Leo Moore leommoore

JavaScript - Memoization

Memoization is a programming technique which attempts to increase a function’s performance by caching its previously computed results. Because JavaScript objects behave like associative arrays, they are ideal candidates to act as caches. Each time a memoized function is called, its parameters are used to index the cache. If the data is present, then it can be returned, without executing the entire function. However, if the data is not cached, then the function is executed, and the result is added to the cache.

Memoization can potentially increase performance by caching the results of previous function calls.
Memoized functions store a cache which is indexed by their input arguments. If the arguments exist in the cache, then the - cached value is returned. Otherwise, the function is executed and the newly computed value is added to the cache.
Object arguments should be stringified before using as an index.
Memoization can be automatically applied to referentially transpa

#Node - Running in Production This gist is based on the excellent post by @hacksparrow which is found at http://www.hacksparrow.com/running-express-js-in-production-mode.html. The main principle is that you want the application to detect that it is running on a production server and to use the production configuration. The way to do this is to set the NODE_ENV=production. To do this you need to do the following:

$ export NODE_ENV=production

But we have a little problem here. The NODE_ENV environment variable will be lost if the server restarts, so it is safer to put it in the .bash_profile file. That way the variable will set again every time the system reboots. You will find the file in your home directory. It's a hidden file, so you can't see it unless you do a ls -la. We will append the export command to the .bash_profile file.

#MongoDB MapReduce

(See http://mapreduce.org/ for more information on MapReduce)

MapReduce is a programming framework popularized by Google and used to simplify data processing across massive data sets. As people rapidly increase their online activity and digital footprint, organizations are finding it vital to quickly analyze the huge amounts of data their customers and audiences generate to better understand and serve them. MapReduce is the tool that is helping those organizations.

Most enterprises deal with multiple types of data (text, rich text, rdbms, graph, etc…) and need to process all this data quickly and efficiently to derive meaningful insights that bring business value to the organization. With MapReduce, computational processing can occur on data stored either in a filesystem (unstructured) or within a database (structured).

There are two fundamental pieces of a MapReduce query:

#MongoDB - Setting up a Replica Set

cd \mongodbdir\

mkdir db1
mkdir db2
mkdir db3

###Primary mongod --dbpath ./db1 --port 30000 --replSet "demo"

#MongoDB - Mongo Shell

###Single Task You can run commands in MongoDB from the command prompt by feeding the command into the mongo shell using:

mongo server1/admin --eval "db.runCommand({logRotate:1})"

mongo localhost:30000/admin --eval "db.runCommand({logRotate:1})"

This example will rotate the log file without remaining in the mongo shell. Note: admin refers to the admin database. Executing the command returns:

#MongoDB - Basic Commands

##Saving Data

db  //Tells you the current database

show collections //Shows the collections available in the current db

db.foo.save({_id:1, x:10}) //Save the document into the foo collection

db.bar.save({_id:1, x:10}) //Save the document into the bar collection

#JavaScript - Observer Pattern An array of subscribers are just callback functions

addSubscriber() and removeSubscriber() methods that add to and remove from the subscribers array
A publish() method that takes data and calls all subscribers, passing the data to them
A make() method that takes any object and turns it into a publisher by adding all of the above methods to it

var observer = {

#Ubuntu - Installing Java

##Java 8 sudo add-apt-repository ppa:webupd8team/java sudo apt-get update sudo apt-get install oracle-java8-installer

##To install the JDK

sudo apt-get install python-software-properties

#MongoDB - JavaScript Since a query may return a large number of records which is too large for the client, the find returns a cursor instead of the data. This cursor can be assigned to a variable.

var vendorCursor = db.vendors.find();

You can see the size of the cursor using:

vendorCursor.size();

You can check to see if there is more data after the current cursor point in the data set using:

	var app = require(process.cwd() + '/app');
	var winston = require('winston');
	var _ = require('lodash');

	// Set up logger
	var customColors = {
	trace: 'white',
	debug: 'green',
	info: 'green',
	warn: 'yellow',