Our Courses
Hadoop
Terms & Conditions
Charges for the Training is NON REFUNDABLE, NON TRANSFERABLE, NON-EXTENDABLE.
Timings & Dates may vary.
In case of cancellation of Training from our side, the participants of the cancelled Training will be given an option to be upgraded to another Training. If the offer is denied by them, only then will they be considered for a refund.
If In Any Case training is cancelled by Organizers due to any reason, we will refund the fee after deducting Bank Changes.
If you are not satisfied with our teaching,then drop us email at info@smartcodingg.com
Refund will be in 3 stages:
Verification>>Approval>>Bank Credit through the same mode of payment.
Cash refund is NOT possible under any circumstance.
We are not responsible for any software failing to run/install on the participant's laptop owing to different configurations in laptops.
If you are not satisfied with the quality of services provided during the Training, drop us a mail @ info@alvinitsolutions.in
- Live classes will be conduct from Monday-Friday. You Will Also Get Life Time Access of Recorded Sessions.
- Code files will be provided.
- 2+ Live Projects
- Query solving sessions
- Certification of Completion
What you will take after course?
Hadoop Syllabus
Hadoop is an Apache project (i.e. an open source software) to store & process Big Data. Hadoop stores Big Data in a distributed & fault tolerant manner over commodity hardware. Afterwards, Hadoop tools are used to perform parallel data processing over HDFS (Hadoop Distributed File System).
Syllabus
Introduction to Big Data and Hadoop
Objectives
Need for Big Data
Three Characteristics of Big Data
Characteristics of Big Data Technology
Appeal of Big Data Technology
Handling Limitations of Big Data
Introduction to Hadoop
Hadoop Configuration
Apache Hadoop Core Components
Hadoop Core Components—HDFS
Hadoop Core Components—MapReduce
HDFS Architecture
Ubuntu Server—Introduction
Hadoop Installation—Prerequisites
Hadoop Multi-Node Installation—Prerequisites
Single-Node Cluster vs. Multi-Node Cluster
MapReduce
Characteristics of MapReduce
Real-Time Uses of MapReduce
Prerequisites for Hadoop Installation in Ubuntu Desktop 12.04
Hadoop MapReduce—Features
Hadoop MapReduce—Processes
Advanced HDFS–Introduction
Advanced MapReduce
Data Types in Hadoop
Distributed Cache
Distributed Cache (contd.)
Joins in MapReduce
Introduction to Pig
Components of Pig
Data Model
Pig vs. SQL
Prerequisites to Set the Environment for Pig Latin
Summary
Hive HBase and Hadoop Ecosystem Components
Hive, HBase and Hadoop Ecosystem Components
Objectives
Hive—Introduction
Hive—Characteristics
System Architecture and Components of Hive
Basics of Hive Query Language
Data Model—Tables
Data Types in Hive
Serialization and De serialization
UDF/UDAF vs. MapReduce Scripts
HBase—Introduction
Characteristics of HBase
HBase Architecture
HBase vs. RDBMS
Cloudera—Introduction
Cloudera Distribution
Cloudera Manager
Hortonworks Data Platform
MapR Data Platform
Pivotal HD
Introduction to ZooKeeper
Features of ZooKeeper
Goals of ZooKeeper
Uses of ZooKeeper
Sqoop—Reasons to Use It
Sqoop—Reasons to Use It (contd.)
Benefits of Sqoop
Apache Hadoop Ecosystem
Apache Oozie
Introduction to Mahout
Usage of Mahout
Apache Cassandra
Apache Spark
Apache Ambari
Key Features of Apache Ambari
Hadoop Security—Kerberos
Summary