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lisabon 2012 [21]
2 years ago
12

Draw a Hierarchical input process output ( HIPO ) chart to represent a high - level view of the functions of the proposed system

.​
Computers and Technology
1 answer:
Morgarella [4.7K]2 years ago
5 0

The format to use in drawing the Hierarchical input process output  chart to show a high - level view of the functions of the proposed system is given in the image attached.

<h3>What is hierarchical input process output?</h3>

An HIPO model is known to be a form of hierarchical input process output model that helps in  systems analysis design and also in documentation .

Note that it is often used for depicting the modules of a system based on the use of hierarchy and for saving each module and thus by following the method used in the image attached, one can draw a Hierarchical input process output ( HIPO ) chart to represent a high - level view of the functions of the proposed system.​

Learn more about HIPO  from

brainly.com/question/2665138

#SPJ1

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TASK 1. JUMBLE ME! Direction: Arrange the jumbled letters to form a word. 1. PEREAM 2. RRENT CU 3. METREMO H 4. TORSISER 5. TANC
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<h3>What is arrangement of words?</h3>

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4 years ago
Modify the WordCount program so it outputs the wordcount for each distinct word in each file. So the output of this DocWordCount
stepladder [879]

Answer and Explanation:

package PackageDemo;

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;

import org.apache.hadoop.fs.Path;

import org.apache.hadoop.io.IntWritable;

import org.apache.hadoop.io.LongWritable;

import org.apache.hadoop.io.Text;

import org.apache.hadoop.mapreduce.Job;

import org.apache.hadoop.mapreduce.Mapper;

import org.apache.hadoop.mapreduce.Reducer;

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

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

import org.apache.hadoop.util.GenericOptionsParser;

public class WordCount {

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

{

Configuration c=new Configuration();

String[] files=new GenericOptionsParser(c,args).getRemainingArgs();

Path input=new Path(files[0]);

Path output=new Path(files[1]);

Job j=new Job(c,"wordcount");

j.setJarByClass(WordCount.class);

j.setMapperClass(MapForWordCount.class);

j.setReducerClass(ReduceForWordCount.class);

j.setOutputKeyClass(Text.class);

j.setOutputValueClass(IntWritable.class);

FileInputFormat.addInputPath(j, input);

FileOutputFormat.setOutputPath(j, output);

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

}

public static class MapForWordCount extends Mapper<LongWritable, Text, Text, IntWritable>{

public void map(LongWritable key, Text value, Context con) throws IOException, InterruptedException

{

String line = value.toString();

String[] words=line.split(",");

for(String word: words )

{

Text outputKey = new Text(word.toUpperCase().trim());

IntWritable outputValue = new IntWritable(1);

con.write(outputKey, outputValue);

}

}

}

public static class ReduceForWordCount extends Reducer<Text, IntWritable, Text, IntWritable>

{

public void reduce(Text word, Iterable<IntWritable> values, Context con) throws IOException, InterruptedException

{

int sum = 0;

for(IntWritable value : values)

{

sum += value.get();

}

con.write(word, new IntWritable(sum));

}

}

}

8 0
3 years ago
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