wincent

2015-01-29 Unofficial Relay FAQ

Compilation of questions and answers about Relay from React.js Conf.

Disclaimer: I work on Relay at Facebook. Relay is a complex system on which we're iterating aggressively. I'll do my best here to provide accurate, useful answers, but the details are subject to change. I may also be wrong. Feedback and additional questions are welcome.

What is Relay?

Relay is a new framework from Facebook that provides data-fetching functionality for React applications. It was announced at React.js Conf (January 2015).

odil5

<?php


$ghost = 'XXX.XXX.XXX.XXX';
$guser = 'USER_NAME';
$gpwd = 'PASSWORD';
$gdbname = 'DB_NAME';

$db = mysql_connect($ghost, $guser, $gpwd) or die("Could not connect: " . mysql_error());
mysql_select_db ($gdbname, $db) or die (mysql_error($db));

vlucas

#!/bin/bash

# @link https://gist.github.com/mattscilipoti/8424018
#
# Called by "git push" after it has checked the remote status,
# but before anything has been pushed.
#
# If this script exits with a non-zero status nothing will be pushed.
#
# Steps to install, from the root directory of your repo...

tsenart

package main

import (
	"net/http"
	"database/sql"
	"fmt"
	"log"
	"os"
)

staltz

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.

---

michaljemala

package main

import (
	"crypto/tls"
	"crypto/x509"
	"flag"
	"io/ioutil"
	"log"
	"net/http"
)

chanks

Turning PostgreSQL into a queue serving 10,000 jobs per second

RDBMS-based job queues have been criticized recently for being unable to handle heavy loads. And they deserve it, to some extent, because the queries used to safely lock a job have been pretty hairy. SELECT FOR UPDATE followed by an UPDATE works fine at first, but then you add more workers, and each is trying to SELECT FOR UPDATE the same row (and maybe throwing NOWAIT in there, then catching the errors and retrying), and things slow down.

On top of that, they have to actually update the row to mark it as locked, so the rest of your workers are sitting there waiting while one of them propagates its lock to disk (and the disks of however many servers you're replicating to). QueueClassic got some mileage out of the novel idea of randomly picking a row near the front of the queue to lock, but I can't still seem to get more than an an extra few hundred jobs per second out of it under heavy load.

So, many developers have started going straight t

earthgecko

#!/bin/bash
# bash generate random alphanumeric string
#

# bash generate random 32 character alphanumeric string (upper and lowercase) and 
NEW_UUID=$(cat /dev/urandom | tr -dc 'a-zA-Z0-9' | fold -w 32 | head -n 1)

# bash generate random 32 character alphanumeric string (lowercase only)
cat /dev/urandom | tr -dc 'a-z0-9' | fold -w 32 | head -n 1

spion

Warning

This benchmark has been misleading for a while. It was originally made to demonstrate how JIT compilers can do all sorts of crazy stuff to your code - especially LuaJIT - and was meant to be a starting point of discussion about what exactly LuaJIT does and how.

As a result, its not indicative of what its performance may be on more realistic data. Differences can be expected because

1. the text will not consist of hard-coded constants

jboner

Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD