Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Sign up for free
Menu
Search
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Pricing
Search
Sign in
Sign up for free
Google BigQuery の話 #yapcasia
Search
Sponsored
·
Your Podcast. Everywhere. Effortlessly.
Share. Educate. Inspire. Entertain. You do you. We'll handle the rest.
→
Naoya Ito
August 30, 2014
Technology
11k
21
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
Google BigQuery の話 #yapcasia
Naoya Ito
August 30, 2014
More Decks by Naoya Ito
See All by Naoya Ito
アルゴリズムは何を圧縮しているのか ─ Haskell から育った「圧縮代数」というメンタルモデル
naoya
16
4.4k
Haskell を武器にして挑む競技プログラミング ─ 操作的思考から意味モデル思考へ
naoya
13
4.7k
Haskell でアルゴリズムを抽象化する / 関数型言語で競技プログラミング
naoya
21
8k
Functional TypeScript
naoya
19
6.9k
TypeScript 関数型スタイルでバックエンド開発のリアル
naoya
77
38k
シェルの履歴とイクンリメンタル検索を使う
naoya
16
6.8k
20230227-engineer-type-talk.pdf
naoya
91
87k
関数型プログラミングと型システムのメンタルモデル
naoya
63
110k
TypeScript による GraphQL バックエンド開発
naoya
29
38k
Other Decks in Technology
See All in Technology
アクセスキーこわい やめかたと漏らさない工夫
sassssan68
1
630
2026-09-08 そのJavaモダナイゼーション、AIに丸投げで大丈夫?IBM Bobで変わる品質と効率
yutanonaka
1
150
AIエージェントの一手は 誰も見ていない - Falco拡張OSS「Prempti」とeBPFで サーバーレス実行基盤を二層防御する
keitah
0
490
あけおめLINE 傾向とその対策
nasa9084
0
270
C#コードの結合を可視化する Roslyn解析による設計改善と リファクタリング判断
dora56
0
350
ScotSecure West 2026 - Glasgow
raybugg
0
150
Cloudflare Workers 向けアプリを C# で構築する ~WASM Native AOT への道~
nenonaninu
1
1.1k
アプリをもっと"iOSアプリっぽく"する小さな工夫 / Small Touches That Make Your App Feel More Like an iOS App
matsuji
2
1k
beyond jj: config & tools ecosystem
indirect
0
5.8k
AI 時代のスタートアップエコシステ厶から考究する技術的負債との向き合い方
m3m0r7
PRO
3
2.6k
Oracle Base Database Service 技術詳細
oracle4engineer
PRO
16
120k
俺の仕事は AIに奪われないし、たぶんその BIも要らない
hikaruri
0
540
Featured
See All Featured
実際に使うSQLの書き方 徹底解説 / pgcon21j-tutorial
soudai
PRO
203
76k
Fireside Chat
paigeccino
43
4k
Keith and Marios Guide to Fast Websites
keithpitt
413
23k
Kristin Tynski - Automating Marketing Tasks With AI
