Write a MapReduce job that processes the global weather dataset and returns the records of the country "India". The output should contain 4 different files. Each file would contain weather data of one entire century.

For example: 4 part files should contain the data in the following pattern:

• File1 : Year 1700-1799 ( All the records of the 18th century will be stored in File1)
• File2 : Year 1800-1899( All the records of the 19th century will be stored in File2)
• File3 : Year 1900-1999( All the records of the 20th century will be stored in File3)
• File4 : Year 2000-Present ( All the records of the 21st century will be stored in File4)

Input Dataset: Refer to the path given below: (hdfs:///bigdatapgp/common_folder/assignment3/weather/weather1.csv)

Dataset Description:

COLUMN NAME	DESCRIPTION
dt	Date
AverageTemperature	Average Temperature of that city
AverageTemperatureUncertainity	Uncertainty in the Average Temperature
City	Name of the city
Country	Name of the country that the city belongs to
Latitude	Latitude of the city
Longitude	Longitude of the city

Constraints:

• Skip header row while reading the file
• Use the concept of Partitioner

Expected Solution: You need to paste the MR code, Hadoop commands & path of the final jar that is used to achieve this output.