Apache Spark and Scala Training

Live Online & Classroom Enterprise Training

Master Apache Spark, a fast, in-memory distributed collections framework written in the programming language Scala. This Spark & Scala course will enable candidates to gain an in depth knowledge of Scala's programming model. It also gives them exposure to near-to-real-time data analytics through hands-on examples in Spark and Scala.

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What is Apache Spark Scala Training about?

This course introduces learners to Apache Spark, one of the most powerful open-source big data processing frameworks, using Scala, its native programming language. Participants will gain hands on experience in Spark’s core concepts, including RDDs, DataFrames, SQL, streaming, and machine learning pipelines. The course emphasizes writing efficient big data applications with Scala, integrating Spark with Hadoop, Kafka, and cloud platforms. By the end of the course, learners will be able to design and implement high-performance data processing pipelines for real-world use cases.

What are the objectives of Apache Spark Scala Training ?

Understand Spark architecture and execution model.
Write Spark applications using Scala for batch and streaming data.
Use RDDs, DataFrames, and Spark SQL for data processing.
Apply Spark MLlib for machine learning and predictive analytics.
Integrate Spark with big data ecosystems and cloud environments.

Who is Apache Spark Scala Training for?

Data engineers working on large-scale data pipelines.
Big data developers and architects.
Data scientists implementing distributed ML algorithms.
Software engineers exploring Spark for real-time applications.
Students and professionals pursuing careers in big data.

What are the prerequisites for Apache Spark Scala Training?

Prerequisites:

Basic knowledge of programming (preferably Java/Scala/Python).
Understanding of databases and data structures.
Familiarity with Hadoop or distributed computing concepts.
Knowledge of Linux command line and scripting.
Optional: Exposure to machine learning concepts.

Learning Path:

Introduction to Apache Spark and the big data ecosystem.
Scala fundamentals for Spark programming.
Spark Core: RDDs, DataFrames, and transformations.
Spark SQL, Streaming, and MLlib basics.
Integrating Spark with Hadoop, Kafka, and cloud platforms.

Related Courses:

Big Data Analytics with Hadoop
Data Engineering with PySpark
Machine Learning with Spark MLlib
Scala Programming Fundamentals

Available Training Modes

Live Online Training

5 Days

Course Outline Expand All

Expand All

Module 1- Introduction to Spark

Spark Overview

MapReduce vs. Spark

Spark Components and Full-Stack

Working with Spark

Install Apache Spark

Module 2- Introduction to Programming in Scala

Introduction to Scala

Scala Programming Constructs

Basic Operations in Scala

Scala Type Interface

Scala Object-oriented Aspects

Scala Functional Programming Aspects

Basic Scala Programming Skills

Module 3- Creating Applications in Spark using RDD

Introduction to RDDs

Working on Spark Project

Working with RDDs

Demo: How to create RDD

Module 4- Running SQL Queries using Spark SQL

Spark SQL Overview

Working with SparkSession

Working with Dataframes

DataFrames

Interoperability using different Approaches

Working with Datasets

Operating on various Data Sources

Catalog API

Module 5- Spark Streaming

Introduction to Spark Streaming

Introduction to DStreams

Spark Streaming Sources

Transformation and Operations on DStreams

Performance Tuning

Module 6- Spark Structured Streaming

Introduction to Spark Structured Streaming

Structured Streaming Architecture, model and its Components

Structured Streaming APIs

Spark job to count the number of words

Module 7- Spark ML Programming

Machine Learning Applications and its Types

Machine Learning using Spark Mllib & Spark ML

Demo - Spark ML

ML Pipeline

Spark Mllib Supported Types and Algorithms

Module 8- Spark GraphX and GraphFrames

Graph and Graph Parallel System

GraphX and Property Graph

Graph Operator

Graph Analytics

Introduction to GraphFrames

Working with GraphFrames

GraphFrame Algorithms

Who is the instructor for this training?

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