Spark Online Training| Apache Spark Course online in USA & India

Apache Spark developer training


We are planning to start online spark training in Bangalore. If you are interested please fill the form.

Spark training weekend batch
Fee: 20,000/- with 5000 money back (if u practice well & if you get cloudera/databricks/hortnworks certificate)
Mode: online
Call: 9247159150 (please WhatsApp me)
Daily Training:  Dec 1 – Jan 10
Time 6.30 AM to 8.30 AM IST (daily batch)
Time: 6PM-10:30 pm IST (Weekend)
Trainer: Venu

To attend this training, just click on this gotomeeting link (enter ur name & email)


If you are looking for spark training, please fill this form:


Spark Training for Non-Hadoop background Students.

Note: In my training, every session recorded. Ill share that video after training for revision purpose.

Please find reviews here

Each and every Spark training session recorded,
Give daily tasks with real-time scenarios

Recorded Spark Demo

Within this time, if you want to learn, just contact me ill send some materials, just learn those.

Course content:

Hadoop Overview

  • Lecture
    • How HDFS read/write the data
    • YARN internal architecture
    • HDFS Internal Architecture.
  • Hands-On
    • HDFS Shell Commands
    • Install Hadoop & Spark in Ubuntu
    • Configure Hadoop/spark environment in Eclipse

Hive Overview

  • Lecture
    • How Hive functioning properly
    • Optimize Hive queries
    • Using Sqoop
  • Hands-On
    • Process csv, JSON data
    • Bucketing, Partitioning tables.
    • Import MySQL/Oracle data using Sqoop

Scala Basics

  • Lecture
    • Functional language
    • Scala Vs Java
  • Hands-On
    • Strings, Numbers
    • List, Array, Map, Set
    • Control Statements, collections
    • Functions, methods
    • Pattern matching

Spark Overview

  • Lecture
    • The power of Spark?
    • Spark Ecosystem
    • Spark Components vs Hadoop
  • Hands-On
    • Installation & Eclipse configuration
    • Programs in Command line Interface & Eclipse
    • Process Local, HDFS files

RDD Fundamentals

  • Lecture
    • Purpose and Structure of RDDs
    • Transformations, Actions, and DAG
    • Key-Value Pair RDDs
  • Hands-On
    • Creating RDDs from Data Files
    • Reshaping Data to Add Structure
    • Interactive Queries Using RDDs

SparkSQL and DataFrames

  • Lecture
    • Spark SQL and DataFrame Uses
    • DataFrame / SQL APIs
    • Catalyst Query Optimization
  • Hands-on
    • Creating (CSV, JSON) DataFrames
    • Querying with DataFrame API and SQL
    • Caching and Re-using DataFrames
    • Process Hive data in Spark

Spark DataSet API

  • Lecture
    • Power of Dataset API in Spark 2.0
    • Serialization concept in DataSet
  • Hands-on
    • Creating DataSet API
    • Process CSV, JSON, XML, Text data
    • DataSet Operation

Spark Job Execution

  • Lecture
    • Jobs, Stages, and Tasks
    • Partitions and Shuffles
    • Broadcast Variables and accumulators
    • Job Performance
  • Hands-On
    • Visualizing DAG Execution
    • Observing Task Scheduling
    • Understanding Performance
    • Measuring Memory Usage
    • shared variables usage

Clustering Architecture

  • Lecture
    • Cluster Managers for Spark: Spark Standalone, YARN, and Mesos
    • Understanding Spark on YARN
    • What happened in a cluster when you submit a job
  • Hands-On
    • Tracking Jobs through the Cluster UI
    • Understanding Deploy Modes
    • Submit a sample job and monitor job

Spark Streaming

  • Lecture
    • Streaming Sources and Tasks
    • DStream APIs and Stateful Streams
    • Flink Introduction
    • Kafka architecture
  • Hands-On
    • Creating DStreams from Sources
    • Operating on DStream Data
    • Viewing Streaming Jobs in the Web UI
    • Sample Flink Streaming program.
    • Kafka sample program

AWS with Spark

  • Lecture
    • AWS architecture
    • Redshift, EMR, and EC2 functionalities
    • How to minimize AWS cost
  • Hands-On
    • Submit a sample jar in AWS Cluster
    • Create a cluster using EMR
    • Read/Write data from Redshift

Advanced concepts in Spark

  • Lecture
    • Memory management in Spark
    • How to optimize Spark Applications
    • Spark how to integrate with other Applications
  • Hands-On
    • Spark with Cassandra Integration
    • Alluxio/Tachyon hands-on experience
    • Apache Kudu with spark

Sample Spark Project

  • Lecture
    • End to end a project overview
    • Complicated problems in a project
    • Common steps in any project
  • Hands-On
    • Implement Spark SQL Mini project
    • Kafka, Cassandra, Spark Streaming project
    • Pull Twitter data and analyze the data
    • Oozie scheduling & shell script

Important notes:

  • Daily after training assign a task
  • Who completed all these tasks they will get 5000/- money back.
  • After training provides a solution to that problem.
  • Minimum 3 months online support & Job Assistance
  • Training in Spark 2.3.1 and spark 1.6.3 in Scala language
  • Excellent Materials all major spark and Scala books
  • Guide to get Cloudera/MapR/Databricks spark certification

Recommendations: To learn Apache Spark, no need to learn Hadoop, but If you have Hadoop knowledge, it’s a huge plus to implement production level project.
To learn Spark Minimum core java (to learn Scala) and SQL queries knowledge mandatory.
This training intentionally is done for non Hadoop background students.

If you interested to take Online Spark training, just fill the form we will send scale materials to familiarize scala & spark.



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