2. An Overview of Hadoop
Hadoop is a open-source tool which can be used
effectively in processing huge volumes of data sets. It
works in a distributed computing scenario. Hadoop is
one of the best solution for addressing the issue of big
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 What is Hadoop.
 Why do we need Hadoop.
 How Hadoop works.
 HDFS Architecture.
 What is Map – Reduce.
 Hadoop Cluster.
 Hadoop Processes.
 Topology of a Hadoop Cluster.
 Distinction of Hadoop Framework .
 Prerequisites to learn hadoop.
4. What is Hadoop
 Hadoop is an open Sourse Framework.
 Developed by Apache Software Foundation.
 Used for distributed processing of large date sets.
 It works across clusters of computers using a simple
programming model (Map-Reduce).
5. Why do we need Hadoop
 Data is growing faster.
 Need to process multi petabytes of data.
 The performance of traditional applications is
 The number of machines in a cluster is not constant.
 Failure is expected, rather than exceptional.
6. How Hadoop Works
 The Hadoop core consists of two modules :
 Hadoop Distributed File System (HDFS) [Storage].
 Map Reduce [Processing].
7. HDFS Architecture
8. What is Map – Reduce
 Map Reduce plays a key role in hadoop framework.
 Map Reduce is a Programming model for writing
applications that rapidly process large amount of data.
 Mapper – is a function that processes input data to
generate intermediate output data.
 Reducer – Merges all intermediate data from all
mappers and generate final output data.
9. Hadoop Cluster
 A Hadoop Cluster consist of multiple machines Which
can be classified into 3 types
 Secondary Namenode
10. Hadoop Processes
 Below are the daemons (Processes) Which runs in a
Name node (Runs on a master machine)
Job Tracker (Runs on a master machine)
Data node (Runs on slave machines)
Task Tracker (Runs on slave machines)
11. Topology of a Hadoop Cluster
 Simple – Hadoop allows users to quickly write efficient
 Reliable – Because Hadoop runs on commodity
hardware, it can face frequent automatically handle
 Scalable – we can increase or decrease the number of
nodes (machine) in hadoop cluster.
 Linux bases operating system (Mac
OS, Redhat, ubuntu)
 Java 1.6 or higher version
 Disk space ( To hold HDFS data and it’s replications )
 Ram (Recommended 2GB)
 A cluster of computers.
 You can even install Hadoop on single machine.
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