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
由Spanner來看Google資料庫的前世今生
Search
Szu-Kai Hsu (brucehsu)
November 07, 2012
Technology
4
280
由Spanner來看Google資料庫的前世今生
2012年秋,網際網路資料庫 @ 國立中正大學資工所
Szu-Kai Hsu (brucehsu)
November 07, 2012
Tweet
Share
More Decks by Szu-Kai Hsu (brucehsu)
See All by Szu-Kai Hsu (brucehsu)
Running Life Lean
brucehsu
0
170
Core Unleashed Part II: Introduction to GobiesVM (and STM) @ RubyKaigi 2014
brucehsu
0
2.1k
[RubyConf.tw 2014] Cores unleashed - Exploiting Parallelism in Ruby with STM
brucehsu
0
2.2k
用 Go 打造程式語言執行環境:實例剖析 [OSDC.tw 2014]
brucehsu
3
2.3k
pickbox @ OSDC.tw 2013 Lightning Talk
brucehsu
0
57
Building Web 2.0 APIs
brucehsu
1
150
Rapid Web Development by Example
brucehsu
3
3.1k
TechWed@CCU #0
brucehsu
2
510
Chromium OS
brucehsu
2
200
Other Decks in Technology
See All in Technology
Connect 100+を支える技術
kanyamaguc
0
180
Yamla: Rustでつくるリアルタイム性を追求した機械学習基盤 / Yamla: A Rust-Based Machine Learning Platform Pursuing Real-Time Capabilities
lycorptech_jp
PRO
4
220
Geminiとv0による高速プロトタイピング
shinya337
0
230
赤煉瓦倉庫勉強会「Databricksを選んだ理由と、絶賛真っ只中のデータ基盤移行体験記」
ivry_presentationmaterials
2
290
Southwest airlines®️ USA Contact Numbers: Complete 2025 Support Guide
oliversmith12
0
110
KubeCon + CloudNativeCon Japan 2025 に行ってきた! & containerd の新機能紹介
honahuku
0
120
KubeCon + CloudNativeCon Japan 2025 Recap by CA
ponkio_o
PRO
0
290
Understanding_Thread_Tuning_for_Inference_Servers_of_Deep_Models.pdf
lycorptech_jp
PRO
0
160
AIとともに進化するエンジニアリング / Engineering-Evolving-with-AI_final.pdf
lycorptech_jp
PRO
0
150
20250707-AI活用の個人差を埋めるチームづくり
shnjtk
3
3k
MUITにおける開発プロセスモダナイズの取り組みと開発生産性可視化の取り組みについて / Modernize the Development Process and Visualize Development Productivity at MUIT
muit
1
13k
モバイル界のMCPを考える
naoto33
0
410
Featured
See All Featured
What’s in a name? Adding method to the madness
productmarketing
PRO
23
3.5k
A designer walks into a library…
pauljervisheath
207
24k
Automating Front-end Workflow
addyosmani
1370
200k
It's Worth the Effort
3n
185
28k
Code Review Best Practice
trishagee
69
18k
Music & Morning Musume
bryan
46
6.6k
Practical Tips for Bootstrapping Information Extraction Pipelines
honnibal
PRO
20
1.3k
Rails Girls Zürich Keynote
gr2m
94
14k
Templates, Plugins, & Blocks: Oh My! Creating the theme that thinks of everything
marktimemedia
31
2.4k
[Rails World 2023 - Day 1 Closing Keynote] - The Magic of Rails
eileencodes
35
2.4k
Raft: Consensus for Rubyists
vanstee
140
7k
Docker and Python
trallard
44
3.5k
Transcript
由 Spanner來看 Google資料庫 的 前世今⽣生 Szu-Kai Hsu (brucehsu)
Spanner is a scalable multi-version globally-distributed synchronously-replicated database
BigTable
Handling
Handling really
Handling really BIG DATA
key-value
key-value { “CCU”: “123”, “NCTU”: “113”, “NTU”: “112” }; key
key-value { “CCU”: “123”, “NCTU”: “113”, “NTU”: “112” }; value
distributed
Lack of transaction, think of our first project.
CAP
C A P
Consistency A P
Consistency Availability P
Consistency Availability Partition tolerance
Consistency Availability Partition tolerance Consistency
Megastore
NoSQL datastores are highly scalable, but their limited API and
loose consistency models complicate application development. “ “
In Megastore, data model is declared in a strong-typed schema
strong-typed schema CREATE TABLE User { required int64 user_id; required string name; } PRIMARY KEY(user_id), ENTITY GROUP ROOT;
Based on BigTable BigTable
PRIMARY user_id PRIMARY user_id, nyan_id
Local and Global Indexes are introduced: Local Index Find corresponding
data in entity group Global Index Find corresponding data in external groups Local Index Global Index
(user_id, born,nyan_id) For local index CREATE LOCAL INDEX NyanByBorn ON
Nyan(user_id, born); CREATE LOCAL INDEX NyanByBorn ON Nyan(user_id, born);
Consistency achieved via Paxos algorithm Paxos 2 Replicas 1 Witness
At least
Replica consists of Replication server and Coordinator Replication server Coordinator
write oversee
Witness’ Replication server only writes logs logs
Average Latency: 100-400ms Poor write throughput 100-400ms
Spanner ,finally.
We believe it is better to have application programmers deal
with performance problems due to overuse of transactions as bottlenecks arise, rather than always coding around the lack of transactions. “ “
Data model is almost identical to Megastore almost identical Basic
unit defined as Directory Directory
Data model is almost identical to Megastore almost identical Basic
unit defined as Directory Directory Same prefix key, therefore adjacent
Data model is almost identical to Megastore almost identical Basic
unit defined as Directory Directory Same prefix key, therefore adjacent Fine-grained mapping
Data model is almost identical to Megastore almost identical Basic
unit defined as Directory Directory Same prefix key, therefore adjacent Fine-grained mapping Interleaved rows gain performance
Two-phase commit for distributed transactions Two-phase commit 1Vote Coordinator Participants
Two-phase commit for distributed transactions Two-phase commit 2Commit Coordinator Participants
Locking remains a big issue Locking Especially when someone went
down, causing deadlock, literally.
Paxos is here to rescue, again Paxos will make sure
ALL logs are copied to every replicas. ALL logs
Real Innovation lies in time TrueTime API utilizes atomic clock
& GPS to determine the order of each transactions atomic clock GPS
NewSQL is the new NoSQL and Spanner is the best
example so far.