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: Storage For The Rest Of Us
Search
Andrew Godwin
May 26, 2015
Programming
1
470
Small Data: Storage For The Rest Of Us
A talk I gave at PyWaw Summit 2015.
Andrew Godwin
May 26, 2015
Tweet
Share
More Decks by Andrew Godwin
See All by Andrew Godwin
Reconciling Everything
andrewgodwin
1
210
Django Through The Years
andrewgodwin
0
88
Writing Maintainable Software At Scale
andrewgodwin
0
330
A Newcomer's Guide To Airflow's Architecture
andrewgodwin
0
240
Async, Python, and the Future
andrewgodwin
2
540
How To Break Django: With Async
andrewgodwin
1
580
Taking Django's ORM Async
andrewgodwin
0
590
The Long Road To Asynchrony
andrewgodwin
0
510
The Scientist & The Engineer
andrewgodwin
1
580
Other Decks in Programming
See All in Programming
Amazon SQSコンシューマー疎結合への旅 - 出張! #DevelopersIO IT技術ブログの中の人が語る勉強会 #3
quiver
0
310
『Railsオワコン』と言われる時代に、なぜブルーモ証券はRailsを選ぶのか
free_world21
1
360
DMMプラットフォームがTiDB Cloudを採用した背景
pospome
9
4.2k
新宿ダンジョンを可視化してみた
satoshi7190
3
390
MetricKitで予期せぬ終了を検知する話 / Detect unexpected termination with MetricKit
nekowen
1
200
Tailwind CSSを本気でカスタマイズする方法
fsubal
14
5.5k
Goのエラースタックトレースの歴史と今後
sonatard
10
1.8k
PostmanでAPIの動作確認が楽になった話
h455h1
0
180
"config" ってなんだ? / What is "config"?
okashoi
0
320
Ruby Function Composition
bkuhlmann
1
340
dbtのドメイン分割による データ基盤の改善とDigdagとの連携
sakama
0
440
AmperとFleetを使ったAndroidアプリ
yoppie
0
250
Featured
See All Featured
ReactJS: Keep Simple. Everything can be a component!
pedronauck
660
120k
The MySQL Ecosystem @ GitHub 2015
samlambert
244
12k
Making Projects Easy
brettharned
109
5.5k
Sharpening the Axe: The Primacy of Toolmaking
bcantrill
21
1.4k
Exploring the Power of Turbo Streams & Action Cable | RailsConf2023
kevinliebholz
7
3.4k
Writing Fast Ruby
sferik
622
60k
Large-scale JavaScript Application Architecture
addyosmani
504
110k
Making the Leap to Tech Lead
cromwellryan
125
8.5k
Bash Introduction
62gerente
605
210k
Fantastic passwords and where to find them - at NoRuKo
philnash
39
2.5k
The Language of Interfaces
destraynor
151
23k
[Rails World 2023 - Day 1 Closing Keynote] - The Magic of Rails
eileencodes
8
1.3k
Transcript
Andrew Godwin @andrewgodwin SMALL DATA STORAGE FOR THE REST OF
US
Andrew Godwin Hi, I'm Django Core Developer Senior Engineer at
Far too many hobbies
BIG DATA What does it mean?
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
Scaling Breakpoints
Sharding point Datasets paritioned by primary key
Vertical split Entirely unrelated tables
Denormalisation It's not free!
Consistency leeway Can you take inconsistent views?
Load Shapes
Read-heavy Write-heavy Large size
Read-heavy Write-heavy Large size Wikipedia TV show website Minecraft Forums
Amazon Glacier Eventbrite Logging
Read-heavy Write-heavy Large size Offline storage Append formats In-memory cache
/ flat files Many indexes Fewer indexes
Extremes
Extreme Reads Heavy Replication Extreme Writes Sacrifice ordering or consistency
Extreme Size Sacrifice query time
Extreme Longevity Flash in cold storage Extreme Survivability Rad-hardened Flash
Extreme Auditability True append only storage
SSDs Magnetic Tape Hard Drives Consumer Flash CDs/DVDs Long-life Flash
Metal-Carbon DVDs 3-6 months 5-10 years 3-5 years 100+ years Approximate time to bit flip, unpowered at room temperature
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