In my reducer part of MapReduce, I have the code
public static class IntSumReducer extends Reducer<Text, Text, Text, Text> {
private Text textValue = new Text();
private FloatWritable floatWritable = new FloatWritable();
#Override
public void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException {
double total = 0.00;
int count = 0;
for (Text val: values) {
String line = val.toString();
String[] field = line.split(",");
count+=1;
total += Float.parseFloat(field[1]);
}
String v = String.valueOf(count) + "," + String.valueOf(total);
textValue.set(v);
context.write(key, textValue);
}
}
However, the output returns 1 for every key but not the occurrences of the key. Also, how can I format the total to a number that has "," for a thousand value with 2 decimals?
Current Output
1 1, 1201.22135
Desired Output
1 3, 1,201.22
(3 is number of occurrences of key 1 and 1,201.22 is the total value of all key 1)
Related
This is a follow up question of Extracting rows containing specific value using mapReduce and hadoop
Mapper function
public static class MapForWordCount extends Mapper<Object, Text, Text, IntWritable>{
private IntWritable saleValue = new IntWritable();
private Text rangeValue = new Text();
public void map(Object key, Text value, Context con) throws IOException, InterruptedException
{
String line = value.toString();
String[] words = line.split(",");
for(String word: words )
{
if(words[3].equals("40")){
saleValue.set(Integer.parseInt(words[0]));
rangeValue.set(words[3]);
con.write( rangeValue , saleValue );
}
}
}
}
Reducer function
public static class ReduceForWordCount extends Reducer<Text, IntWritable, Text, IntWritable>
{
private IntWritable result = new IntWritable();
public void reduce(Text word, Iterable<IntWritable> values, Context con) throws IOException, InterruptedException
{
for(IntWritable value : values)
{
result.set(value.get());
con.write(word, result);
}
}
}
Output obtained is
40 105
40 105
40 105
40 105
EDIT 1 :
But the Expected output is
40 102
40 104
40 105
What am I doing wrong ?
What exactly is happening here in mapper and reducer function ?
In the context of the original question - you don't need the loop not in the mapper nor in the reducer as you are duplicating entries:
public static class MapForWordCount extends Mapper<Object, Text, Text, IntWritable>{
private IntWritable saleValue = new IntWritable();
private Text rangeValue = new Text();
public void map(Object key, Text value, Context con) throws IOException, InterruptedException
{
String line = value.toString();
String[] words = line.split(",");
if(words[3].equals("40")){
saleValue.set(Integer.parseInt(words[0]));
rangeValue.set(words[3]);
con.write(rangeValue , saleValue );
}
}
}
And in the reducer, as suggested by #Serhiy in the original question you need only one line of code:
public static class ReduceForWordCount extends Reducer<Text, IntWritable, Text, IntWritable>
{
private IntWritable result = new IntWritable();
public void reduce(Text word, Iterable<IntWritable> values, Context con) throws IOException, InterruptedException
{
con.write(word, null);
}
Regrading "Edit 1" - I will leave it a trivial practice :)
What exactly is happening
You are consuming lines of comma-delimited text, splitting the commas, and filtering out some values. con.write() should only be called once per line if all you are doing is extracting only those values.
The mapper will group all the "40" keys that you output and form a list of all the values that were written with that key. And that is what the reducer is reading over.
You should probably try this for your map function.
// Set the values to write
saleValue.set(Integer.parseInt(words[0]));
rangeValue.set(words[3]);
// Filter out only the 40s
if(words[3].equals("40")) {
// Write out "(40, safeValue)" words.length times
for(String word: words )
{
con.write( rangeValue , saleValue );
}
}
If you don't want duplicate values for the length of the split string, then get rid of the for loop.
All your reducer is doing is just printing out what it received from the mapper.
Mapper output would be something like this :
<word,count>
Reducer output would be like this :
<unique word, its total count>
Eg: A line is read and all words in it are counted and put in a <key,value> pair:
<40,1>
<140,1>
<50,1>
<40,1> ..
here 40,50,140, .. are all keys and the value is the count of number of occurrences of that key in a line. This happens in the mapper.
