Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Look ma' I know my algorithms!
Search
Lucia Escanellas
October 24, 2014
Programming
7
450
Look ma' I know my algorithms!
RubyConf Argentina 2014
Lucia Escanellas
October 24, 2014
Tweet
Share
Other Decks in Programming
See All in Programming
複数のAWSアカウントから横断で 利用する Lambda Authorizer の作り方
tc3jp
0
120
コードを読んで理解するko build
bells17
1
110
お前もAI鬼にならないか?👹Bolt & Cursor & Supabase & Vercelで人間をやめるぞ、ジョジョー!👺
taishiyade
7
4.2k
1年目の私に伝えたい!テストコードを怖がらなくなるためのヒント/Tips for not being afraid of test code
push_gawa
1
640
はじめての Go * WASM * OCR
sgash708
1
120
なぜイベント駆動が必要なのか - CQRS/ESで解く複雑系システムの課題 -
j5ik2o
14
4.8k
Honoとフロントエンドの 型安全性について
yodaka
7
1.5k
CloudNativePGを布教したい
nnaka2992
0
120
バッチを作らなきゃとなったときに考えること
irof
2
550
Jakarta EE meets AI
ivargrimstad
0
580
メンテが命: PHPフレームワークのコンテナ化とアップグレード戦略
shunta27
0
320
CloudRun, Spanner に対する負荷試験の反省と オブザーバビリティによるアプローチ
oyasumipants
1
120
Featured
See All Featured
Navigating Team Friction
lara
183
15k
How GitHub (no longer) Works
holman
314
140k
Music & Morning Musume
bryan
46
6.4k
A designer walks into a library…
pauljervisheath
205
24k
What’s in a name? Adding method to the madness
productmarketing
PRO
22
3.3k
GitHub's CSS Performance
jonrohan
1030
460k
Easily Structure & Communicate Ideas using Wireframe
afnizarnur
193
16k
Bash Introduction
62gerente
611
210k
Rebuilding a faster, lazier Slack
samanthasiow
80
8.9k
Code Reviewing Like a Champion
maltzj
521
39k
Being A Developer After 40
akosma
89
590k
Optimizing for Happiness
mojombo
377
70k
Transcript
Look ma’, I know my algorithms!
Lucia Escanellas raviolicode
Attributions https://flic.kr/p/6DDvQP https://flic.kr/p/qv5Zp https://flic.kr/p/6SaZsP https://flic.kr/p/edauSN https://flic.kr/p/4uNfK8 https://flic.kr/p/o9ggdk https://flic.kr/p/6kfuHz https://flic.kr/p/5kBtbS
Speed Speed
Zen Elegance Elegance
Toolbox
Theory Theory
This example Not so common
FROM >30HS TO 18 S
WHY USE ORDERS? ALGORITHMS ARE POWERFUL AVOID TRAPS IN RUBY
WHY USE ORDERS? ALGORITHMS ARE POWERFUL AVOID TRAPS IN RUBY
WHY USING ORDERS? ALGORITHMS ARE POWERFUL AVOID TRAPS IN RUBY
Let’s have a look at the PROBLEM
Ordered array How many pairs (a,b) where a ≠ b
-100 <= a + b <= 100
Array: [-100, 1, 100]
Array: [-100, 1, 100] (-100, 1), (-100, 100), (1, 100)
Array: [-100, 1, 100] (-100, 1), (-100, 100), (1, 100)
-100 + 1 = 99 YES
Array: [-100, 1, 100] (-100, 1), (-100, 100), (1, 100)
-100 + 100 = 0 YES
Array: [-100, 1, 100] (-100, 1), (-100, 100), (1, 100)
1 + 100 = 101 NO
Array: [-100, 1, 100] (-100, 1), (-100, 100), (1, 100)
Result: 2
First solution Combinations of 2 elements Filter by: -100 <=
a + b <= 100
def count! combinations = @numbers.combination(2).to_a! ! combinations! .map{ |a,b| a
+ b }! .select do |sum|! sum.abs <= THRESHOLD! end.size! end
10K takes 10s BUT 100M takes 30hs
Time to buy a NEW LAPTOP!
Big O notation How WELL an algorithm SCALES as the
DATA involved INCREASES
Calc Array size (length=N) Count elements one by one: O(N)
Calc Array size (length=N) Count elements one by one: O(N)
Length stored in variable: O(1)
Graphical Math Properties Order Mathematical Properties
Remember: f < g => O(f + g) = O(g)
O(K . f) = O(f) O(1) < O(ln N) < O(N) < O(N2) < O(eN)
Ex: Binary Search Find 7 in [1, 2, 3, 4,
5, 6, 7, 8] 1. element in the middle is 5 2. 5 == 7 ? NO 3. 5 < 7 ? YES => Find 7 in [6, 7, 8] Step 1
! Find 7 in [0, 1, 2, 3, 4, 5,
6, 7, 8] 1. element in the middle is 7 2. 7 == 7 ? YES! FOUND IT!! Step 2
Ex: Binary Search Worst case: ceil ( Log2 N )
23 = 8 ONLY 3 steps
Typical examples Access to a Hash O(1) Binary search O(log
N) Sequential search O(N) Traverse a matrix NxN O(N2)
DON’T JUST BELIEVE ME fooplot.com
BUT raviolicode, I’m getting BORED
I WANT CONCURRENCY I WANT CONCURRENCY
wait… was it Concurrency? or Parallelism?
None
None
None
None
None
None
GIL+CPU-bound NO I/O OPERATIONS concurrency = OVERHEAD
NOT what I was expecting
Parallelism... Parallelism
None
What do we REALLY get? O(N2 / cores) = O(N
2 ) jRubyGo Scala
NO Spoilers O(N2) O(N.log(N)) O(N)
THINKING algorithms is as IMPORTANT as ANY OTHER technique
BYE.
Wait! It's still slow. Wait! It’s still SLOW
Given [1,2,3,4,5] Take 1, then print [5,4,3,2] Take 2, then
print [5,4,3] and so on…
What’s the ORDER of this code? @nums.each_with_index do |a,i|! !
puts @nums.slice(i+1,N).reverse! .inspect! end
What’s the ORDER of this code? @nums.each_with_index do |a,i|! !
puts @nums.slice(i+1,N).reverse! .inspect! end Looks like O(N)
What’s the ORDER of this code? @nums.each_with_index do |a,i|! !
puts @nums.slice(i+1,N).reverse! .inspect! end Behaves like O(N2)
Let’s Look at the DOCS Ruby-Doc.org ! #reverse
O(N) hidden! O(N)!
What’s the ORDER of this code? @nums.each_with_index do |a,i|! !
puts @nums.slice(i+1,N).reverse! .inspect! end O(N2)!
Leaky abstractions LEAKY ABSTRACTIONS
All Non-trivial abstractions are LEAKY to some degree
ABSTRACTIONS DO NOT really SIMPLIFY as they were meant to
Knowing THE ALGORITHMS Behind everyday methods PAYS OFF
Thanks :) Thanks :)