rponte

Pretende usar UUID como PK em vez de Int/BigInt no seu banco de dados? Pense novamente...

TL;TD

Não use UUID como PK nas tabelas do seu banco de dados.

Um pouco mais de detalhes

craigtp

Advanced Distributed System Design Course - Udi Dahan

Notes by Craig Phillips

Fallacies of Distributed Computing

• There are 11 fallacies of Distributed Computing:
  1. The network is reliable
  2. Latency isn’t a problem
  3. Bandwidth isn’t a problem
  4. The network is secure

5. The topology won’t change

bgadrian

type Set struct {
	list map[int]struct{} //empty structs occupy 0 memory
}

func (s *Set) Has(v int) bool {
	_, ok := s.list[v]
	return ok
}

soulmachine

First of all, please note that token expiration and revoking are two different things.

1. Expiration only happens for web apps, not for native mobile apps, because native apps never expire.
2. Revoking only happens when (1) uses click the logout button on the website or native Apps;(2) users reset their passwords; (3) users revoke their tokens explicitly in the administration panel.

1. How to hadle JWT expiration

A JWT token that never expires is dangerous if the token is stolen then someone can always access the user's data.

Quoted from JWT RFC:

pmunin

using System;
using System.Collections.Concurrent;
using System.Collections.Generic;
using System.ComponentModel;
using System.Timers;

namespace DebounceUtils
{
    /// <summary>
    /// Event debouncer helps to prevent calling the same event handler too often (like mark Dirty or Invalidate)

vasanthk

System Design Cheatsheet

Picking the right architecture = Picking the right battles + Managing trade-offs

Basic Steps

1. Clarify and agree on the scope of the system

• User cases (description of sequences of events that, taken together, lead to a system doing something useful)
  • Who is going to use it?
  • How are they going to use it?

richardkundl

namespace BloomFilter
{
	using System;
	using System.Collections;

	/// <summary>
	/// Bloom filter.
	/// </summary>
	/// <typeparam name="T">Item type </typeparam>
	public class Filter<T>

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