Then, these key,valuepairs are sent to the reducer where similar keys are all reduced to a single key and all the values associates with that key is summed to give a value to the key-value pair. So, the result of the reducer would be something like:
<40,10>
<50,5>
...
In your case, the reducer isn't doing anything. The unique values/words found by the mapper are just given out as the output.
Ideally, you are supposed to reduce & get an output like : "40,150" was found 5 times on the same line.
My Mapper task returns me following output:
2 c
2 g
3 a
3 b
6 r
I have written reducer code and keycomparator that produces the correct output but how do I get Top 3 out (top N by count) of Mapper Output:
public static class WLReducer2 extends
Reducer<IntWritable, Text, Text, IntWritable> {
#Override
protected void reduce(IntWritable key, Iterable<Text> values,
Context context) throws IOException, InterruptedException {
for (Text x : values) {
context.write(new Text(x), key);
}
};
}
public static class KeyComparator extends WritableComparator {
protected KeyComparator() {
super(IntWritable.class, true);
}
#Override
public int compare(WritableComparable w1, WritableComparable w2) {
// TODO Auto-generated method stub
// Logger.error("--------------------------> writing Keycompare data = ----------->");
IntWritable ip1 = (IntWritable) w1;
IntWritable ip2 = (IntWritable) w2;
int cmp = -1 * ip1.compareTo(ip2);
return cmp;
}
}
This is the reducer output:
r 6
b 3
a 3
g 2
c 2
The expected output from reducer is top 3 by count which is:
r 6
b 3
a 3
Restrict your output from reducer. Something like this.
public static class WLReducer2 extends
Reducer<IntWritable, Text, Text, IntWritable> {
int count=0;
#Override
protected void reduce(IntWritable key, Iterable<Text> values,
Context context) throws IOException, InterruptedException {
for (Text x : values) {
if (count > 3)
context.write(new Text(x), key);
count++;
}
};
}
Set number of reducers to 1. job.setNumReduceTasks(1).
If your Top-N elements could be stored in memory, you could use a TreeMap to store the Top-N elements and if your process could be aggregated using only one reducer.
Instantiate a instance variable TreeMap in the setup() method of your reducer.
Inside your reducer() method you should aggregate all the values for the keygroup and then compare the result with the first (lowest) key in the Tree, map.firstKey(). If your current value is bigger than the lowest value in the Tree then insert the current value into the treemap, map.put(value, Item) and then delete the lowest value from the Tree map.remove(value).
In the reducer's cleanup() method, write to the output all the TreeMap's elements in the required order.
Note: The value to compare your records must be the key in your TreeMap. And the value of your TreeMap should be the description, tag, letter, etc; related with the number.
I'm having trouble with the map functions:
The original data is stored in the tsv file:
I just want the last two columns saved:
the first is the original node(383), second is the target(4575), third is the weight(1)
383 4575 1
383 4764 1
383 5458 1
383 5491 1
public void map(LongWritable key, Text value,OutputCollector output, Reporter reporter) throws IOException {
String line = value.toString();
String[] tokens = line.split("t");
int weight = Integer.parseInt(tokens[2]);
int target = Integer.parseInt(tokens[0]);
}
Here is my code:
public void map(LongWritable key, Text value, Context context) throws IOException InterruptedException
{
String line = value.toString();
//split the tsv file
String[] tokens = line.split("/t");
//save the weight and target
private Text target = Integer.parsetxt(tokens[0]);
int weight = Integer.parseInt(tokens[2]);
context.write(new Text(target), new Intwritable(weight) );
}
}
public class Reduce extends Reducer<Text, IntWritable, Text, IntWritable>
{
#Override
public void reduce(Text key, Iterable<IntWritable> values,Context context)
throws IOException, InterruptedException
{
//initialize the count variable
int weightsum = 0;
for (IntWritable value : values) {
weightsum += value.get();
}
context.write(key, new IntWritable(weightsum));
}
}
String[] tokens = line.split("t");
should be
String[] tokens = line.split("\t");
split with spaces.
