prayagupa

import spark.SparkContext
import SparkContext._

/**
 * A port of [[http://blog.echen.me/2012/02/09/movie-recommendations-and-more-via-mapreduce-and-scalding/]]
 * to Spark.
 * Uses movie ratings data from MovieLens 100k dataset found at [[http://www.grouplens.org/node/73]]
 */
object MovieSimilarities {

prayagupa

package com.vast.example

import java.net.InetSocketAddress
import java.util.UUID
import java.util.concurrent.{Executors, TimeUnit}
import com.google.common.base.Splitter
import com.twitter.finagle.http.Http
import com.twitter.finagle.builder.{Server, ServerBuilder}
import com.twitter.finagle.service.TimeoutFilter
import com.twitter.finagle.{Service, SimpleFilter, GlobalRequestTimeoutException}

prayagupa

object Solution {
    def removeDuplicates(A : Array[Int]) : Array[Int] = {
      val length=A.length
      if(length==0 || length==1) A
      var index=1
      for(compareIndex <- 1 to length) {
        if(A(compareIndex)!=A(compareIndex-1)) {
          A(index)=A(compareIndex)
          index=index+1
        }

prayagupa

Examples of RESTful API calls for E-commerce platforms

These examples are type 3 RESTful API requests and responses. The JSON-HAL specification is used to implement HATEOAS.

Some of the examples are based on my work as architect of the RESTful API at http://www.hautelook.com. All proprietary information has been removed.

Relevant links

• JSON-HAL specification: http://stateless.co/hal_specification.html#media_type_identifiers
• JSON linking with HAL: http://blog.stateless.co/post/13296666138/json-linking-with-hal

prayagupa

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

---

This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

---

prayagupa

for (var i=0; i < 100000; i++) {
	db.mass_insert.save({
		"first_name": "James",
		"middle_name": "Richard",
		"last_name": "Windsgate",
		"email": "jamesrichardwindsgate@email.com"
	});
};

prayagupa

Latency numbers every programmer should know

L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns             
Compress 1K bytes with Zippy ............. 3,000 ns  =   3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs
SSD random read ........................ 150,000 ns  = 150 µs

Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs

prayagupa

import akka.actor._
import com.eventstream.PackageArrivedEvent
import com.eventstream.publisher.PackageArrivedPublisher
import com.eventstream.subscriber.PackageArrivedSubscriber

object EventStreamApplication extends App {

  implicit val system = ActorSystem("event-stream")

prayagupa

Using core.async for Producer-consumer Systems

# Set up input file
repeat 10000 echo "." >> input

# Run inline
time lein run inline < input > output

# Run async

prayagupa

Here is an example in Javascript based on a package I'm working on for Atom:

var format = '{%n  "commit": "%H",%n  "abbreviated_commit": "%h",%n  "tree": "%T",%n  "abbreviated_tree": "%t",%n  "parent": "%P",%n  "abbreviated_parent": "%p",%n  "refs": "%D",%n  "encoding": "%e",%n  "subject": "%s",%n  "sanitized_subject_line": "%f",%n  "body": "%b",%n  "commit_notes": "%N",%n  "verification_flag": "%G?",%n  "signer": "%GS",%n  "signer_key": "%GK",%n  "author": {%n    "name": "%aN",%n    "email": "%aE",%n    "date": "%aD"%n  },%n  "commiter": {%n    "name": "%cN",%n    "email": "%cE",%n    "date": "%cD"%n  }%n},';

var commits = [];

new BufferedProcess({
    command: 'git',
 args: [