Ameen Khan ameenkhan07

Each of these commands will run an ad hoc http static server in your current (or specified) directory, available at http://localhost:8000. Use this power wisely.

Discussion on reddit.

Python 2.x

$ python -m SimpleHTTPServer 8000

The papers included in CSE-586 reading.

Consensus and Paxos

Paxos Made Moderately Complex. Robbert Van Renesse and Deniz Altinbuken, ACM Computing Surveys, 2015.
Paxos made live - An engineering perspective. Tushar D. Chandra, Robert Griesemer, Joshua Redstone. ACM PODC, Pages: 398 - 407, 2007
ZooKeeper: Wait-free coordination for internet-scale systems P. Hunt, M. Konar, F. P. Junqueira, and B. Reed USENIX ATC 2010.
The Chubby Lock Service for Loosely-Coupled Distributed Systems. Mike Burrows, OSDI 2006.
In Search of an Understandable Consensus Algorithm. Diego Ongaro, John Ousterhout, USENIX ATC, 2014.
WPaxos: Wide Area Network Flexible Consensus. Ailidani Ailijiang, Aleksey Charapko, Murat Demirbas, Tevfik Kosar, IEEE TPDS, 2019.
Dissecting the Performance of Strongly-Consistent Replication Protocols. Ailidani Ailijiang, Aleksey Charapko, Murat Demirbas, Sigmod 2019.

Stevey's Google Platforms Rant

I was at Amazon for about six and a half years, and now I've been at Google for that long. One thing that struck me immediately about the two companies -- an impression that has been reinforced almost daily -- is that Amazon does everything wrong, and Google does everything right. Sure, it's a sweeping generalization, but a surprisingly accurate one. It's pretty crazy. There are probably a hundred or even two hundred different ways you can compare the two companies, and Google is superior in all but three of them, if I recall correctly. I actually did a spreadsheet at one point but Legal wouldn't let me show it to anyone, even though recruiting loved it.

I mean, just to give you a very brief taste: Amazon's recruiting process is fundamentally flawed by having teams hire for themselves, so their hiring bar is incredibly inconsistent across teams, despite various efforts they've made to level it out. And their operations are a mess; they don't real

What to Expect and Tips

• 45-minute systems interview, focus on responding to real world problems with an unhealthy service, such as a web server or database. The interview will start off at a high level troubleshooting a likely scenario, dig deeper to find the cause and some possible solutions for it. The goal is to probe your knowledge of systems at scale and under load, so keep in mind the challenges of the Facebook environment.
• Focus on things such as tooling, memory management and unix process lifecycle.

Systems

More specifically, linux troubleshooting and debugging. Understanding things like memory, io, cpu, shell, memory etc. would be pretty helpful. Knowing how to actually write a unix shell would also be a good idea. What tools might you use to debug something? On another note, this interview will likely push your boundaries of what you know (and how to implement it).

Design/Architecture

Interview is all about taking an ambiguous question of how you might build a system and letting

Tutorial: Designing a GraphQL API

This tutorial was created by Shopify for internal purposes. We've created a public version of it since we think it's useful to anyone creating a GraphQL API.

It's based on lessons learned from creating and evolving production schemas at Shopify over almost 3 years. The tutorial has evolved and will continue to change in the future so nothing is set in stone.

	:100000000C9439030C9480030C9480030C948003AB
	:100010000C9480030C9480030C9480030C94800354
	:100020000C9480030C9480030C942B290C94FD29D0
	:100030000C94FE1F0C9480030C9480030C9480039A
	:100040000C9480030C9480030C9480030C94800324
	:100050000C9480030C944B200C9480030C9480032C
	:100060000C9480030C9480030C9480030C94800304
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	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


	// C++ Structure

	/*The constructor initializes id to 42 when it's called. It's called an initliazation list.

	In your example, it is equivalent to
	*/

	struct TestStruct {
	int id;

	import matplotlib.pyplot as plt
	import cv2 as cv
	import numpy as np
	import os
	# import math
	from sobel import sobel

	OUTPUT_DIR = "outputs/"
	img_name = "./hough.jpg"

	def _dilate(self, img, str_img=[]):
	'''Expands the poindary of img
	'''
	w, h = img.shape
	res = np.asarray([[0 for _ in range(h)] for _ in range(w)])
	# Iterating the anchor of the structure image over the original image
	for i, im_row in enumerate(img):
	for j, im_ele in enumerate(im_row):
	if img[i][j]:
	for k in range(-1, 2):