Apache Spark With Examples for Big Data Analytics

Apache Spark With Examples for Big Data Analytics, available at $19.99, has an average rating of 3.5, with 42 lectures, based on 119 reviews, and has 2222 subscribers.

You will learn about Get clear understanding of the limitations of MapReduce and role of Spark in overcoming these limitations Understand fundamentals of Scala Programming Language and it’s features Expertise in using RDD for creating applications in Spark Mastering SQL queries using SparkSQL Gain thorough understanding of Spark Streaming features This course is ideal for individuals who are Professionals aspiring for a career in field of real time Big data analytics or Analytics professionals or Senior IT Professionals or Developers and Architects or Students who wish to gain a thorough understanding of Apache Spark or Freshers or Software Architects, Engineers and Developers It is particularly useful for Professionals aspiring for a career in field of real time Big data analytics or Analytics professionals or Senior IT Professionals or Developers and Architects or Students who wish to gain a thorough understanding of Apache Spark or Freshers or Software Architects, Engineers and Developers.

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Summary

Title: Apache Spark With Examples for Big Data Analytics

Price: $19.99

Average Rating: 3.5

Number of Lectures: 42

Number of Published Lectures: 42

Number of Curriculum Items: 42

Number of Published Curriculum Objects: 42

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Get clear understanding of the limitations of MapReduce and role of Spark in overcoming these limitations

Understand fundamentals of Scala Programming Language and it’s features

Expertise in using RDD for creating applications in Spark

Mastering SQL queries using SparkSQL

Gain thorough understanding of Spark Streaming features

Who Should Attend

Professionals aspiring for a career in field of real time Big data analytics

Analytics professionals

Senior IT Professionals

Developers and Architects

Students who wish to gain a thorough understanding of Apache Spark

Freshers

Software Architects, Engineers and Developers

Target Audiences

Professionals aspiring for a career in field of real time Big data analytics

Analytics professionals

Senior IT Professionals

Developers and Architects

Students who wish to gain a thorough understanding of Apache Spark

Freshers

Software Architects, Engineers and Developers

This course covers all the fundamentals you need to write complex Spark applications. By the end of this course you will get in-depth knowledge on Spark core,Spark SQL,Spark Streaming.

This course is divided into 9 modules

1. Dive Into Scala – Understand the basics of Scala that are required for programming Spark applications.Learn about the basic constructs of Scala such as variable types, control structures, collections,and more.
2. OOPS and Functional Programming in Scala – Learn about object oriented programming and functional programming techniques in Scala
3. Introduction to Apache Spark – Learn Spark Architecture,Spark Components and spark use-cases
4. Spark Basics – Learn how to configure/run spark in eclipse/intellij
5. Working with RDDs in Spark – Learn what is Resilient Distributed Dataset,Different types of actions and transformations which can be applied on RDDs
6. Aggregating Data with Pair RDDs – Learn how Pair RDD is different from RDD,Different types of actions and transformations which can be applied on Pair RDDs
7. Advanced Spark Concepts – Learn how Spark uses Broadcast variables and Accumulators to perform calculations,how persistence and partitioning helps to achieve performance
8. Spark SQL and Data Frames – Understand the difference between Dataframe and Dataset
9. Spark Streaming – Learn how to analyse massive amount of dataset on the fly

All the concepts are explained using hands-on examples.This course covers 10+ hands-on big data examples such as

Explore player data from 2014 world cup

Agregate data from ebay online auction data

Understand different data points from Adhaar data

Develop application to analyse funds received by Indian startup

Explore the price trend by looking at the real estate data in California

Help retailer to find out valid and invalid purchase transactions of chain of stores in Bangalore

Write Spark program find out count of stores in each US region from USA states & Store locations data

Develop Spark Streaming application to perform Twitter Sentiment Analysis

30-day Money-back Guarantee!?You will get 30-day money-back guarantee from Udemy for this course.?

If not satisfied simply ask for a refund within 30 days. You will get a full refund. No questions whatsoever asked.

Course Curriculum

Chapter 1: Dive Into Scala

Lecture 1: Introduction to scala

Lecture 2: Environment Setup

Lecture 3: Hello Scala

Lecture 4: Flow Controls

Lecture 5: Functions and operators

Lecture 6: OOPS concepts

Lecture 7: Traits

Lecture 8: Arrays

Lecture 9: Collections

Chapter 2: Introduction to Apache Spark

Lecture 1: BigData and Need for Apache Spark

Lecture 2: What is Spark,Spark Features and Spark Eco System

Lecture 3: Spark Architecture

Lecture 4: Spark Usecases

Chapter 3: Spark Configuration

Lecture 1: Setup Environment

Lecture 2: Word Count Program in Spark

Chapter 4: Working with RDDs in Spark

Lecture 1: What is RDD & How to Create

Lecture 2: Transformations – filter & map

Lecture 3: Solving Cars By Mileage problem using map and filter transformations

Lecture 4: Solving Cars In America problem using map and filter transformations

Lecture 5: Transformations – flatmap,union & intersection

Lecture 6: Analysis on 2014 football world cup player information

Lecture 7: RDD Actions

Lecture 8: Nasa Access Logs Analysis

Chapter 5: Aggregating Data with Pair RDDs

Lecture 1: Pair RDD – How to Create,reduceByKey

Lecture 2: groupByKey and reduceBykey vs groupByKey

Lecture 3: Transformations – mapvalues sortbykey countbykey

Lecture 4: Analysis on 2015 Indian Startup funding information

Lecture 5: Analysis on real estate data using pair rdd operations

Lecture 6: Join Operations

Chapter 6: Advanced Spark Concepts

Lecture 1: Broadcast Variables

Lecture 2: Accumulators

Lecture 3: Persistence and Caching

Lecture 4: Partitioning

Chapter 7: Spark SQL

Lecture 1: What is Spark SQL

Lecture 2: DataFrames

Lecture 3: DataSets

Lecture 4: Ebay Auction Data Analysis

Lecture 5: Adhaar Data Analysis

Chapter 8: Spark Streaming

Lecture 1: What is Spark Streaming?

Lecture 2: DStreams

Lecture 3: Spark Streaming Example

Lecture 4: Twitter Sentiment Analysis

Instructors

Code Peekers
Peek Into Success Through Code

Rating Distribution

1 stars: 10 votes

2 stars: 5 votes

3 stars: 15 votes

4 stars: 18 votes

5 stars: 71 votes

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