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BigData Hadoop Online Training
Hadoop Online Training

What is Hadoop?

Hadoop is an open source framework that processes large data sets (Bigdata), in a distributed storage environment. This platform can process/handle large volume of data (Bigdata) in a small amount of time. APIs for MapReduce applications enables us to read, write and compute data in parallel. It helps to run different kinds of computation on this huge volume of data with ease.

Hadoop Distributed File System (HDFS) was made to store the huge amount (hundreds of gigabytes) of data every second. This stored data is used to generate various analytics. Traditional databases cannot handle data of this size.

Hadoop Online Training course for Developer & Admin

Before you start your training, See what will you learn in this Hadoop Online training
Hadoop Online Training - BigData Online Training

1. Introduction to HADOOP

What are BIG DATA features and challenges
Problems with Traditional Large-Scale Systems
Horizontal and vertical scaling
Why Comparison with RDBMS
A brief history and Limitation
Available version

2. HADOOP CLUSTER & EcoSystem

Available Distributions of Hadoop (Apache, Cloudera, Hortonworks, etc)
Hadoop Architecture & Planning for cluster
Cluster Daemons & Its Functions :
a. Name Node
b. Secondary Node
c. Data Nodes
d. Job Tracker
e. Task Trackers
Hadoop Ecosystem components and uses

3. Hadoop HDFS

HDFS Design & Goals
Understand Blocks and Configuration of block size
Block replication, replication factor and failure handling
Understand Rack Awareness and Configuring racks in Hadoop
File read and write anatomy in HDFS

4. YARN - YET ANOTHER RESOURCE NEGOTIATOR

YARN Architecture
Components of YARN
* Resource Manager * Node Manager * Job History Server * MR Application Master YARN Application execution flow
Running and Monitoring YARN Applications
Understand and Configure Capacity / Fair Schedulers in YARN

5. HADOOP INSTALLATION & DEPLOYMENT

Setting up Apache / Cloudera environment
Specifying the Configuration
Performing Initial HDFS Configuration
Performing Initial YARN and Map-Reduce Configuration
Logging & Cluster Monitoring

6. Cloudera Hadoop SANDBOX OR QUICK START

Installation of Cloudera quick start
Difference in sandbox and distributed environment
Overview of apache HUE

7. Hadoop MAPREDUCE, MAPREDUCE STREAMING (IN JAVA)

All MapReduce API Concepts and Architecture
Writing MapReduce Drivers, Mappers, and Reducers in Java
Speeding Up Hadoop Development by Using Eclipse
Old Vs New Hadoop MapReduce APIs
Writing Mappers and Reducers with the Streaming API
Different question raised for MapReduce

8. HBASE HADOOP DATABASE

Problems with RDBMS
Introduction to HBase
Non-RDBMS, Not-Only SQL or No-SQL
Installation HBase & Deployment
Types CRUD & Batch Operations
Filters, Counters, Pool
Rest Interface & Web-UI

9. SHELL AND COMMANDS

Hadoop Developer commands using shell
Map-Reduce job deployment
Oozie workflow design
Different Components Jobs design.

10. HIVE – SQL & OLAP Layer on Hadoop

Hadoop Online Training - Apache Hive Vs PIG

Introduction – Architecture - Hive Vs RDBMS - Create Tables (Managed, external) - Managed Vs External tables
Exercise: Hive access through Hive Client - Partitioning (static and dynamic) - Serde (XML Serde, JsonSerde)
Hive Schema and Data Storage
Data Types & Introduction to SQL
Hive-SQL: DML & DDL
Hive-SQL: Views & Indexes
Explain and use the various Hive file formats
Use Hive to run SQL-like queries to perform data analysis
Use Hive to join data sets using a variety of techniques, including Mapside joins and Sort-Merge-Bucket joins
Integration to HBase & Cassandra
Sentiment Analysis and N-Grams
Hive Thrift Service

11. FLUME Hadoop

Installation of Flume
Ingesting Data from External Sources with Flume
Configuration for flume
REST Interfaces
Best Practices for Importing Data

12. SQOOP – RDBMS - Hadoop Data Acquisition

Introduction - Why Sqoop - Import Architecture - Sqoop Export Architecture
Installation of Sqoop
Ingesting Data from External (RDBMS) Sources with Sqoop
Sqoop import/export use cases hands-on
Integration of Sqoop and Hbase
Integration of Sqoop and Hive
Best Practices for Importing Data

13. Py-Spark Essentials

  • Overview – Daemons - A Spark Standalone Cluster - Components & Terminologies - Workers, Driver Programs, Tasks - Executors & Cluster Manager

    Working Pyspark (Hands-on)

    RDD Execution model - Types of RDDs - RDD Operations - Transformations and Actions - Lazy executions - RDD Lineage - Loading data in RDD – Transformations and Actions - Creating the SparkContext - REPL Commands - Different types of basic operations - Language integrated Query methods - RDD Operations - Text, CSV, JSON, Sequence, Parquet, ORC, Compression Techniques – Spark SQL

    14. CONCLUSION & FAQS

  • sessions * Hue * Cloudera Manager * Zookeeper *Impala * Ooozie * Etc

    Who can take the Big Data Hadoop Training?

    Developers, Adminstrators, Operation team members or even fresher who want to begin their careers can take this course.

    Prerequisites for Hadoop Training: None.

    Duration : 35 Hours Live Training sessions + Unlimited Real Environment Access to practice

    Machine Configuration : 8GB RAM and i3+ processor

    Features of our Hadoop Online Training:

  • 100% Flexible Timings + 100% Moneyback gurantee
  • Live Instructor Led Sessions. Dont Type your queries, Ask questions, talk to trainer
  • Install on your machine, Unlimited Real Environment Access to practice
  • Get Hadoop documents, exercises and Revisit Training Videos to View class Recordings
  • Fast-track / Regular / Weekend as per your convenience

    • Our Big Data Hadoop trainers are:

  • Certified Consultant working in MNCs
  • Excellent Trainers.

    • Demo of Hadoop Online Training

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