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10% OFF - Best hadoop Training Institute in Noida Sector 15, 16, 18 | 10% OFF - Best hadoop Training Institute in Noida Sector 15, 16, 18

Course: (hadoop) Duration: 2 TO 3 MON Weekdays: Mon-Fri(1hr/D)
Weekends: Sat-Sun(2.5hrs/D) 100% job: Assistance Guaranteed 7.4LPA: Highest Package

Webtrackker Training and Placement

These days there are so many training institutes who claims to offer training and placement. They might be authentic and keep up to their promises, but how would a candidate trust an institute among so many or make the right choice? Here webtrackker Training Institute stands out with it’s unique 100% job Assistance with sufficient no of interview guarantee. Employability is not merely a part of the training goals but the ultimate objective of our Customized Profiles Based courses.

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Apache Hadoop Development training course lets you master the concepts of the Hadoop framework and prepares you for Cloudera’s CCA175 Big data certification. With our online Hadoop training, you’ll learn how the components of the Hadoop ecosystem, such as Hadoop 2.7, Yarn, MapReduce, HDFS, Pig, Impala, HBase, Flume, Apache Spark, etc. fit in with the Big Data processing lifecycle. Implement real life projects in banking, telecommunication, social media, insurance, and e-commerce on CloudLab. Best hadoop Training in Noida Sector 15, 16, 18

Best hadoop Training Center in Noida Sector 15, 16, 18- Apache Hadoop Development training by Webtrackker will master you in HDFS, MapReduce, Yarn, Hive, PIG, Oozie, Flume, etc. In this Apache Hadoop Development online course you will work on 4 real life projects and prepare yourself for Cloudera Spark and Hadoop Developer Certification (CCA175) Exam. You will get 6 months of Webtrackker Hadoop cloudlab access with this course.

Best hadoop Training Institute in Noida Sector 15, 16, 18- This Apache Hadoop Developer Certification Training will help you get a detailed idea about Big Data and Hadoop. Some of the topics included are introduction to the Hadoop ecosystem, understanding of HDFS and MapReduce including MapReduce abstraction. Learn to install, implement various components of Hadoop like Pig, Hive, Flume, Sqoop and YARN.

Hadoop is a distributed computing system that works on commodity hardware on a scale and speed that is just not possible for other database processing systems to match. Due to this there is a huge demand for Hadoop Developers who can deploy Hadoop on a massive scale. This Hadoop Developer online training equips you with the right skill sets needed to take the Professional Hadoop Developer Cloudera Certification. This Hadoop Certification training is your passport to the most sought-after jobs in the Big Data world. Best hadoop Training Center in Noida Sector 15, 16, 18

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hadoop Training training Class in Noida - The trainer explained all the course modules in a simple and precise way which really helped me master the technology in a very short period of time. Thank you webtrackker for the amazing Training

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Course Description & Detail

Hadoop Course Content:

Hadoop Overview, Architecture Considerations, Infrastructure, Platforms and Automation

Use case walk through

ETL, Log Analytics, Real Time Analytics

NoSQL Introduction

Traditional RDBMS approach, NoSQL introduction, Hadoop & Hbase positioning

Hbase Introduction

What it is, what it is not, its history and common use-cases, Hbase Client – Shell, exercise

Hbase Architecture

Building Components, Storage, B+ tree, Log Structured Merge Trees, Region Lifecycle, Read/Write Path

Hbase Schema Design

Introduction to hbase schema, Column Family, Rows, Cells, Cell timestamp, Deletes, Exercise - build a schema, load data, query data

Hbase Java API – Exercises

Connection, CRUD API, Scan API, Filters, Counters, Hbase MapReduce, Hbase Bulk load

Hbase Operations, cluster management

Performance Tuning, Advanced Features, Exercise, Recap and Q&A

MapReduce for Developers

Introduction

Traditional Systems / Why Big Data / Why Hadoop, Hadoop Basic Concepts/Fundamentals

Hadoop in the Enterprise

Where Hadoop Fits in the Enterprise, Review Use Cases

Architecture

Hadoop Architecture & Building Blocks, HDFS and MapReduce

Hadoop CLI

Walkthrough, Exercise

MapReduce Programming

Fundamentals, Anatomy of MapReduce Job Run, Job Monitoring, Scheduling, Sample Code Walk Through, Hadoop API Walk Through, Exercise

MapReduce Formats

  • Input Formats, Exercise, Output Formats, Exercise
  • Hadoop File Formats
  • MapReduce Design Considerations
  • Hadoop File Formats
  • MapReduce Algorithms

Walkthrough of 2-3 Algorithms

MapReduce Features

Counters, Exercise, Map Side Join, Exercise, Reduce Side Join, Exercise, Sorting, Exercise

Use Case A (Long Exercise)

Input Formats, Exercise, Output Formats, Exercise

MapReduce Testing

Hadoop Ecosystem

Oozie, Flume, Sqoop, Exercise 1 (Sqoop), Streaming API, Exercise 2 (Streaming API), Hcatalog, Zookeeper

HBase Introduction

Introduction, HBase Architecture

VIEW Types

Default Views, Overriden Views, Normal Views

MapReduce Performance Tuning

Development Best Practice and Debugging

Apache Hadoop for Administrators

Hadoop Fundamentals and Architecture

Why Hadoop, Hadoop Basics and Hadoop Architecture, HDFS and Map Reduce

Hadoop Ecosystems Overview

Hive, Hbase, ZooKeeper, Pig, Mahout, Flume, Sqoop, Oozie

Hardware and Software requirements

Hardware, Operating System and Other Software, Management Console

Deploy Hadoop ecosystem services

Hive, ZooKeeper, HBase, Administration, Pig, Mahout, Mysql, Setup Security

Enable Security – Configure Users, Groups, Secure HDFS, MapReduce, HBase and Hive

