cgbystrom

# Monkey patching with redis-py didn't work out so well
#from gevent import monkey; monkey.patch_all()
import gevent
import redis
import time
import random

client = redis.Redis(host='localhost', port=6379, db=0)
client.flushdb()

cgbystrom

# Monkey patching with redis-py didn't work out so well
#from gevent import monkey; monkey.patch_all()
import gevent
import redis
import time
import random

client = redis.Redis(host='localhost', port=6379, db=0)
client.flushdb()

cgbystrom

var bp = require('beaconpush');

// Create a new client
var beaconpush = new bp.Client('<your-api-key>', '<your-secret-key>');

// Get number of users currently connected to your site
beaconpush.usersConnected(function (numConnected) {
  console.log('There are ' + numConnected + ' users online');
});

cgbystrom

import java.util.ArrayList;

public class TestArrayIteration {
    public static void testArray() {
        Integer[] arr = new Integer[1000];
        for (int i = 0; i < 1000; i++) {
            arr[i] = 1;
        }

        int total = 0;

cgbystrom

public class StringTokenizer {
    public static String[] tokenize(String string, char delimiter) {
        String[] temp = new String[(string.length() / 2) + 1];
        int wordCount = 0;
        int i = 0;
        int j = string.indexOf(delimiter);
        
        while( j >= 0) {
            temp[wordCount++] = string.substring(i, j);
            i = j + 1;

cgbystrom

Reports for netperf's TCP_CRR test (i.e TCP accept() performance)

Below is list of results collected with netperf. The interesting value is TCP_CRR, it measures how fast it can TCP connect/request/response/receive. In short, the transaction rate. The test is used to simulate a normal HTTP/1.0 transaction. What's worrying is that this value has very low on Xen virtualized guests. Performance differences between bare metal and virtualization has been as high as 2-3x.

cgbystrom

(function (){
    /*!
 * jQuery JavaScript Library v1.6.2
 * http://jquery.com/
 *
 * Copyright 2011, John Resig
 * Dual licensed under the MIT or GPL Version 2 licenses.
 * http://jquery.org/license
 *
 * Includes Sizzle.js

cgbystrom

# Naive implementation of an activity stream service using Cassandra.
# Just a proof of concept and not anything that is for production use.
# Probably flawed in many ways like proper key usage, writing and features.

import pycassa
import datetime
import uuid

pool = pycassa.connect('Actstream')

cgbystrom

import org.jboss.netty.channel.*;
import org.jboss.netty.util.HashedWheelTimer;
import org.jboss.netty.util.Timeout;
import org.jboss.netty.util.Timer;
import org.jboss.netty.util.TimerTask;

import java.util.concurrent.TimeUnit;

/**
 * Simulates latency of Netty events

cgbystrom

"""
Prints usage for Route 53 for a given time period
(exported from the Amazon Route 53 usage console).
"""

import csv
route53_reader = csv.reader(open('route_53_usage_february_2012.csv', 'rb'), delimiter=',', quotechar='|')
route53_reader.next() # Skip header

zone_lookup = dict('INSERT_ZONE_ID'='mydomain.com')