Description

Details and functionalhttps://www.youtube.com/embed/LeVUWyPGcmsity of the course, HDFS, PIG, HIVE and HBASE, are some of the main topics that the Hadoop course at Databyte covers. The institute focuses on teaching and training its students such that they become professionals that fill the growing requirements incorporates.

This is an instructor-led course with an average batch size of 10 students. In the 60 hours of classroom training, you will get both the theoretical and practical knowledge needed to build the necessary skills. The institute’s holistic approach is stemmed to meet the long-term needs of the student and hence they provide 100% job/placement assistance with an option of seeking a trial class before the enrolment.

What will I Learn?

  • Tools that are a part of the Hadoop Ecosystem like Pig, Hive, Sqoop, Flume, Oozie, and HBase
  • Complete knowledge of Big Data and Hadoop including HDFS (Hadoop Distributed File System), YARN (Yet Another Resource Negotiator) and MapReduce.

Specifications

  • Free Demo
  • 100% Placement Assistance
  • Missed Class Recovery
  • Certification by Institute
  • Instalment Facility
  • Interview Training

Virtual box/VM Ware 

  • Basics & Installations

 

Linux 

  • Basics

 

Hadoop

  • What is Hadoop?
  • Why Hadoop and flow of Hadoop
  • Scaling
  • Distributed Framework
  • Hadoop v/s RDBMS
  • A brief history of Hadoop

 

Hadoop installation in pseudo mode

  • Adding and removing nodes (without down time)
  • Decommissioning nodes
  • Block size
  • Hadoop Processes ( NN, SNN, JT, DN, TT)
  • Common errors when running Hadoop cluster, solutions

 

HDFS- Hadoop distributed File System 

  • HDFS Design and Architecture
  • HDFS Concepts
  • Interacting HDFS using the command line
  • Dataflow
  • Introduction about Blocks
  • Data Replication
  • Admin Commands
  • Hadoop archives

 

Hadoop Processes 

  • Name node and its functionality
  • Secondary name node and its functionality
  • Job tracker and its functionality
  • Task tracker and its functionality
  • Data node and its functionality
  • Resource manager and its functionality Hadoop
  • Node Manager and its functionality

 

Map Reduce 

  • Developing Map Reduce Application
  • Phases in Map-Reduce Framework
  • Map Reduce Input and Output Formats
  • Advanced Concepts
  • Combiner
  • HAR
  • Partitioner, sorting, shuffling
  • Different phases of MapReduce programs
  • Data localization
  • Different unstructured data processing examples
  • Image processing by using MapReduce

 

Joining datasets in MapReduce jobs 

  • Map-side join
  • Reduce-Side join

 

Hadoop Programming Languages 

PIG

  • Introduction (Basics)
  • Installation and Configuration
  • Different datatypes
  • Interacting HDFS using PIG
  • Map Reduce Programs through PIG 6. PIG Commands
  • Execution mechanisms (grunt, script…)
  • Loading, Filtering, Grouping, joins….
  • Sample programs in PIG with Real-time

 

Hive 

  • Basics (Introduction)
  • Installation and Configurations
  • Datatypes and operators
  • HQL Commands
  • Interacting HDFS using Hive
  • MapReduce programs through Hive
  • Joins, groups, filter……
  • Sample Programs in a hive with real-time
  • Join vs Map Join

 

Impala 

  • Basics
  • Commands

 

Sqoop 

  • Introduction to scoop
  • Installations & Configurations
  • Sqoop commands
  • Connect to a relational database using sqoop and downloading lakhs of records to Hadoop (in a single minute)

 

Flume 

  • Basics (Introduction)
  • Installation and Configurations

 

NoSQL Databases Concepts 

 

Hbase

  • Basics & Installations
  • commands
  • Interacting Hbase with HDF

 

MongoDB 

  • Basics & Installations I
  • All queries for processing data

 

Apache Spark 

  • Introduction
  • Installations and configurations
  • RDD, SC….
  • Scala Introduction
  • Interacting spark with HDFS
  • Programs in Spark through Scala

 

Specialities 

  • ETL tool (Data Warehousing BI Tools) 

 

PDI

  • Introduction
  • Creating RDBMS database
  • Establishing Connection between PDI to RDMS database
  • Creating data in Hadoop
  • Establishing Connection between PDI to Hadoop data
  • Moving data from Hadoop to RDBMS and vice versa
  • Summarization

Mr.Karthik

The trainer has 3 years of industry experience and more than 6 years of teaching experience and trained 200+ students. The trainer is an expert in Python programming. The trainer has in-depth knowledge in Python datatypes, Selenium web-Driver andHadoop Ecosystem. 

 

No reviews found

Batch Start Date End Date Timings Batch Type

Description

Details and functionalhttps://www.youtube.com/embed/LeVUWyPGcmsity of the course, HDFS, PIG, HIVE and HBASE, are some of the main topics that the Hadoop course at Databyte covers. The institute focuses on teaching and training its students such that they become professionals that fill the growing requirements incorporates.

This is an instructor-led course with an average batch size of 10 students. In the 60 hours of classroom training, you will get both the theoretical and practical knowledge needed to build the necessary skills. The institute’s holistic approach is stemmed to meet the long-term needs of the student and hence they provide 100% job/placement assistance with an option of seeking a trial class before the enrolment.

What will I Learn?

  • Tools that are a part of the Hadoop Ecosystem like Pig, Hive, Sqoop, Flume, Oozie, and HBase
  • Complete knowledge of Big Data and Hadoop including HDFS (Hadoop Distributed File System), YARN (Yet Another Resource Negotiator) and MapReduce.

Specifications

  • Free Demo
  • 100% Placement Assistance
  • Missed Class Recovery
  • Certification by Institute
  • Instalment Facility
  • Interview Training
₹15,000 ₹ 15,000

Hurry up!! Limited seats only

No Comments

Please login to leave a review

Related Classes

₹15,000 ₹15,000

Hurry up!! Limited seats only

Map location

Shares