Configuring User and Groups, Configuring Secure HDFS, Configuring Secure MapReduce, Configuring Secure HBase and Hive

Manage and Monitor your cluster

Command Line Interface

Troubleshooting your cluster

Introduction to Big Data and Hadoop

Hadoop Overview

Why Hadoop, Hadoop Basic Concepts, Hadoop Ecosystem – MapReduce, Hadoop Streaming, Hive, Pig, Flume, Sqoop, Hbase, Oozie, Mahout, Where Hadoop fits in the Enterprise, Review use cases

Apache Hive & Pig for Developers

Overview of Hadoop

Why Hadoop, Hadoop Basic Concepts, Hadoop Ecosystem – MapReduce, Hadoop Streaming, Hive, Pig, Flume, Sqoop, Hbase, Oozie, Mahout, Where Hadoop fits in the Enterprise, Review use cases

Overview of Hadoop

Big Data and the Distributed File System, MapReduce

Hive Introduction

Why Hive?, Compare vs SQL, Use Cases

Hive Architecture – Building Blocks

Hive CLI and Language (Exercise), HDFS Shell, Hive CLI, Data Types, Hive Cheat-Sheet, Data Definition Statements, Data Manipulation Statements, Select, Views, GroupBy, SortBy/DistributeBy/ClusterBy/OrderBy, Joins, Built-in Functions, Union, Sub Queries, Sampling, Explain

Hive Architecture – Building Blocks

Hive CLI and Language (Exercise), HDFS Shell, Hive CLI, Data Types, Hive Cheat-Sheet, Data Definition Statements, Data Manipulation Statements, Select, Views, GroupBy, SortBy/DistributeBy/ClusterBy/OrderBy, Joins, Built-in Functions, Union, Sub Queries, Sampling, Explain

Hive Usecase implementation -(Exercise)

Use Case 1, Use Case 2, Best Practices

Advance Features

Transform and Map-Reduce Scripts, Custom UDF, UDTF, SerDe, Recap and Q&A

Pig Introduction

Position Pig in Hadoop ecosystem, Why Pig and not MapReduce, Simple example (slides) comparing Pig and MapReduce, Who is using Pig now and what are the main use cases, Pig Architecture, Discuss high level components of Pig, Pig Grunt - How to Start and Use

Pig Latin Programming

Data Types, Cheat sheet, Schema, Expressions, Commands and Exercise, Load, Store, Dump, Relational Operations,Foreach, Filter, Group, Order By, Distinct, Join, Cogroup,Union, Cross, Limit, Sample, Parallel

Use Cases (working exercise)

Use Case 1, Use Case 2, Use Case 3 (compare pig and hive)

Advanced Features, UDFs

Best Practices and common pitfalls

Mahout & Machine Learning

Mahout Overview, Mahout Installation, Introduction to the Math Library, Vector implementation and Operations (Hands-on exercise), Matrix Implementation and Operations (Hands-on exercise), Anatomy of a Machine Learning Application

Classification

Introduction to Classification, Classification Workflow, Feature Extraction, Classification Techniques (Hands-on exercise)

Evaluation (Hands-on exercise)

Clustering, Use Cases, Clustering algorithms in Mahout, K-means clustering (Hands-on exercise), Canopy clustering (Hands-on exercise)

Clustering

Mixture Models, Probabilistic Clustering – Dirichlet (Hands-on exercise), Latent Dirichlet Model (Hands-on exercise), Evaluating and Improving Clustering quality (Hands-on exercise), Distance Measures (Hands-on exercise)

Recommendation Systems

Overview of Recommendation Systems, Use cases, Types of Recommendation Systems, Collaborative Filtering (Hands-on exercise), Recommendation System Evaluation (Hands-on exercise), Similarity Measures, Architecture of Recommendation Systems, Wrap Up

Track Weekdays Weekend Track Fast Track
Course Duration 45-60 Days 8 Weekends Customized
Hours 1-2 hours a day 2-3 hours a day Customized
Training Mode 1 Live Classroom Live Classroom Live Classroom
Training Mode 2 Online Online Online

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Learning Outcomes

  • Our all faculty having 6 to 10+ years current industry experience.
  • Our all trainer are certified professionals.
  • We have 60+ system lab with latest version of hardware and software.
  • We conduct 100 % free personality development classes with Mock Job interviews & Presentation skills.
  • We provide 100% free study material in form of E-Book’s, video, Dumps paper, 800 Interview Questions with Project and Source material.
  • After completing course we offer course complete Certificate along with 6 months company experience latter.
  • We offer 100% placement with reference interview call.
  • Hostel facilities available at Rs.4,500/- per month
  • Webtrackker Top Placement Company are :- HCL, Wipro, Dell, Birlasoft, TechMahindra, TCS, IBM etc.
  • Webtrackker hr team focuses on Group Discussions, personality development, and create students RESUME as per current company standards .
  • After completion of 70% training course content, we will arrange the interview calls to students & prepare them to F2F interaction. See webtrackker Recent Placed Candidates.
  • CV Designing as per the company standard (Job Description).
  • We provide Job Portal for Credentials so that Candidates can apply the job.
  • We provide 100% placement assistance
  • We provides interviews calls till Placement.

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