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Spark Training

Tekslate’s Apache Spark training is designed to help you develop your skills and expertise in working with Big Data Hadoop System. It will enable you to gain in-depth knowledge on Apache Spark, and Scala programming language including Spark Streaming, Spark RDD, Spark SQL, GraphX programming, Spark Shell Scripting, etc., through obtaining hands-on experience by working on real-time projects under the guidance of certified trainer during training.

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30 Hrs Instructor Led Training
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20 Hrs Project & Exercises
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Curriculum

A complete index of
job-ready skills curated
to meet the industrial need.
Explore.

Introduction to Big Data Hadoop and Apache Spark Topics:

  • What is Big Data?

  • Big Data Customer Scenarios

  • Limitations and Solutions of Existing Data Analytics Architecture with Uber Use Case

  • How Hadoop Solves the Big Data Problem?

  • What is Hadoop?

  • Hadoop’s Key Characteristics

  • Hadoop Ecosystem and HDFS

  • Hadoop Core Components

  • Rack Awareness and Block Replication

  • YARN and its Advantage

  • Hadoop Cluster and its Architecture

  • Hadoop: Different Cluster Modes

  • Big Data Analytics with Batch & Real-time Processing

  • Why Apache Spark is needed?

  • What is Apache Spark?

  • How Apache Spark differs from other frameworks?

  • What is Scala?

  • Why Scala for Apache Spark?

  • Scala in other Frameworks

  • Introduction to Scala REPL

  • Basic Scala Operations

  • Variable Types in Scala

  • Control Structures in Scala

  • For each loop, Functions and Procedures

  • Collections in Scala- Array

  • ArrayBuffer, Map, Tuples, Lists, and more

  • Apache Spark at Yahoo!

  • Functional Programming

  • Higher Order Functions

  • Anonymous Functions

  • Class in Scala

  • Getters and Setters

  • Custom Getters and Setters

  • Properties with only Getters

  • Auxiliary Constructor and Primary Constructor

  • Singletons

  • Extending a Class

  • Overriding Methods

  • Traits as Interfaces and Layered Traits

  • Apache Spark’s Place in the Hadoop Ecosystem

  • Apache Spark Components & its Architecture

  • Apache Spark Deployment Modes

  • Introduction to Apache Spark Shell

  • Writing your first Apache Spark Job Using SBT

  • Submitting Apache Spark Job

  • Apache Spark Web UI

  • Data Ingestion using Sqoop

  • Challenges in Existing Computing Methods

  • Probable Solution & How RDD Solves the Problem

  • What is RDD, Its Operations, Transformations & Actions

  • Data Loading and Saving Through RDDs

  • Key-Value Pair RDDs

  • Other Pair RDDs, Two Pair RDDs

  • RDD Lineage

  • RDD Persistence

  • WordCount Program Using RDD Concepts

  • RDD Partitioning & How It Helps Achieve Parallelization

  • Passing Functions to Apache Spark

  • Need for Apache Spark SQL

  • What is Apache Spark SQL?

  • Apache Spark SQL Architecture

  • SQL Context in Apache Spark SQL

  • User Defined Functions

  • Data Frames & Datasets

  • Interoperating with RDDs

  • JSON and Parquet File Formats

  • Loading Data through Different Sources

  • Apache Spark – Hive Integration

  • Why Machine Learning?

  • What is Machine Learning?

  • Where Machine Learning is Used?

  • Face Detection: USE CASE

  • Different Types of Machine Learning Techniques

  • Introduction to MLlib

  • Features of MLlib and MLlib Tools

  • Various ML algorithms supported by MLlib

  • Supervised Learning - Linear Regression, Logistic Regression, Decision Tree, Random Forest

  • Unsupervised Learning - K-Means Clustering & How It Works with MLlib

  • Analysis of US Election Data using MLlib (K-Means)

  • Need for Kafka

  • What is Kafka?

  • Core Concepts of Kafka

  • Kafka Architecture

  • Where is Kafka Used?

  • Understanding the Components of Kafka Cluster

  • Configuring Kafka Cluster

  • Kafka Producer and Consumer Java API

  • The need of Apache Flume

  • What is Apache Flume?

  • Basic Flume Architecture

  • Flume Sources

  • Flume Sinks

  • Flume Channels

  • Flume Configuration

  • Integrating Apache Flume and Apache Kafka

  • Drawbacks in Existing Computing Methods

  • Why Streaming is Necessary?

  • What is Apache Spark Streaming?

