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Sathya Technologies is a hub for innovative trainings on the latest technologies. We are on the lookout for qualified and passionate instructors to team up with us to design and delivery cutting edge technology courses, helping the students achieve their professional and personal learning goals. Our client base provides a platform for interacting with some of the best technology companies on various training and project support program. https://sathyatech.com/hadoop-course-training-institute-ameerpet-hyderabad/

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mail us sathyainhyd@gmail com

Mail Us:-sathyainhyd@gmail.com

Call Us:- 65538958 /65538968 / 65538978

Hadoop Training

Sathya technologies is one of the best Software Training Institute in Hyderabad india.offers world

class training on various trending software technologies in hyderabad Join our hadoop

Training Classes and Get trained By Real time Industry professionals to Get hands on experience.

We provide hadoop classroom and Online trainings for students ,software and administration

professionals. Our training sessions covers all information from basic to advanced level.we ensure

that sathya tech is the best hadoop Training institute in hyderabad

HADOOP TRAINING COURSE CONTENT

MAP REDUCE

Map Reduce Architecture

Map Reduce Programing Model

Map Reduce Program structure

Hadoop streaming

Executing Java – Map Reduce Job

Understanding of Java Map Reduce Classes

Configuration

Path

Job

Mapper

Reducer

Text

Intwritables

Long writables

File Input Format

File Output Format

Generic Options Pavser

Joining Datasets in Map Reduce Jobs

Map Joins

reduce Joins

combiners partitioners

Combiners Partitioners

Python Map Reduce

Unit Testing Mapeduce Jobs

Hadoop Pipelining

Creating Input and Output Formats in Map Reduce Jobs

Text Input Format

Key Value Input Format

Sequence File Input Format

Data Localization in Map Reduce

Examples

HIVE

Introduction

Hive Architecture

Hive Metastore

Hive Query Launguage

Difference between HQL and SQL

Hive Built in Functions

Hive UDF (user defined functions)

Hive UDAF (user defined Aggregated functions)

Hive UDTF (user defined table Generated functions)

Hive Serde?

Hive & Hbase Integration

Hive Working with unstructured data

Hive Working With Xml Data

Hive Working With Json Data

Hive Working With Urls And Weblog Data

Hive – Json – Serde

Loading Data From Local Files To Hive Tables

Loading Data From Hdfs Files To Hive Tables

Tables Types

Inner Tables

External Tables

Partitioned Tables

Non – Partitioned Tables

Dynamic Partitions In Hive

Concept Of Bucketing

Hive Views

Hive Unions

Hive Joins

Multi Table / File Inserts

Inserting Into Local Files

Inserting Into Hdfs Files

Array Operations In Hive

Map (Associative Arrays) Operations in Hive

hive udf by java hive udf by python

Hive UDF by Java

Hive UDF by Python

PIG

Introduction to pig

Pig Latin Script

Pig Console / Grunt Shell

Execting Pig Latin Script

Pig Relations, Bags, Tuples, Fields

Data Types

Nulls

Constants

Expressions

Schemas

Parameter Substitution

Arithmetic Operators

Comparison Operators

Null Operators

Boolean Operators

Defence Operators

Sign Operators

Flatten Operators

Caster Operators

Relational Operators in Pig

ICOGROUP

CROSS

DISTINCT

FILTER

FOREACH

GROUP

JOIN (INNER)

JOIN (OUTER)

LIMIT

LOAD

ORDER

SAMPLE

SPILT

STORE

UNION

Diagnostic Operators in Pig

Describe

Dump

Explain

illustrate

Illustrate

Eval Functions in Pig

AVG

CONCAT

COUNT

CONI-STAR

DIFF

IS EMPTY

MAX

MIN

SIZE

SUM

TOKENIZE

writing Custom UDFS in Pig

Using Java

Using Python

SQOOP (SQL + HADOOP)

Introduction to Sqoop

SQOOP Import

SQOOP Export

Importing Data From RDBMS to HDFS

Importing Data From RDBMS to HIVE

Importing Data From RDBMS to HBASE

Exporting From HASE to RDBMS

Exporting From HBASE to RDBMS

Exporting From HIVE to RDBMS

Exporting From HDFS to RDBMS

Transformations While Importing / Exporting

Defining SQOOP Jobs

NOSQL

What is “Not only SQL”

NOSQL Advantages

What is problem with RDBMS for Large

Data Scaling Systems

Types of NOSQL & Purposes

Key Value Store

Columer Store

Document Store

Graph Store

Introduction to ricsk – NOSQL Database

Introduction to cassandra – NOSQL Database

Introduction to MangoDB and CouchDB Database

Introduction to Neo4j – NOSQL Database

Intergration of NOSQL Databases with Hadoop

hbase

HBASE

Introduction to big table

What is NOSQL and colummer store Database

HBASE Introduction

Hbase use cases

Hbase basics

Column families

Scans

Hbase Architecture

Clients

Rest

Thrift

Java

Hive

Map Reduce Integration

Map Reduce Over Hbase

Hbase data Modeling

Hbase Schema design

Hbase CRUD operators

Hive & Hbase interagation

Hbase storage handles

OOZIE

Introduction to OOZIE

OOZIE as a seheduler

OOZIE as a Workflow designer

Seheduling jobs (OOZIE CODE)

Defining Dependences between jobs

(OOZIE Code Examples)

Conditionally controling jobs

(OOZIE Code Examples)

Defining parallel jobs (OOZIE Code Examples)

FLUME

Introduction to FLUME

What is the streaming File

FLUME Architecture

FLUME Nodes & FLUME Manager

FLUME Local & Physical Node

FLUME Agents & FLUME Collector

ZOOKIPER

Introduction to ZOOKEEPER

ZOOKEEPER Architecture

Controlling Connection of Distbrited Apps

HBASE & ZOOKEEPER

flume zookeeper a sample code

Flume & ZOOKEEPER

A Sample Code

Free On Hadoop Course

Phyton & Pydoop

Mongo DB

Cascading

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