Big Data & Hadoop Training Institute :



Big Data & Hadoop Training Institute :

Overview of Big Data & Hadoop

1.What is Big Data & Hadoop

2.Sources of Big Data

3.Challenges with Big Data

4.Problems with traditional RDBMS

5.What is Hadoop

6.History of Hadoop

7.Benefits of Hadoop

8.How Hadoop solves problems with RDBMS?

9.Why Hadoop?


Software Installation

1.Pre requisites

2.Understanding decencies software and installing

3.Understanding hadoop configuration files

4.Setup single node hadoop cluster

5.Configuring Hadoop

6.The Command-Line Interface

7.Understanding hadoop Shell and shell commands

8.Hands on hadoop shell commands



HDFS (Hadoop Distributed File System)

1.Architecture of HDFS

2.HDFS Features

3.Name Node & Data Node

4.Secondary Name Node

5.Data Loading into HDFS

6.Anatomy of File Read & Write

7.Rack Awareness

8.Check Pointing

9.HDFS Integrity

10.Safe Mode

Federation & High Availability

Map Reduce-1(Classic)

1.Map Reduce Architecture

2.JobTraker & TaskTracer

3.Job Execution Flow

4.Monitoring Progress

5.Debugging MapReduce Jobs

6.Input Splits , Shuffling & Sorting

7.Practitioner & Record Readers


9.Distributed cache

10.Using Joins in MapReduce

11.Input & Output Formats

12.Data Compression Techniques

13.Job Schedulers

14.Failovers in Map Reduce

15.Hadoop Pipes and Hadoop Streaming

16.Hands on Examples: Writing a MapReduce Program and Running a MapReduce Job

Map Reduce-2(YARN)

1.Limitations of Mardeuce-1

2.YARN Architecture

3.Resource Manager

4.Node Manager

5.Application Master

6.Task Manager

7.Job Flow

8.Handing Failovers


1.Introduction to Spark

2.Spark RDD’s

3.Architecture of Spark

4.Spark execution engine

5.MapReduce v/s Spark

6.Spark Transformers

7.Spark Actions

8.Introduction to Flume,Kafka,Scala


1.Introduction to Impala

2.Impala v/s Hive,Pig,RDBMS

3.Features & benefits of Impala

4.Analyzing data with Impala


1.Introductions to Pig

2.Architecture of Pig

3.Pig Latin

4.Pig Data Types, Commands & Operators

5.Data Loading

6.Data processing

7.Pig Builtin Functions & UDFs

8.Pig Workflows

9.Hands on Exercises &Real Time Examples


1.Introduction & Architecture

2.Hive Configuration and Settings

3.Hive Query Language

4.Hive Data Types, DDL & DML

5.Loading Data into hive tables

6.Partitions & Bucketing

7.SERDEs in hive

8.Hive Built-in Functions& User Defined Functions(UDFs)

9.Writing & Executing Hive scripts

10.Hands on Examples& Real time Examples


1.Installing & Configuring Sqoop

2.Sqoop Tools

3.Import RDBMS data to Hive using Sqoop

4.Export from to Hive to RDBMS using Sqoop

5.Hands-On Exercise: Import data from RDBMS to HDFS and Hive

6.Hands-On Exercise: Export data from HDFS/Hive to RDBMS


1.Introduction to HCatalog

2.Advantages and Uses of HCatalog

3.HCatalog Load and Store Interfaces

4.Using HCatalog in PIG


1.Introduction to Beeline

2.Advantages of Beeline

3.Beeline v/s Hive


1.Introduction to NoSQL Databases

2.HBase Architecture

3.Internals of HBase

4.Hbase-Hive Integration

5.Real time use case of HBase

2.YARN Architecture

3.Resource Manager

4.Node Manager

5.Application Master

6.Task Manager

7.Job Flow

8.Handing Failovers


About Ascent Big Data & Hadoop Training Institute In Bangalore

Ascent Big Data & Hadoop Training Institute Providing high quality training at affordable fees is our core value. We offers classroom on niche technologies which are in high demand. All our trainers are IT professionals with rich experience. We work with our students in developing the right skills they need to build their career in present competitive environment. We have flexible batch times to suit the timings of graduating students and working professionals.

Ascent Software Training Institute In Bangalore Excellent Trainers and Fabulous Lab this is what you can expect from us.Free training materials, Free Career consulting, Career guidance by experienced IT professionals, Pleasant and modern training rooms

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