDDs
✔ Distributed shared memory vs RDD
✔ Fine and coarse-grained update
✔ Spark Actions (Collect, Count, Take, First, Reduce, CountByValue, Max, Min, Sum, Top, Take Ordered, Take Sample, Foreach)

✔ Learning about Spark SQL
✔ The context of SQL in Spark for providing structured data processing
✔ Data Frames in Spark
✔ Creating Data Frames
✔ Purpose of Data Set
✔ Data Frame Vs Data Set
✔ JSON support in Spark SQL
✔ Working with XML data
✔ Parquet files
✔ Creating Hive context
✔ Writing a Data Frame to Hive
✔ Reading JDBC files
✔ Manual inferring of schema
✔ Working with CSV Files

✔ Comparing Spark applications with Spark Shell
✔ Creating a Spark application using Scala or Java (Word count program)
✔ Deploying a Spark application
✔ Scala built application
✔ Creation of the mutable list, set and set operations, lists, tuples, and concatenating lists
✔ The web user interface of a Spark application

✔ Introduction to live project
✔ code walkthrough
✔ Project explanation

✔ All the materials like PPTs and Complete reference books will share it over email.

✔ Sample resumes will share over email
✔ How to prepare spark resume and sample resume walkthrough