String[] tokens = line.split("\\s+");
private Text target = Integer.parsetxt(tokens[1]);
int weight = Integer.parseInt(tokens[2]);
I am a hadoop newbie.
I want to get a partition number on output file.
At first, I made a customized partitioner.
public static class MyPartitioner extends Partitioner<Text, LongWritable> {
public int getPartition(Text key, LongWritable value, int numReduceTasks) {
int numOfChars = key.toString().length();
return numOfChars % numReduceTasks;
}
}
It works. But, I want to output partition numbers 'visually' on Reducer.
How can I get a partiton number ??
Below is my reducer source.
public static class MyReducer extends Reducer<Text, LongWritable, Text, Text>{
private Text textList = new Text();
public void reduce(Text key, Iterable<LongWritable> values, Context context)
throws IOException, InterruptedException {
String list = new String();
for(LongWritable value: values) {
list = new String(list + "\t" + value.toString());
}
textList.set(list);
context.write(key, textList);
}
}
I want to put a partition number on 'list' respectively. There will be '0' or '1'.
list = new String(list + "\t" + value.toString() + "\t" + ??);
It would be great if someone helps me.
+
Thanks to the answer, I got a solution. But, It didn't work and I think I did something wrong.
Below is the modified MyPartitioner.
public static class MyPartitioner extends Partitioner {
public int getPartition(Text key, LongWritable value, int numReduceTasks) {
int numOfChars = key.toString().length();
return numOfChars % numReduceTasks;
private int bring_num = 0;
public void configure(JobConf job) {
bring_num = jobConf.getInt(numOfChars & numReduceTasks);
}
}
}
Add the below code to the Reducer class to get the partition number in a class variable which can be later used in the reducer method.
String partition;
protected void setup(Context context) throws IOException,
InterruptedException {
Configuration conf = context.getConfiguration();
partition = conf.get("mapred.task.partition");
}
I am new to Hadoop and Java. My mapper outputs text and Arraywritable. I having trouble to read ArrayWritable values. Unbale to cast .get() values to integer. Mapper and reducer code are attached. Can someone please help me to correct my reducer code in order to read ArrayWritable values?
public static class Temp2Mapper extends Mapper<LongWritable, Text, Text, ArrayWritable>{
private static final int MISSING=9999;
#Override public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException{
String line = value.toString();
String date = line.substring(07,14);
int maxTemp,minTemp,avgTemp;
IntArrayWritable carrier = new IntArrayWritable();
IntWritable innercarrier[] = new IntWritable[3];
maxTemp=Integer.parseInt(line.substring(39,45));
minTemp=Integer.parseInt(line.substring(47,53));
avgTemp=Integer.parseInt(line.substring(63,69));
if (maxTemp!= MISSING)
innercarrier[0]=new IntWritable(maxTemp); // maximum Temperature
if (minTemp!= MISSING)
innercarrier[1]=new IntWritable(minTemp); //minimum temperature
if (avgTemp!= MISSING)
innercarrier[2]=new IntWritable(avgTemp); // average temperature of 24 hours
carrier.set(innercarrier);
context.write(new Text(date), carrier); // Output Text and ArrayWritable
}
}
public static class Temp2Reducer
extends Reducer<Text, ArrayWritable, Text, IntWritable>{
#Override public void reduce(Text key, Iterable<ArrayWritable> values, Context context )
throws IOException, InterruptedException {
int max = Integer.MIN_VALUE;
int[] arr= new int[3];
for (ArrayWritable val : values) {
arr = (Int) val.get(); // Error: cannot cast Writable to int
max = Math.max(max, arr[0]);
}
context.write( key, new IntWritable(max) );
}
}
ArrayWritable#get method returns an array of Writable.
You can't cast an array of Writable to int. What you can do is:
iterate over this array
cast each item (which will be of type Writable) of the array to IntWritable
use IntWritable#get method to get the int value.
for (ArrayWritable val: values) {
for (Writable writable: val.get()) { // iterate
IntWritable intWritable = (IntWritable)writable; // cast
int value = intWritable.get(); // get
// do your thing with int value
}
}