Java programing question WeatherDaily.dat BbC COMP163 Avemge Day of First Frost

Question

Java programing question WeatherDaily.dat
BbC COMP163 Avemge Day of First Frost Farmers need to harvest their crops early enough to avoid a killing frost. For this assignment you are to write a program that reads a file created with data from the National Climatic Data Center to determine the avernge first day in the fall that a frost occurs. The file weatherDaily.dat contains several years of Greensboro daily weather data sorted by increasing date. Each line in the file represents one day's weather and contains the values: year month day precipitation snow daily high daily low date of this weather record date of this weather record from 1 to 12 date of this weather record from 1 to 31 amount of precipitation on this day amount of snow that fell on this day highest temperature recorded on this day in tenths of a degree Celsius lowest temperature recorded on this day in tenths of a degree Celsius All values are integers. The program only requires the year, month, day and daily low, although your program must read all data values in each line. a. Write a program that displays the date of the first autumn frost for each year in the file. We define an autumn frost as any day when the temperature is less than zero degrees Celsius. Fall frosts occur after July. The first day of frost is when the daily low is less than zero and the month is greater than 7. After you find the first day of frost, you need to skip the rest of the days until December 31. You can use a boolean variable to indicate that a frost has already been found b. Enhance your program to display the average last frost day of the year. You carn use the following methods to convert the year, month and day to day of the year Your program will also have to count the number of years in the file. You can display the average day of the year and then use that with the monthDay method to get the calendar day

Explanation / Answer

import java.util.Iterator;

import org.apache.hadoop.fs.Path;

import org.apache.hadoop.io.LongWritable;

import org.apache.hadoop.io.Text;

import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;

import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;

import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;

import org.apache.hadoop.mapreduce.Job;

import org.apache.hadoop.mapreduce.Mapper;

import org.apache.hadoop.mapreduce.Reducer;

import org.apache.hadoop.conf.Configuration;

public class MyMaxMin {

//Mapper

/**

*MaxTemperatureMapper class is static and extends Mapper abstract class

having four hadoop generics type LongWritable, Text, Text, Text.

*/

public static class MaxTemperatureMapper extends

Mapper<LongWritable, Text, Text, Text> {

/**

* @method map

* This method takes the input as text data type.

* Now leaving the first five tokens,it takes 6th token is taken as temp_max and

* 7th token is taken as temp_min. Now temp_max > 35 and temp_min < 10 are passed to the reducer.

*/

@Override

public void map(LongWritable arg0, Text Value, Context context)

throws IOException, InterruptedException {

//Converting the record (single line) to String and storing it in a String variable line

String line = Value.toString();

//Checking if the line is not empty

if (!(line.length() == 0)) {

//date

String date = line.substring(6, 14);

//maximum temperature

float temp_Max = Float

.parseFloat(line.substring(39, 45).trim());

//minimum temperature

float temp_Min = Float

.parseFloat(line.substring(47, 53).trim());

//if maximum temperature is greater than 35 , its a hot day

if (temp_Max > 35.0) {

// Hot day

context.write(new Text("Hot Day " + date),

new Text(String.valueOf(temp_Max)));

}

//if minimum temperature is less than 10 , its a cold day

if (temp_Min < 10) {

// Cold day

context.write(new Text("Cold Day " + date),

new Text(String.valueOf(temp_Min)));

}

}

}

}

//Reducer

/**

*MaxTemperatureReducer class is static and extends Reducer abstract class

having four hadoop generics type Text, Text, Text, Text.

*/

public static class MaxTemperatureReducer extends

Reducer<Text, Text, Text, Text> {

/**

* @method reduce

* This method takes the input as key and list of values pair from mapper, it does aggregation

* based on keys and produces the final context.

*/

public void reduce(Text Key, Iterator<Text> Values, Context context)

throws IOException, InterruptedException {

//putting all the values in temperature variable of type String

String temperature = Values.next().toString();

context.write(Key, new Text(temperature));

}

}

/**

* @method main

* This method is used for setting all the configuration properties.

* It acts as a driver for map reduce code.

*/

public static void main(String[] args) throws Exception {

                          //reads the default configuration of cluster from the configuration xml files

Configuration conf = new Configuration();

//Initializing the job with the default configuration of the cluster

Job job = new Job(conf, "weather example");

//Assigning the driver class name

job.setJarByClass(MyMaxMin.class);

//Key type coming out of mapper

job.setMapOutputKeyClass(Text.class);

//value type coming out of mapper

job.setMapOutputValueClass(Text.class);

//Defining the mapper class name

job.setMapperClass(MaxTemperatureMapper.class);

//Defining the reducer class name

job.setReducerClass(MaxTemperatureReducer.class);

//Defining input Format class which is responsible to parse the dataset into a key value pair

job.setInputFormatClass(TextInputFormat.class);

//Defining output Format class which is responsible to parse the dataset into a key value pair

job.setOutputFormatClass(TextOutputFormat.class);

//setting the second argument as a path in a path variable

Path OutputPath = new Path(args[1]);

//Configuring the input path from the filesystem into the job

FileInputFormat.addInputPath(job, new Path(args[0]));

//Configuring the output path from the filesystem into the job

FileOutputFormat.setOutputPath(job, new Path(args[1]));

//deleting the context path automatically from hdfs so that we don't have delete it explicitly

OutputPath.getFileSystem(conf).delete(OutputPath);

//exiting the job only if the flag value becomes false

System.exit(job.waitForCompletion(true) ? 0 : 1);

}

}

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