School For Training
Big Data
Back to Dashboard

Hey there, great course, right? Do you like this course?

All of the most interesting lessons further. In order to continue you just need to purchase it

CALL NOW

Course sections

Section 1
Module 1
1
PL-SQL (Procedure Language – SQL)
2
Introduction to Programming Languages
3
Introduction to PL/SQL
4
The Advantages of PL/SQL
5
PL/SQL Architecture
6
PL/SQL Data types
Section 2
During this course
Section 3
you will learn:
1
Introduction to Big Data and Analytics
2
Introduction to Hadoop
3
Hadoop Ecosystem – Concepts
4
Hadoop MapReduce Concepts and Features
5
Developing the MapReduce Applications
6
Pig Concepts
7
Hive Concepts
8
Sqoop Concepts
9
Flume Concepts
10
Oozie Workflow Concepts
11
Impala Concepts
12
Hue Concepts
13
HBASE Concepts
14
ZooKeeper Concepts
15
Real Life Use Cases
Section 4
Reporting Tool
1
Tableau
Section 5
Virtualbox/VM Ware
1
Basics
2
Installations
3
Backups
4
Snapshots
Section 6
Linux
1
Basics
2
Installations
3
Commands
Section 7
Hadoop
1
Why Hadoop?
2
Scaling
3
Distributed Framework
4
Hadoop v/s RDBMS
5
Brief History of Hadoop
Section 8
Setup hadoop
1
Pseudo Mode
2
Cluster Mode
3
Ipv6
4
Ssh
5
Installation of Java, Hadoop
6
Configurations of Hadoop
7
Hadoop Processes ( NN, SNN, JT, DN, TT)
8
Temporary Directory
9
Common Errors when running Hadoop Cluster, Solutions
Section 9
HDFS- Hadoop Distributed File System
1
HDFS Design and Architecture
2
HDFS Concepts
3
Interacting HDFS using Command-Line
4
Interacting HDFS using Java APIs
5
Dataflow
6
Blocks
7
Replica
Section 10
Hadoop Processes
1
Name Node
2
Secondary Name Node
3
Job Tracker
4
Task Tracker
5
Data Node
Section 11
MapReduce
1
Developing MapReduce Application
2
Phases in MapReduce Framework
3
Map Reduce Input and Output Formats
4
Advanced Concepts
5
Sample Applications
6
Combiner
Section 12
Joining datasets in MapReduce jobs
1
Map-side Join
2
Reduce-side Join
Section 13
MapReduce – Customization
1
Custom Input Format Class
2
Hash Partitioner
3
Custom Partitioner
4
Sorting Techniques
5
Custom Output Format Class
Section 14
HADOOP PROGRAMMING LANGUAGES
1
HIVE
2
PIG
Section 15
OVERVIEW – HADOOP DEVELOPER
Section 16
Introduction – The Motivation for Hadoop
1
Problems with Traditional Large-scale Systems
2
Requirements for a New Approach
Section 17
Hadoop: Basic Concepts
1
An Overview of Hadoop
2
The Hadoop Distributed File System
3
Hands-On Exercise
4
How MapReduce Works
5
Hands-On Exercise
6
Anatomy of a Hadoop Cluster
7
Other Hadoop Ecosystem Components
Section 18
Writing a MapReduce Program
1
The MapReduce Flow
2
Examining a Sample MapReduce Program
3
Basic MapReduce API Concepts
4
The Driver Code
5
The Mapper
6
The Reducer
7
Hadoop’s Streaming API
8
Using Eclipse for Rapid Development
9
Hands-on Exercise
10
The New MapReduce API
Section 19
Common Map Reduce Algorithms
1
Sorting and Searching
2
Indexing
3
Machine Learning With Mahout
4
Term Frequency – Inverse Document Frequency
5
Word Co-occurrence
6
Hands-On Exercise
Section 20
PIG Concepts..
1
Data Loading in PIG
2
Data Extraction in PIG
3
Data Transformation in PIG
4
Hands-on Exercise on PIG
Section 21
Hive Concepts
1
Hive Query Language
2
Alter and Delete in Hive
3
Partition in Hive
4
Indexing
5
Joins in Hive.Unions in hive
6
Industry Specific Configuration of Hive Parameters
7
Authentication
8
Statistics with Hive
9
Archiving in Hive
10
Hands-on exercise
Section 22
Working with Sqoop
1
Introduction
2
Import Data
3
Export Data
4
Sqoop Syntax
5
Databases Connection
6
Hands-on exercise
Section 23
Working with Flume
1
Introduction
2
Configuration and Setup
3
Flume Sink with Example
4
Channel
5
Flume Source with Example
6
Complex Flume Architecture
Section 24
OOZIE
1
OOZIE Concepts
Section 25
IMPALA
1
IMPALA Concepts
Section 26
HUE
1
HUE Concepts
Section 27
HBASE
1
HBASE Concepts
Section 28
Zookeepers
1
Zookeepers concepts
Section 29
Reporting Tool
1
Reporting Tool

OOZIE

OOZIE Concepts

Lesson is locked. Please Buy course to proceed.

Working with Flume Complex Flume Architecture
Completed
IMPALA IMPALA Concepts
Get Widget
Get Widget