elsonrodriguez

kind: StorageClass
apiVersion: storage.k8s.io/v1beta1
metadata:
  name: fast
provisioner: kubernetes.io/gce-pd
parameters:
  type: pd-ssd

rondy

FWIW: I (@rondy) am not the creator of the content shared here, which is an excerpt from Edmond Lau's book. I simply copied and pasted it from another location and saved it as a personal note, before it gained popularity on news.ycombinator.com. Unfortunately, I cannot recall the exact origin of the original source, nor was I able to find the author's name, so I am can't provide the appropriate credits.

---

Effective Engineer - Notes

• By Edmond Lau
• Highly Recommended 👍
• http://www.theeffectiveengineer.com/

What's an Effective Engineer?

sonnenjon

/*NPS ROLLING 30-DAYS AVG AND DAILY SCORE CHART*/
SELECT a.date,
	a.net_promoters / a.responses * 100 AS score,
	(SUM(b.net_promoters)
		 /
	SUM(b.responses)) * 100 AS score_30d
FROM (
SELECT date(s.created_at) AS date,
	SUM(CASE WHEN s.score >= 9 THEN 1.0
			WHEN s.score <= 6 THEN -1.0

odewahn

I really liked @tjvantoll article Handling Failed HTTP Responses With fetch(). The one thing I found annoying with it, though, is that response.statusText always returns the generic error message associated with the error code. Most APIs, however, will generally return some kind of useful, more human friendly message in the body.

Here's a modification that will capture this message. The key is that rather than throwing an error, you just throw the response and then process it in the catch block to extract the message in the body:

fetch("/api/foo")
  .then( response => {
    if (!response.ok) { throw response }
    return response.json()  //we only get here if there is no error
 })

valyala

Optimizing postgresql table for more than 100K inserts per second

• Create UNLOGGED table. This reduces the amount of data written to persistent storage by up to 2x.
• Set WITH (autovacuum_enabled=false) on the table. This saves CPU time and IO bandwidth on useless vacuuming of the table (since we never DELETE or UPDATE the table).
• Insert rows with COPY FROM STDIN. This is the fastest possible approach to insert rows into table.
• Minimize the number of indexes in the table, since they slow down inserts. Usually an index on time timestamp with time zone is enough.
• Add synchronous_commit = off to postgresql.conf.
• Use table inheritance for fast removal of old data:

duffn

DROP TABLE if exists d_date;

CREATE TABLE d_date
(
  date_dim_id              INT NOT NULL,
  date_actual              DATE NOT NULL,
  epoch                    BIGINT NOT NULL,
  day_suffix               VARCHAR(4) NOT NULL,
  day_name                 VARCHAR(9) NOT NULL,
  day_of_week              INT NOT NULL,

Integralist

Basic

import code; code.interact(local=locals())

Advanced

IPython with embed()

uniruddh

import Foundation
import UIKit

class RestService{
    
    /**
    GET respons from REST API.
    
    :param: reqUrl            URL of webservice.
    :param: completionHandler callback function, this will called once you get response.

m-ou-se

# Download latest archlinux bootstrap package, see https://www.archlinux.org/download/
wget 'ftp://ftp.nluug.nl/pub/os/Linux/distr/archlinux/iso/latest/archlinux-bootstrap-*-x86_64.tar.gz'

# Make sure you'll have enough entropy for pacman-key later.
apt-get install haveged

# Install the arch bootstrap image in a tmpfs.
mount -t tmpfs none /mnt
cd /mnt
tar xvf ~/archlinux-bootstrap-*-x86_64.tar.gz --strip-components=1

kylemcdonald

import PIL.Image
from cStringIO import StringIO
import IPython.display
import numpy as np
def showarray(a, fmt='png'):
    a = np.uint8(a)
    f = StringIO()
    PIL.Image.fromarray(a).save(f, fmt)
    IPython.display.display(IPython.display.Image(data=f.getvalue()))