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# get setting 
echo "stats settings" | nc localhost 11211 

# get current memory usage 
echo "stats" | nc -w 1 localhost 11211 | awk '$2 == "bytes" { print $2" "$3 }'

# start in verbose mode
/usr/local/bin/memcached -vv

# start with higher memory

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# Start server
zkServer.sh start

# Connect to server
zkCli.sh -server 127.0.0.1:2181

# Connect to server with authentification

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// dependency tree for compile scope 
gradle -q vsa-batch-processing-core:dependencies --configuration compile

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DataSourceTransactionManagerAutoConfiguration

# Initializers
org.springframework.context.ApplicationContextInitializer
org.springframework.boot.autoconfigure.logging.AutoConfigurationReportLoggingInitializer

# Auto Configure
org.springframework.boot.autoconfigure.EnableAutoConfiguration
org.springframework.boot.autoconfigure.aop.AopAutoConfiguration
org.springframework.boot.autoconfigure.amqp.RabbitAutoConfiguration

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package com.company.cache

import com.google.common.base.Charsets
import com.google.common.hash.HashFunction
import com.google.common.hash.Hasher
import com.google.common.hash.Hashing
import com.vendavo.security.pseudo.SecUser
import org.springframework.cache.interceptor.KeyGenerator
import org.springframework.security.core.Authentication
import org.springframework.security.core.context.SecurityContextHolder

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import groovy.sql.GroovyRowResult
import org.apache.commons.dbcp.BasicDataSource
import org.apache.commons.lang.StringEscapeUtils

import javax.sql.DataSource
import java.sql.ResultSet
import java.sql.Statement

/**
 * Helper class to get data from database into a simple CSV without any extra formatting.

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package com.vaadin.grails.datasource

import com.vaadin.data.util.sqlcontainer.connection.SimpleJDBCConnectionPool
import com.vaadin.grails.Grails
import org.codehaus.groovy.grails.commons.GrailsApplication

import java.sql.SQLException

class GrailsConnectionPool extends SimpleJDBCConnectionPool {

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convexHull <- function(x)
{
  indices <- chull(x[,1], x[,2])
  points <- x[indices,]
  points
}
convexHullFactory <- function()
{
  list(name=convexHull,udxtype=c("transform"),intype=c("float","float"), outtype=c("float","float"), outnames=c("x","y"))
}

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import java.util.ArrayDeque;
import java.util.Deque;

public class History<ENTITY> {

    private Deque<ENTITY> backStack = new ArrayDeque<>();
    private Deque<ENTITY> forwardStack;
    private ENTITY current;
    private int max;

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Are we missing big pictue?
Are we missing the goal and crucial features of application?
Are we talking too much about big picture, goals, crucial features? Maybe we should just do it.