Hadoop is a cluster computing framework. Hadoop tools empower more developers and more organizations to leverage Hadoop for big data management. There’s been a growing demand for Hadoop tools that can make Hadoop's vast processing power more accessible. I’m going to present a Brief explanation of the various applications and tools that are associated with Hadoop. Also, I would be presenting a project how on how some of these tools where used to analyze the percentage of brain injured person in New England in the month of December 2010 survey to determine if brain transplant was an option to solve brain problem in the Nation.

1. COMPONENTS OF A
HADOOP APPLICATION
PRESENTATION BY  NICO

2. CORE COMPONENTS
 Hadoop Common
 HDSF
 Hadoop MapReduce
 YARN

3. HADOOP COMMON
• Data Access Components are - Pig and Hive

4. • Data Storage Component is - HBase

5. • Data Integration Components are -
Apache Flume, Sqoop, Chukwa

6. • Data Management and Monitoring
Components are - Ambari, Oozie and
Zookeeper

7. • Data Serialization Components are - Thrift
and Avro

8. • Data Intelligence Components are - Apache
Mahout and Drill

9. AN ANALYSIS OF BRAIN INJURY
Goal:
• Determine the percentage of brain injured
persons from New England compared to the
Nation for the month of December 2010

10. Why chose this project?
• This project was able to aloud me apply HBase,
Hive, Pig, which are tolls associated with Hadoop
common.
• These tools where available for free and easy to
navigate with.

11. Dataset source
• The dataset came from the U.S. Department
of Health and human services
 Survey to implement brain transplant

12. Dataset information
• Filename: US-DEC-2010-BRAIN
• File size: 90.2 KB (92,320 bytes).
• The data span a period of 5 years, including ~998,877
reviews up to September 2015
• Reviews include brain cancer research and department of
mental health.

13. Problem with dataset
• Only problem was unstructured – non-
traditional row-column form

14. • Dataset was then converted to .CSV format
Dataset has 100 instances and 11 attributes

15. Dataset was imported in to Hadoop common
using the file browser and then store inside
HBase.
• Using Hcatalog, a table was created that
automatically fits the number of rows and
column to suit the dataset.

16. Table US-DEC-2010-BRAIN PREVIEW

17. Data is then import into the table with a single
click (create). This would take a few minute
depending on the size of the dataset
• Actual Table US-DEC-2010-BRAIN PREVIEW

18. • Hive Query Language (HQL) was used to
generate statements that produce result of
the number of brain injured persons by state
• Target states where ME, RI, VT, NH, MA and CT

19. SELECT * FROM table_brain
WHERE table_brain.state = 'ME'
ME = 3

20. SELECT * FROM table_brain
WHERE table_brain.state = 'RI
RI = 5

21. SELECT * FROM table_brain
WHERE table_brain.state = 'VT'
VT = 0

22. NH = 1
SELECT * FROM table_brain
WHERE table_brain.state = 'NH'

23. SELECT * FROM table_brain
WHERE table_brain.state = ‘MA'
MA = 12

24. SELECT * FROM table_brain
WHERE table_brain.state = 'CT'
CT = 5

25. SELECT * FROM table_brain
NATION = 100

26. RESULT
• MAINE = 3
• VERMONT = 0
• NEW HAMPSHIRE = 1
• MASSACHUSETT = 12
• CONNECTICUT = 5
• TOTAL = 26
• NATION =100
• 26/100 = 0.26
• 0.26 * 100 = 26%

27. CONCLUSION
During a survey done in the month of
December 2010, to determine the number of brain
injured persons in the nation to enforce brain
transfer procedure, 26% of the nation’s total came
from New England.