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Hey! I saw this has been indexed by the search engines. It is a first draft of a post I ended up publishing on my blog at: Scaling PostgreSQL With Pgpool and PgBouncer

Thanks for stopping by!

PostgreSQL and Pgpool Architecture

MySQL - XtraBackupを使ったバックアップ＆リストアについて

■ 前提環境

ScientificLinux 6.3 (x86_64)

「旅の恥は掻き捨て」ではないですが，過去の恥を書き捨てるつもりで書きます．だから，今回はgistに載せます．

今回は，就活で全敗した話と博士進学を決心した後に起こったイベントについて話します．「就活で全敗」と書きましたけど，ワイドショーで取り上げられるような「50社以上を受けた」というレベルではなく，数社を受けたレベルなので，全敗という字面ほど重くはないです．最初に，僕の主張を述べておくと，

就活やるなら就職するつもりでやらないと時間の無駄
博士課程進学の相談は，早めに，丁寧に．

ということです．

時雨堂を支える技術

日時:	2024-11-10
作:	時雨堂
バージョン:	2024.5
URL:	https://shiguredo.jp/

時雨堂クラウドサービスを支える技術

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

	##########################################################
	# How to NEVER use Lambdas. An inneficient and yet educa-#
	# tonal guide to the proper misuse of the lambda constru-#
	# ct in Python 2.x. [DO NOT USE ANY OF THIS EVER] #
	# by: e000 (13/6/11) #
	##########################################################

	## Part 1. Basic LAMBDA Introduction ##
	# Well, it's worth diving straight into what lambdas are.
	# Lambdas are pretty much anonymous "one line" functions

	# codec: blocks

	describe('articles.views.ArticleView'):

	context('when user has permissions'):

	it('should add new article'):
	# some code

	it('should delete existing article'):

	""":mod:`hstore` --- Using PostgreSQL hstore with SQLAlchemy
	~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

	.. note::

	I released it under Public Domain. Feel free to use!

	It provides :class:`Hstore` type which makes you to store Python
	dictionaries into hstore columns in PostgreSQL. For example::

	Notes on how to use AWS SNS:

	1. Subscribe an HTTP endpoint (i.e. http://myhost/sns_endpoint) on AWS Console
	2. AWS will send subscription confirmation right away
	3. SNS_controller responds to subscription confirmation by sending confirmation using Fog.
	4. Once AWS is happy, you can start sending notifications to your end point via SNS.

	from datetime import datetime
	from sqlalchemy import Column, Integer, DateTime, ForeignKey
	from sqlalchemy.orm import relationship
	from sqlalchemy.ext.declarative import declared_attr
	from flask_security import current_user


	class AuditMixin(object):
	created_at = Column(DateTime, default=datetime.now)
	updated_at = Column(DateTime, default=datetime.now, onupdate=datetime.now)