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Programming with Hadoop
Presented By
Dr. Jyoti Parsola
Contents
• Introduction
• Characteristics
• Hadoop Components
• Word Count Example
Introduction
Hadoop is Apache’s open source software framework for
distributed processing and distributed storage of large datasets
across large clusters of computers build on commodity
hardware.
Hadoop
supports
Hadoop Running applications
on big data
Big Data
Large and growing files
Unstructured data
(does not fit on relational
model)
Coming from users
,application,systems,
sensors
Big Data Challenges
Velocity Volume Variety
Traditional Approach
Big data Powerful
computer
Processing
Hadoop Approach
Big data
Broken into piece
Hadoop Approach
Big data
Computation
Computation
Computation
Computation
Combined
Result
Hadoop Components
Map Reduce
HDFS
Distributed Model
Linux
Low cost
computer
Works on
linux based
machine
Linux Linux Linux
Distributed Model
Task
Tracker
Data
Node
Task
Tracker
Data
Node
Task
Tracker
Data
Node
Task
Tracker
Data
Node
Slaves
Slaves
Master
Map Reduce
HDFS
Hadoop Framework
Slaves
Master
Fault Tolerant
Batch Processing
Slaves
Master
Application
Queue
Slaves
Master
Scalable
1000s
Hadoop Computing Model
• Two main phases: Map and Reduce
• Any job is converted into map and reduce tasks
• Developers need ONLY to implement the Map and Reduce classes
Data Flow
Shuffling and
Sorting
Blocks of
the input
file in HDFS
Map tasks (one
for each block)
Reduce tasks
Output is written
to HDFS
K’, list (V’)
Word Count
Hadoop tools
• Hive
• Hbase
• Pig
• Oozie
• Flume
• Scoop
Thank you

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hadoop overview.pptx