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
Fast In-memory Analytics for Retail Data with C...
Search
ernestoarbitrio
April 09, 2017
Technology
78
0
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
Fast In-memory Analytics for Retail Data with Columnar Databases
ernestoarbitrio
April 09, 2017
More Decks by ernestoarbitrio
See All by ernestoarbitrio
Enable effective Observability with Python
pamaron
0
150
PyConZA 2022 Best practices for good(ish) and clean(ish) code
pamaron
0
130
PyCon Italia 2022 Best practices for good(ish) and clean(ish) code
pamaron
0
290
Bokeh: Using python for interactive data visualization
pamaron
1
180
Keystroke Behavioural Analysis For Fraud Detection: Deep Learning as-a-service Infrastructure
pamaron
0
68
Indexing and search tons of data with ElasticSearch and Django
pamaron
0
420
Interactive plot with django and highchart JS (without JS)
pamaron
0
400
Other Decks in Technology
See All in Technology
1000⼈規模のClaude Enterprise運⽤を「Oktaのグループ」と「Slack」に集約する
sansantech
PRO
1
520
Digital Credentials API × OpenID4VP ブラウザ完結型本人確認の実装知見(OAuth/OIDC Numa (Immersion) Workshop 2026)
oidfj
PRO
0
360
AI時代のデータ基盤を考える問い
pacocat
0
750
会計事務所と顧問先の契約関係をOIDC・OAuthで表現する
terara
0
520
「ミスを許さない手順書」を作ってみた 〜 個人的にはこれ以上できることはあまりなさそう/20260827-ssmjp-operation-procedure-update
opelab
15
16k
Cloudflare製品を活用した AIガバナンス実践入門 / AI governance with Cloudflare Service
delta_tech
1
130
Kiro Crew で始める マルチエージェント開発
miu_crescent
PRO
0
210
Introduction to Sansan for Engineers / エンジニア向け会社紹介
sansan33
PRO
6
77k
分割40%キーボードにスムーズに入門するには
hoto17296
1
200
1.5時間を無駄にして学んだwsl2におけるaptとsnapの選択と仕組み
yosaka0123
0
470
EUDIWの枠組みを出発点に民間エコシステムの在り方を考える(OAuth/OIDC Numa (Immersion) Workshop 2026)
oidfj
PRO
0
370
わたしが知り合いゼロの勉強会に 行けるようになるまで
r5ni4
2
840
Featured
See All Featured
エンジニアに許された特別な時間の終わり
watany
108
250k
How to audit for AI Accessibility on your Front & Back End
davetheseo
0
520
Technical Leadership for Architectural Decision Making
baasie
3
540
The B2B funnel & how to create a winning content strategy
katarinadahlin
PRO
1
490
Ten Tips & Tricks for a 🌱 transition
stuffmc
0
180
How to Ace a Technical Interview
jacobian
281
24k
Joys of Absence: A Defence of Solitary Play
codingconduct
1
450
Put a Button on it: Removing Barriers to Going Fast.
kastner
60
4.5k
Beyond borders and beyond the search box: How to win the global "messy middle" with AI-driven SEO
davidcarrasco
3
220
Testing 201, or: Great Expectations
jmmastey
46
8.3k
Avoiding the “Bad Training, Faster” Trap in the Age of AI
tmiket
0
220
Claude Code どこまでも/ Claude Code Everywhere
nwiizo
67
57k
Transcript
Fast In-memory Analytics for Retail Data with Columnar Databases Ernesto
Arbitrio - Valerio Maggio arbitrio |
[email protected]
Florence April 6, 2017
Retail Data • Overview of data we have • granularity
• refresh/update rate • Quantity and storage required (space) • services developed around these data
“Materialized Views” • Description of what they are (non-technical) •
Some examples of Analytics we do on this data
The Problem! ~1 TByte Data We need OLAP Performance: 75M
rows -> 5hours
The Solution! Use a Column-oriented Database (i.e. Just swap Rows
with Columns) Chuck Norris Test Passed!
None
Query
None
Thank you get in touch @__pamaron__ @leriomaggio