  • Apache Spark Streaming Features

  • Apache Spark Streaming Workflow

  • How Uber Uses Streaming Data

  • Streaming Context & DStreams

  • Transformations on DStreams

  • Describe Windowed Operators and Why it is Useful

  • Important Windowed Operators

  • Slice, Window and ReduceByWindow Operators

  • Stateful Operators

  • Apache Spark Streaming: Data Sources

  • Streaming Data Source Overview

  • Apache Flume and Apache Kafka Data Sources

  • Example: Using a Kafka Direct Data Source

  • Perform Twitter Sentimental Analysis Using Apache Spark Streaming

We have made a tailored curriculum covering the latest industry-ready concepts to serve every individual’s learning desires.

Spark Training  Objectives

After the successful completion of Apache Spark training at Tekslate, the participant will be able to

  • Get an overview of Big Data & Hadoop including HDFS (Hadoop Distributed File System), YARN (Yet Another Resource Negotiator).
  • Gain knowledge of Apache Spark and Scala Programming implementation.

  • Gain comprehensive knowledge of various tools that fall in Spark Ecosystem like Spark SQL, Spark MlLib, Sqoop, Kafka, Flume and Spark Streaming.

  • Write Spark applications using Scala.

  • Understand RDD, its Operations, Transformations & Actions along with the implementation of Spark algorithms.

  • Gain knowledge on Scala classes concept and execution patterns.

  • Understand data ingestion using Sqoop.

  • Perform SQL queries using Spark SQL.

  • Use Kafka to produce and consume messages.

  • Top companies like Microsoft, Amazon, IBM, etc., are incorporating Apache Spark in their deployments.

  • There is a high market demand for certified Apache Spark developers and high salary packages are being offered to them.

  • The average pay of a Certified Apache Spark developer stands at 105,700 USD per annum.

The following job roles will get benefited from learning this course:

  • Aspirants looking for a career in this field.
  • Analytics professionals

  • Research professionals

  • IT developers and testers

  • Data scientists

  • BI and reporting professionals

  • Professionals who want to enhance their skills in Big Data analytics.

As such, there are no prerequisites for learning Apache Spark course. Anyone who is interested in learning this course can join this training.

  • Having basic knowledge of databases, SQL and query language will be beneficial, but not mandatory.

We will provide two real-time projects under the guidance of a professional trainer, who will explain you on how to acquire in-depth knowledge on all the concepts involved in these projects.

contact us
+1 930 200 4823

Training  Options

Different individuals. Different upgrade goals. Different modes of learning.

We got solutions for everyone looking for an AWS Architect course. Opt in for your convenient upgrade option, and we will guide you through.

Duration
One-on-one Session
Support
Resources
Time
Fee

Live Online.

30 Hours
Yes
24x7
Additional tips from the trainer

24 Jan 2022, 07:00 AM IST

31 Jan 2022, 07:00 AM IST

 

Self-Paced

30 Hours
No
Weekdays & Working Hours
Accessible through LMS
At your convenience
 

Spark Training Upcoming Batches

Weekday
24 Jan, 2022 - 24 Feb, 2022
01:30 AM IST
Weekday
31 Jan, 2022 - 03 Mar, 2022
01:30 AM IST
Weekend
29 Jan, 2022 - 01 Mar, 2022
02:30 AM IST
Weekend
22 Jan, 2022 - 22 Feb, 2022
02:30 AM IST
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Schedules Doesn't Suit You ?

Our Team can set up a batch at your convinient time.

Corporates  Training

Experience and witness the express transformation of your workforce from the world-class tech upgrade platform.

Customized training options

Tailored curriculum to fit your project needs.

Practical exposure is assured.

We have got everything covered for any IT upgrade for your organization. We are one click away.

Success Stories from Future Digital Leaders

tekslate-reviews
Its a great learning experience at Tekslate, it provides flexible course timings any time anywhere as per user convenience. I attended Apache Spark training last month. The course content they deliver is very informative and according to latest developments required for the certification exam.

Madhu Sudan

tekslate-reviews
Hi, I’m Arjun attended Apache Spark training with my colleagues. The trainer is highly experienced and talented in implementing projects with an in-detail explanation which helped me to clear Spark developer certification in first submit itself.

Arjun

tekslate-reviews
Tekslate provides the best Apache Spark training at an affordable price. The trainer is highly skilled in explaining projects with real-time examples which helped me to understand even better. Thank you Tekslate. I highly recommend Tekslate for the people who want to gain knowledge of Spark and Scala concepts.

Niharika

Spark Training  FAQ'S

Have questions? We’ve got the answers. Get the details on how you can grow in this course.

Our trainers are well experienced professionals and certified in working with front-end development technologies.

We will record all the Live sessions you go through, and we will send the recording of the class you missed.

For practical execution, our trainer will provide server access to the student. 

Join a Free Spark Training  Demo Session

See if this course is a fit for you by joining us for an online info session. You’ll meet our team, get an overview of the curriculum and course objectives, and learn about the benefits of being a student at Tekslate

By providing us with your details, We wont spam your inbox.

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