The aggregation functions min and max can be done using hadoop.mapreduce package. Max and Min functions are performed over the input csv file that contains two columns of values to get minimum and maximum value for each column.
public class maxmin {
public static class maxminmapper extends Mapper<LongWritable, Text, Text, DoubleWritable> {
Text t1 = new Text();
public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
String[] colvalue = value.toString().split(“,”);
for (int i = 0; i < colvalue.length; i++) {
t1.set(String.valueOf(i + 1));
context.write(t1, new DoubleWritable(Double.parseDouble(colvalue[i])));
} } }
public static class maxminReducer extends Reducer<Text, DoubleWritable, Text, DoubleWritable> {
public void reduce(Text key, Iterable<DoubleWritable> values, Context context) throws IOException, InterruptedException {
double min = Integer.MAX_VALUE, max = 0;
Iterator<DoubleWritable> iterator = values.iterator(); //Iterating
while (iterator.hasNext()) {
double value = iterator.next().get();
if (value < min) { //Finding min value
min = value;
}
if (value > max) { //Finding max value
max = value;
} }
context.write(new Text(key), new DoubleWritable(min));
context.write(new Text(key), new DoubleWritable(max));
} }
public static void main(String[] args) throws Exception {
Path inputPath = new Path(“hdfs://localhost:54310/home/sortinput”);
Path outputDir =new Path(“hdfs://localhost:54310/home/MaxMinOutput1”);
Configuration conf = new Configuration();
Job job = new Job(conf, “Find Minimum and Maximum”);
job.setJarByClass(maxmin.class);
FileSystem fs = FileSystem.get(conf);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(DoubleWritable.class);
job.setMapperClass(maxminmapper.class);
job.setReducerClass(maxminReducer.class);
job.setInputFormatClass(TextInputFormat.class);
job.setOutputFormatClass(TextOutputFormat.class);
FileInputFormat.addInputPath(job, inputPath);
FileOutputFormat.setOutputPath(job, outputDir);
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}
Input
Output
