[email protected] +91 9541 551 557 +91 9035 406 484
Synergific Store LMS Login Training Calendar

Big Data Hadoop Spark Developer (BDHS)

Live Online (VILT) & Classroom Corporate Training Course

The Big Data Hadoop training course will teach you the concepts of the Hadoop framework, its formation in a cluster environment, and prepares you for Cloudera's Big Data certification.

Expert-Led VILT & Classroom Hands-On CloudLabs Certification Voucher Available
CloudLabs
Projects
Assessments
24/7 Support
Lifetime Access

Overview

With this Big Data Hadoop course, you will learn the big data framework using Hadoop and Spark, including HDFS, YARN, and MapReduce. The course will also cover Pig, Hive, and Impala to process and analyse large datasets stored in the HDFS and use Sqoop and Flume for data ingestion.

Objectives

At the end of BDHS training, participants will be able to understand:

  • The different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
  • Hadoop Distributed File System (HDFS) and YARN architecture
  • MapReduce and its characteristics and assimilate advanced MapReduce concepts
  • Different types of file formats, Avro schema, using Avro with Hive, and Sqoop and Schema evolution
  • Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
  • HBase, its architecture and data storage, and learn the difference between HBase and RDBMS
  • The common use cases of Spark and various interactive algorithms

Prerequisites

There are no prerequisites for this course. However, it’s beneficial to have some knowledge of Core Java and SQL.

Course Outline

  • Apache Hadoop Overview
  • Data Processing
  • Introduction to the Hands-On Exercises

  • Apache Hadoop Cluster Components
  • HDFS Architecture
  • Using HDFS

  • YARN Architecture
  • Working With YARN

  • What is Apache Spark?
  • Starting the Spark Shell
  • Using the Spark Shell
  • Getting Started with Datasets and DataFrames
  • DataFrame Operations

  • Creating DataFrames from Data Sources
  • Saving DataFrames to Data Sources
  • DataFrame Schemas
  • Eager and Lazy Execution

  • Querying DataFrames Using Column Expressions
  • Grouping and Aggregation Queries
  • Joining DataFrames

  • RDD Overview
  • RDD Data Sources
  • Creating and Saving RDDs
  • RDD Operations

  • Writing and Passing Transformation Functions
  • Transformation Execution
  • Converting Between RDDs and DataFrames
  • Key-Value Pair RDDs
  • Map-Reduce
  • Other Pair RDD Operations

  • Datasets and DataFrames
  • Creating Datasets
  • Loading and Saving Datasets
  • Dataset Operations

  • Writing a Spark Application
  • Building and Running an Application
  • Application Deployment Mode
  • The Spark Application Web UI
  • Configuring Application Properties

  • Review: Apache Spark on a Cluster
  • RDD Partitions
  • Example: Partitioning in Queries
  • Stages and Tasks
  • Job Execution Planning
  • Example: Catalyst Execution Plan
  • Example: RDD Execution Plan

  • Apache Spark Streaming Overview
  • Creating Streaming DataFrames
  • Transforming DataFrames
  • Executing Streaming Queries
  • Receiving Kafka Messages
  • Sending Kafka Messages

Available Training Modes

Pick the format that fits your team.

Same authorised curriculum, same trainers, same hands-on cloud labs — delivered the way that works for you.

Live Online (VILT)

Real-time instructor-led sessions over Zoom or Teams. Same classroom, different time zones.

Most popular

Classroom

Face-to-face training delivered at your office, our Bengaluru centre, or any partner venue worldwide.

Onsite

Self-Paced

Recorded sessions plus 24/7 access to cloud labs and assessments. Learn at the pace that works for each engineer.

On-demand

Blended

Live workshops with self-paced reinforcement and project-based labs. Best for hybrid teams across regions.

Hybrid teams
All modes include: hands-on cloud labs, recordings, assessments, certificate of completion. Talk to a solutions advisor →

Our Training Process

How a course becomes measurable skill.

One contract, five steps, zero handoffs. From discovery to deployment, the same Synergific team owns the outcome — not a chain of vendors.

5 Steps from your scoping call to certified, productive engineers.
01

Discover & set goals

We start with a scoping call to understand your team's current skill level, target outcomes, deadlines, and certification needs — then translate that into a measurable success plan with named owners on both sides.

02

Curate the right path

We map the optimal learning path — instructor-led, self-paced, or blended — with hands-on cloud labs, prerequisite refreshers, and certification vouchers built in. No filler modules, no padded curriculum.

03

Deliver hands-on training

Authorised trainers run live sessions backed by 24/7 cloud labs and real-world projects. Theory and practice on the same day — learners stop forgetting concepts before they get to apply them.

04

Assess & mentor

Continuous skill checks, mock exams, and 1:1 mentoring keep the program honest. If anyone falls behind, we course-correct in-flight — you'll never find out at the end that two engineers couldn't keep up.

05

Certify & apply on the job

Voucher-backed certification, post-training office hours, and 30-day reinforcement so skills land on real work — not just on the exam scorecard. Success measured after the course ends, not before.

Client Stories

What our clients say

Voices from L&D leaders, architects, and program managers who’ve trusted us with their upskilling.