This course will prepare you to: Explain the architecture of the Spark And scala. Configure and use new functionalities in Spark And scala Concepts.

What is Scala Setup and configuration of Scala Develop and run basic Scala Programs Scala operations Functions and procedures in Scala Different Scala APIs for common operations Loops and collections Array, Map, Lists, Tuples Pattern matching for advanced operations Eclipse with Scala

Need for stream analytics Comparison with Storm and S4 Real-time data processing using Spark streaming Fault tolerance and check-pointing Stateful Stream Processing DStream and window operations Spark Stream execution flow Connection to various source systems Performance optimizations in Spark

What is Spark SQL Apache Spark SQL Features and Data flow Spark SQL architecture and components Hive and Spark SQL together Play with Data frames and Data states Data loading techniques in Spark Hive Queries through Spark Various Spark SQL DDL and DML operations Performance tuning in SparK

Spark And Scala Training |

Sapphire Global Spark And scala Training makes you an expert in using Spark And scala concepts. Enroll now for Spark And scala online training and get through the concepts of data, by utilizing the internal memory for storing a working set.

Overview

Training Options

INSTRUCTOR LEAD LIVE TRAINING
Rs. 35,000

Live Instructor Online training by Certified & industry expert Trainers
24/7 One Demand Dedicated Server for Hands on Practice.
Flexibility to attend the class at your convenient time.
Earn a Skill Certificate
Professional Resume Preparation end of the trading period.
Plus 45 Days of flexible access e-learning.

CORPORATE TRAINING

Customized Learning delivery model.
Our training practice are perfectly blended with options for effective live instructor lead hands on training.
Training need analysis.
Our Corporate training services are easy accessibility of LMS ( Learning Management System ) online or offline – anytime, anywhere, on any of your devices.
24/7 learner assistance and Support

Course Curriculum

Key features

This course will prepare you to:

Explain the architecture of the Spark And scala.
Configure and use new functionalities in Spark And scala Concepts.

Dive into Scala

What is Scala
Setup and configuration of Scala
Develop and run basic Scala Programs
Scala operations
Functions and procedures in Scala
Different Scala APIs for common operations
Loops and collections Array, Map, Lists, Tuples
Pattern matching for advanced operations
Eclipse with Scala

Object Oriented and Functional Programming

Introduction to object oriented programming
Different oops concepts
Constructor, getter, setter, singleton, overloading and overriding
Nested Classes, Visibility Rules
Functional Structures
Functional programming constructs
Call by Name, Call by Value

Big Data and need for Spark

Introduction to Big Data
Challenges with old Big Data solutions
Batch vs Real-time vs in-Memory processing
MapReduce and its limitations
Apache Storm and its limitations
Need for general purpose solution – Apache Spark

Deep Dive in Apache Spark

What is Apache Spark?
Internals of Spark architecture
Apache Spark design principles
Spark features and characteristics
Apache Spark Eco-system components and their insights

Deploy Spark in Local mode

Setup of Spark Environment
Install and configure prerequisites
Installation of Apache Spark in local mode
Work with Spark in local mode
Troubleshooting the encountered problems

Deploy Apache Spark in different modes

Installation of Spark in standalone mode
Installation of Spark in YARN mode
Installation & configuration of Spark on a real multi-node cluster
Play with Spark in cluster mode
Best practices for Spark deployment

Demystify Apache Spark

Play with Spark shell
Execute Scala and Java statements in shell
Understand Spark Context and driver
Read data from local filesystem
Integrate Spark with HDFS
Cache the data in memory for further use
Distributed persistence
Testing and troubleshooting

Basic Abstraction RDDs

What is RDD in Spark
How RDDs make Spark a feature rich framework
Transformations in Apache Spark RDDs
Spark RDDs action and persistence
Spark Lazy operations - Transformation as well as Caching
Fault tolerance in Spark
Load data and create RDD in Spark
Persist RDD in memory or disk
Pair operations and key-value in Spark
Spark Integration with Hadoop
Apache Spark practicals and workshops

Spark streaming

Need for stream analytics
Comparison with Storm and S4
Real-time data processing using Spark streaming
Fault tolerance and check-pointing
Stateful Stream Processing
DStream and window operations
Spark Stream execution flow
Connection to various source systems
Performance optimizations in Spark

Spark-SQL

What is Spark SQL
Apache Spark SQL Features and Data flow
Spark SQL architecture and components
Hive and Spark SQL together
Play with Data frames and Data states
Data loading techniques in Spark
Hive Queries through Spark
Various Spark SQL DDL and DML operations
Performance tuning in SparK

Spark MLlib and Spark GraphX

Need for Machine Learning
Introduction to Spark machine learning
Various Spark ML libraries
Algorithms for clustering, statistical analytics, classification etc.
Introduction to GraphX
Need for different graph processing engine
Graph handling using Apache Spark

Real Life Spark Project

Live Apache Spark project based on real industry scenarios. Work on real life use-case and handle the real-world problem with live datasets.

Practice Test and Interview Questions

Course Advisor

Course Advisor

R. Sreenatha Reddy

SAP FICO / FSCM / TRM / FM / S4HANA Functional Consultant

Professional Experience:

15+ years of Industry experience as Accountant, Consultant, Module Lead, worked on various IT Organizations like IBM/TCS/ITC infotech/SAP Labs across the globe.

Specialized in SAP