Get & Set Method in Salesforce

Getter and setter methods are used to pass data from your visualforce page to your controller and vice versa..

Let's take a very simple scenario... Let's assume you want to display a textbox in your visualforce page.. When the user enters some value in this textbox and clicks on a button you want the value entered by the user in your Apex class (ie. basically your controller or extension)

So go ahead and create a simple visualforce page.. the code for this would be

<apex:page controller="simplegetset">
  <apex:form>
    <apex:outputlabel value="Enter your name here"/>
       <apex:inputtext value="{!userinput}"/>          
  </apex:form>    
</apex:page>

The Apex code for this page would be...

public class simplegetset
{
    public String userinput{get; set;}
}

Now, the variable "userinput" in your Apex class will store the value entered by the user....

Let's analyze the methods now...

Get

The "get" method is used to pass data from your Apex code to your Visualforce page.. In our example we are not passing any value.. hence, when your page loads initially the textbox will have a empty value...

So, lets modify our code and pass a default value to the textbox.. Change the Apex code as follows..

public class simplegetset
{  
    public String userinput;
    public String getuserinput(){return 'John';}
   
    public void setuserinput(String userinput)
    {
        this.userinput = userinput;
    }   
}

You can now see that your page loads with a value 'John'...

Set

The "set" method is used to pass values from your visualforce page to the controller... In our example the variable "userinput" will be storing the value entered in the textbox..

Now modify your VF page as below..

<apex:page controller="simplegetset">
  <apex:form>
    <apex:outputlabel value="Enter your name here"/>
       <apex:inputtext value="{!userinput}">
           <apex:actionsupport event="onclick" rerender="display" />
       </apex:inputtext>                   
    <apex:outputpanel id="display">
        <apex:outputtext value="The name entered is {!userinput}"/>
    </apex:outputpanel>                   
  </apex:form>    
</apex:page>

The Apex code would be...

public class simplegetset
{
    public String userinput{get; set;}
}

In this example what happens is.. the variable "userinput" stores the value entered in visualforce page and passes it to the Apex code.. hence you are able to see the entered value in the visualforce page..

I guess you might understand what i am saying.. to make things simple now use the same visualforce page.. but modify the Apex code as below..

public class simplegetset
{  
    public String userinput;
    public String getuserinput(){return 'John';}
   
    public void setuserinput(String userinput)
    {
        this.userinput = userinput;
    }   
}

Now, whatever value you enter the page always displays "The name entered is John".... This is because your get method always returns 'John'... but still your set method will store the value you entered in the variable "userinput"....


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Pig Exercise Part V

        Here I am sharing few exercise that can be helpful for project purpose.
Data analysis can be done by Pig:
Here I am taking weatherData to analysis purpose.

For raw data comment your mail ID in comment section.





----loading and parsing data-----

A = load '/weatherPIG' using TextLoader as (data:chararray);
AF = foreach A generate TRIM(SUBSTRING(data, 6, 14)), TRIM(SUBSTRING(data, 46, 53)), TRIM(SUBSTRING(data, 38, 45));
store AF into '/data9' using PigStorage(',');
S = load '/data9/part-m-00000' using PigStorage(',') as (date:chararray, min:double, max:double);

-------Hot Days------

X = filter S by max > 25;

-------Cold Days------

X = filter S by min < 0;

-------Hottest Day-----

H1 = group S all;     /* puts S's data in H1's Tuple */
I = foreach H1 generate MAX(S.max) as maximum;
X = filter S by max == I.maximum;

-------Coldest Day------

H2 = group S all;
J = foreach H2 generate MIN(S.min) as minimum;
X = filter S by min == J.minimum;

Pig Exercise-Part IV

Here is the exercise for pig language. It is referring to some raw data as it is large in space so it cannot be posted here.

For raw data post your email ID in comment.

A. Load Customer records
========================
cust = load '/input/custs' using PigStorage(',') as (custid:chararray, firstname:chararray, lastname:chararray,age:long,profession:chararray);

B. Select only 100 records
==========================
amt = limit cust 100;
dump amt;

c. Group customer records by profession
=======================================
groupbyprofession = group cust by profession;

D. Count no of customers by profession
======================================
countbyprofession = foreach groupbyprofession generate group, COUNT(cust);
dump countbyprofession;

E. Load transaction records
===========================
txn = load '/input/txns' using PigStorage(',') as(txnid:chararray, date:chararray,custid:chararray,amount:double,category:chararray,product:chararray,city:chararray,state:chararray,type:chararray);

F. Group transactions by customer
=================================
txnbycust = group txn by custid;

G. Sum total amount spent by each customer
==========================================
spendbycust = foreach txnbycust generate group, SUM(txn.amount);

H. Order the customer records beginning from highest spender
============================================================
custorder = order spendbycust by $1 desc;

