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
Small Data: Databases in the Real World
Search
Andrew Godwin
August 04, 2014
Programming
2
610
Small Data: Databases in the Real World
A talk I gave at PyCon AU 2014.
Andrew Godwin
August 04, 2014
Tweet
Share
More Decks by Andrew Godwin
See All by Andrew Godwin
Reconciling Everything
andrewgodwin
1
340
Django Through The Years
andrewgodwin
0
230
Writing Maintainable Software At Scale
andrewgodwin
0
460
A Newcomer's Guide To Airflow's Architecture
andrewgodwin
0
370
Async, Python, and the Future
andrewgodwin
2
690
How To Break Django: With Async
andrewgodwin
1
750
Taking Django's ORM Async
andrewgodwin
0
750
The Long Road To Asynchrony
andrewgodwin
0
680
The Scientist & The Engineer
andrewgodwin
1
790
Other Decks in Programming
See All in Programming
CSC509 Lecture 10
javiergs
PRO
0
170
Kotlinで実装するCPU/GPU 「協調的」パフォーマンス管理
matuyuhi
0
350
Functional Calisthenics in Kotlin: Kotlinで「関数型エクササイズ」を実践しよう
lagenorhynque
0
110
開発生産性が組織文化になるまでの軌跡
tonegawa07
0
140
Claude Code on the Web を超える!? Codex Cloud の実践テク5選
sunagaku
0
450
複数チーム並行開発下でのコード移行アプローチ ~手動 Codemod から「生成AI 活用」への進化
andpad
0
100
AsyncSequenceとAsyncStreamのプロポーザルを全部読む!!
s_shimotori
1
270
歴史から学ぶ「Why PHP?」 PHPを書く理由を改めて理解する / Learning from History: “Why PHP?” Rediscovering the Reasons for Writing PHP
seike460
PRO
0
140
HTTPじゃ遅すぎる! SwitchBotを自作ハブで動かして学ぶBLE通信
occhi
0
230
MCPサーバー「モディフィウス」で変更容易性の向上をスケールする / modifius
minodriven
7
1.4k
CSC509 Lecture 09
javiergs
PRO
0
290
Vueのバリデーション、結局どれを選べばいい? ― 自作バリデーションの限界と、脱却までの道のり ― / Which Vue Validation Library Should We Really Use? The Limits of Self-Made Validation and How I Finally Moved On
neginasu
3
1.8k
Featured
See All Featured
VelocityConf: Rendering Performance Case Studies
addyosmani
333
24k
Dealing with People You Can't Stand - Big Design 2015
cassininazir
367
27k
Building an army of robots
kneath
306
46k
Bash Introduction
62gerente
615
210k
Fantastic passwords and where to find them - at NoRuKo
philnash
52
3.5k
Speed Design
sergeychernyshev
32
1.2k
Reflections from 52 weeks, 52 projects
jeffersonlam
355
21k
Distributed Sagas: A Protocol for Coordinating Microservices
caitiem20
333
22k
Keith and Marios Guide to Fast Websites
keithpitt
413
23k
The Invisible Side of Design
smashingmag
302
51k
CoffeeScript is Beautiful & I Never Want to Write Plain JavaScript Again
sstephenson
162
15k
Gamification - CAS2011
davidbonilla
81
5.5k
Transcript
Andrew Godwin @andrewgodwin SMALL DATA REAL WORLD DATABASES IN THE
Andrew Godwin Core Developer Senior Engineer
BIG DATA What does it mean? What is 'big'?
1,000 rows? 1,000,000 rows? 1,000,000,000 rows? 1,000,000,000,000 rows?
Scalable designs are a tradeoff: NOW LATER vs
Small company? Agency? Focus on ease of change, not scalability
You don't need to scale from day one But always
leave yourself scaling points
Rapid development Continuous deployment Hardware choice Scaling 'breakpoints'
Rapid development It's all about schema change overhead
Explicit Schema ID int Name text Weight uint 1 2
3 Alice Bob Charles 76 84 65 Implicit Schema { "id": 342, "name": "David", "weight": 44, }
Silent Failure { "id": 342, "name": "David", "weight": 74, }
{ "id": 342, "name": "Ellie", "weight": "85kg", } { "id": 342, "nom": "Frankie", "weight": 77, } { "id": 342, "name": "Frankie", "weight": -67, }
Continuous deployment It's 11pm. Do you know where your locks
are?
Add NULL and backfill 1-to-1 relation and backfill DBMS-supported type
changes
Hardware choice ZOMG RUN IT ON THE CLOUD
VMs are TERRIBLE at IO Up to 10x slowdown, even
with VT-d.
Memory is king Your database loves it. Don't let other
apps steal it.
Adding more power goes far Especially with PostgreSQL or read-only
replicas
None
Sharding point Vertical split Consistency leeway
Sharding point Datasets paritioned by primary key
Migration plan Implement consistent hashing on primary key Make large
number of logical shards (2048?) Map logical shards to single physical shard Migrate shards using replication
Vertical split Entirely unrelated tables
Migration plan Replicate database to new server Route split tables
there, disable replication - or - Slowly backfill new datastore with fallback lookup
Denormalisation It's not free!
Migration plan Add NULL fields to dependent tables App code
to fetch and fill if not present Possibly prefill on save of new items
Consistency leeway Can you take inconsistent views?
Migration plan Change your site! Talk to your designers! Deliberately
introduce inconsistency!
Big Data isn't one thing It depends on type, size,
complexity, throughput, latency...
Focus on the current problems Future problems don't matter if
you never get there
Efficiency and iterating fast matters The smaller you are, the
more time is worth
Good architecture affects product You're not writing a system in
a vacuum
Thanks! Andrew Godwin @andrewgodwin
[email protected]
are hiring!