mwacc

library(rmr2)

rmr.options(backend = "local")
#hdfs.init()

lm.map = 
  function(., line) {
    keyval( line[[1]], paste(line[[2]], line[[3]], sep="|"))
  }

mwacc

# Spark scala project
mvn archetype:generate -B -DarchetypeGroupId=net.alchim31.maven -DarchetypeArtifactId=scala-archetype-simple -DarchetypeVersion=1.5  -DgroupId=org.apache.spark -DartifactId=<Project name> -Dversion=0.1-SNAPSHOT -Dpackage=org.apache.spark

# flink project
mvn archetype:generate                             \
    -DarchetypeGroupId=org.apache.flink            \
    -DarchetypeArtifactId=flink-quickstart-scala   \
    -DarchetypeVersion=0.9.1                       \
    -DgroupId=org.apache.flink.quickstart          \
    -DartifactId=flink-scala-project               \

mwacc

location / {
            root   /usr/domain.com/nginx/html;
            index  index.jsp;
            post_action /aftertouching;
        }

        location /aftertouching {
            proxy_pass http://10.25.0.11/count.do?resource=$request&status=$request_completion&fromIp=$remote_addr&body_bytes_sent=$body_bytes_sent;
            internal;
        }

mwacc

package example.pig;

import javassist.CannotCompileException;
import javassist.ClassPool;
import javassist.CtClass;
import javassist.CtMethod;
import javassist.NotFoundException;

public class FixHadoopOnWindows {

mwacc

int i = 0;
File file = new File("out2.csv")
file << "Id,Action\n"

new File('out.csv').eachLine { line ->
  if(i > 0) {
    file.append i
  	file.append ','
  	file.append Double.valueOf(line) > 0.6 ? 1 : 0;
  	file.append '\n'

mwacc

class Node {
  def val
	def left
	def right
}


/*
     root
   A       B

mwacc

def levenshtain(String s1, String s2, int i, int j) {
  if(i == -1 && j == -1) {
		return 0
	} else if( j == -1 && i > -1 ) {
		return i
	} else if(i == -1 && j > -1) {
		return j
	} else {
		return min(
				levenshtain(s1, s2, i, j-1)+1,

mwacc

/*
<dependencies>
        <dependency>
            <groupId>com.rabbitmq</groupId>
            <artifactId>amqp-client</artifactId>
            <version>3.1.1</version>
        </dependency>
    </dependencies>

*/

mwacc

class Constants {
    static final goods = [
        'Apple', 'Orange', 'Pineaple', 'Cherry', 'Beef', 'Sugar', 'Milk',
        'Pear', 'Limon', 'Blubbery', 'IceCream', 'Cake', 'Orange', 'Milk',
        'Cola', 'Bread', 'Coffe', 'Cookies', 'Beer', 'Tea', 'Salmon', 'Steal Water', 'Nuts']
    
}

rand = new Random()

mwacc

#Install the R package arules if required
#install.packages("arules");
#load the arules package
library("arules");
 
# read the transaction file as a Transaction class
txn = read.transactions(file="d:\\work\\R\\items.csv", rm.duplicates= FALSE, format="basket",sep=",");
 
#To visualize the item frequency in txn file
itemFrequencyPlot(txn);