I. Select only top 100 customers
================================
top100cust = limit custorder 100;

J. Join the transactions with customer details
==============================================
top100join = join top100cust by $0, cust by $0;
describe top100join;

K. Select the required fields from the join for final output
============================================================
top100 = foreach top100join generate $0,$3,$4,$5,$6,$1;
describe top100;

L.Dump the final output
=======================
dump top100;


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Pig Exercise-part III

Here is Pig programs for wordcount

myinput = load '/sample.txt' as (line);
//TOKENIZE splits the line into a field for each word. 
//flatten will take the collection of records returned by TOKENIZE and
//produce a separate record for each one, calling the single field in the
//record word.

words = foreach myinput generate flatten(TOKENIZE(line)) as word;

grpd = group words by word;

cntd = foreach grpd generate group, COUNT(words);

dump cntd;


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Pig Exercise Part-II

Suppose we have 4 column data with field language, website, pagecount and page_size

    en google.com 50 100
    en yahoo.com 60 100
    us google.com 70 100
    en google.com 68 100

and we want


google.com 118
yahoo.com 60 as output.


records = LOAD '/webcount' using PigStorage(' ') as  (projectname:chararray, pagename:chararray, pagecount:int,pagesize:int);

filtered_records = FILTER records by projectname=='en';

grouped_records = GROUP filtered_records by pagename;     

results = FOREACH grouped_records generate group,SUM(filtered_records.pagecount);

sorted_result = ORDER results by $1 desc;

STORE sorted_result INTO '/YOUROUTPUT';


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Pig Exercise-part I

Note the following about bags:

• A bag can have duplicate tuples.
  
  
• A bag can have tuples with differing numbers of fields. However, if Pig tries to access a field that does not exist, a null value is substituted.
  
  
• A bag can have tuples with fields that have different data types. However, for Pig to effectively process bags, the schema of the tuples within those bags should be the same. For example, if half of the tuples include chararray fields and while the other half include float fields, only half of the tuples will participate in any kind of computation because the chararray fields will be converted to null.
  
  
  Bags have two forms: outer bag (or relation) and inner bag.
  
  

  Example: Outer Bag

  In this example A is a relation or bag of tuples. You can think of this bag as an outer bag.
  

  A = LOAD 'data' as (f1:int, f2:int, f3;int);
  DUMP A;
  (1,2,3)
  (4,2,1)
  (8,3,4)
  (4,3,3)

  Example: Inner Bag

  Now, suppose we group relation A by the first field to form relation X.
  In this example X is a relation or bag of tuples.
  
  The tuples in relation X have two fields. The first field is type int. The second field is type bag; you can think of this bag as an inner bag.
  

  X = GROUP A BY f1;
  DUMP X;
  (1,{(1,2,3)})
  (4,{(4,2,1),(4,3,3)})
  (8,{(8,3,4)})

  
  
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Patent Concept and Program

public class Patent { 
   
      public static class Map extends
    Mapper<LongWritable, Text, Text, Text> {
       
        //Mapper
       
       
        /*
         *This method takes the input as text data type and and tokenizes input
         * by taking whitespace as delimiter. Now key value pair is made and this key 
         * value pair is passed to reducer.                                             
         * @method_arguments key, value, output, reporter
         * @return void
         */   
       
        //Defining a local variable K of type Text
        Text k= new Text();

         //Defining a local variable v of type Text 
        Text v= new Text(); 

  
       
        @Override 
        public void map(LongWritable key, 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(); 

             //StringTokenizer is breaking the record (line) according to the delimiter whitespace
            StringTokenizer tokenizer = new StringTokenizer(line," "); 
 
             //Iterating through all the tokens and forming the key value pair   

            while (tokenizer.hasMoreTokens()) { 

                /* 
                 * The first token is going in jiten, second token in jiten1, third token in jiten,
                 * fourth token in jiten1 and so on.
                 */

                String jiten= tokenizer.nextToken();
                k.set(jiten);
                String jiten1= tokenizer.nextToken();
                v.set(jiten1);

                //Sending to output collector which inturn passes the same to reducer
                context.write(k,v); 
            } 
        } 
    } 
    
       
   
    /*Reducer
     * 
     * Reduce class is static and extends MapReduceBase and implements Reducer 
     * interface having four hadoop generics type Text, Text, Text, IntWritable.
     */
 
    public static class Reduce extends Reducer<Text, Text, Text, IntWritable> {
       
        @Override 
        public void reduce(Text key, Iterable<Text> values, Context context)
        throws IOException, InterruptedException {

            //Defining a local variable sum of type int

            int sum = 0; 

            /*
             * Iterates through all the values available with a key and add them together 
             * and give the final result as the key and sum of its values
             */

            for(Text x : values)
            {
                sum++;
            }
            
            //Dumping the output in context object
            
            context.write(key, new IntWritable(sum)); 
        } 
 
    } 
    
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