this presentation has small introduction about Big data and hadoop framework for beginners . Hope you like it.

1. Presentation on
Big Data & Hadoop
PRESENTED BY:
AROHI KHANDELWAL
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2. Contents :
 What is BIG DATA ?
 Why BIG DATA ?
 Hadoop
 Hadoop Architecture
 Hadoop Distributed File System
 HDFS Architecture
 Map Reduce
 How Map Reduce Works ?
 Hadoop Ecosystem
 What is Hadoop used for ?
 Users of Hadoop
 Advantage & Disadvantage of Hadoop
 Conclusion
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3. What Is BIG DATA ?
Big
Data
Volume
Variety
Velocity
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4. Why BIG DATA ?
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Mobile phone increased 70.3% to 918m in last two years.
Twitter has 328m monthly active users – 55% growth
Facebook has 765m active users.
Google+ has 495m monthly active users – grow 45%
LinkedIn has 300m users.
On every single minute 48 hours of video are posted.

5. Hadoop :
 Open source distributed computing framework .
 Built on Java and Scala languages.
 Named by Doug Cutting on his son’s toy elephant.
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Storage Process Hadoop

6. Hadoop Architecture :
 Hadoop designed and built on two independent frame works namely :
Hadoop Distributed File System
Map Reduce
Hadoop
Map ReduceHDFS
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7. Hadoop Distributed File System :
 Based on Google File System.
 Data is stored in the form of blocks .
 Provide data reliability.
 Provide fast processing on data.
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8. HDFS Architecture :
 Hadoop Distributed File System has : Name node
Data nodes
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9. Map Reduce :
Map Reduce
ReduceMap
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Takes a set of data & breaks
individual elements into tuple
Takes Map’s o/p as i/p and
combine those data tuple
forming a similar set of tuple

10. How Map Reduce works ?
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11. Hadoop
Ecosystem :
HDFS
YARN Map Reduce V2
HBASE
HIVE
Apache Pig
Oozie
Zookeeper
Sqoop
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12. What is Hadoop used for ?
• Yahoo , AmazonSearch
• Facebook , YahooLog processing
• Facebook , AOLData Warehouse
• New York Times
Video & Image
Analysis
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13. Users of Hadoop :
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14. Advantage of Hadoop :
 platform independent.
 Block structured file system.
 We can store any thing.
 Huge storage capacity.
 Rapidly process large amounts of data in parallel.
 Fault-tolerance.
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15. Disadvantage of Hadoop :
 Not Fit for Small Data
 Setup Issue
 Programming model is very restrictive
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16. Summery
 Hadoop excels at Big Data , analytics , batch
processing.
 Not real-time , no random access ; not a database.
 HDFS makes it all possible:
Fault tolerant file system
Fast accessing speed .
 Pig , Hive are easy to use.
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