techseoconnect
PRO
0
520
Unsuck your backbone
ammeep
672
58k
Exploring the Power of Turbo Streams & Action Cable | RailsConf2023
kevinliebholz
37
6.6k
A Tale of Four Properties
chriscoyier
163
24k
The Cost Of JavaScript in 2023
addyosmani
55
10k
Groundhog Day: Seeking Process in Gaming for Health
codingconduct
0
360
Game over? The fight for quality and originality in the time of robots
wayneb77
1
290
Fantastic passwords and where to find them - at NoRuKo
philnash
52
3.8k
Become a Pro
speakerdeck
PRO
31
6.3k
Transcript
(PPHMF#JH2VFSZͷ /BPZB*UP ,"*;&/QMBUGPSN*OD :"1$"TJB5PLZP ˞(PPHMFࣾͷճ͠ ऀͰ͋Γ·ͤΜ
ΞδΣϯμ • #JH2VFSZ֓؍ • #JH2VFSZͷ෦ • ,"*;&/QMBUGPSN*ODͰͷ͍Ͳ͜Ζ
#JH2VFSZ֓؍
(PPHMF#JH2VFSZ
None
#JH2VFSZͱ • ڊେͳσʔλͷ42- ͳͲ ΛඵͰ࣮ߦ͢ΔΫϥυαʔϏε – ԯϨίʔυΛඵ ˞ –
8FCΠϯλʔϑΣʔε͓Αͼ3&45"1* • (PPHMFࣾͰΘΕ͖ͯͨ%SFNFMΛαʔϏεԽ – ݄$MPTFEϦϦʔε – ݄Ұൠެ։ – ܧଓతʹόʔδϣϯΞοϓ – ݄#JH2VFSZ4USFBNJOH ˞(PPHMFͷދͷࢠʮ#JH2VFSZʯΛ'MVFOUEϢʔβʔ͕Θͳ͍ཧ༝͕ͳ͘ͳͬͨཧ༝ IUUQRJJUBDPNLB[VOPSJJUFNTBDBDCCBBBG
ͲΜͳ͜ͱʹΘΕΔ͔ • Ϣʔεέʔε – ϩάղੳ – %BUBXBSF)PVTF – • ͍ͯͳ͍༻్ – ۀ%# ͍3%#.4Ͱ
ͳ͍Αɺͱ͍͏͜ͱ
#JH2VFSZͳ͍͔ͥ • جຊɺϑϧεΩϟϯͰ͕ΜΔ – 3%#.4ͷ#5SFFΠϯσοΫεͱ͔ͳ͍ • 42-Λࢄॲཧ – .11 .BTTJWFMZ1BSBMMFM1SPDFTTJOH
2VFSZ&OHJOF %SFNFM • ઍͷσΟεΫͱߴωοτϫʔΫͰεέʔϧΞτ – 5#ͷσʔλΛඵͰϦʔυ͢Δ*0
ͨͩ͠ • ͍3%#.4Ͱͳ͍ • େਓͰҰʹ͏ͷͰͳ͍ – ओʹόονॲཧʹ͏ • εΩʔϚϨεͰͳ͍ 5#نσʔλͰઢܗҎ ԼͰεέʔϧ͢Δ͕ɺٯ
ʹখ͞ͳσʔλͰඵ ͷΦʔόʔϔου͕͋Δ ͷͰ
BigQuery読書会、@harukasan 資料より引用
ଞͷྨࣅ࣮ͱͷϙδγϣχϯά • -BSHF#BUDI – ҆ఆͯ͠ڊେͳόονΛ࣮ߦͰ͖Δ – ΫΤϦ࣮ߦ࣌ͷΦʔόʔϔου͕େ͖͍ ेඵʙे –
.BQ3FEVDFɺ)BEPPQ )JWF • 4IPSU#BUDI – ΫΤϦ࣮ߦ࣌ͷΦʔόʔϔου͕ඵ – ΞυϗοΫΫΤϦʹ͍͍ͯΔ – .112VFSZ&OHJOF1SFTUPɺ*NQBMBɺ#JH2VFSZ %SFNFM • 4USFBN1SPDFTTJOH – όον࣮ߦͰ͖ͳ͍͕ετϦʔϜʹରͯ͠ϦΞϧλΠϜॲཧͰ͖Δ – /PSJLSBɺ"QBDIF,BGLBɺ5XJUUFS4UPSNFUD "NB[PO3FETIJGU 4IPSU#BUDI ৄ͘͠ ͳ͍ͷͰলུ cf. Batch processing and Stream processing by SQL h;p://www.slideshare.net/tagomoris/hcj2014-‐sql
Ձ֨ • ྉۚ – σʔλอ(#݄ – ΫΤϦ5# εΩϟϯͨ͠σʔλͷαΠ ζ "NB[PO4ΑΓ࣮
͍҆ ($1ؔͷษڧձ͍͘ͱ ͷແྉνέοτΒ ͑ͨΓ͠·͢
#JH2VFSZͷ෦ ͚ͩ͢͜͠
(PPHMF#JH%BUB4UBDL • ʰ(PPHMFΛࢧ͑Δٕज़ʱ – #JH%BUB4UBDL – ('4ɺ#JH5BCMFɺ.BQ3FEVDFFUD • #JH%BUB4UBDL –
#JH%BUB4UBDLͷ্ʹߏங͞Εͨɺͷ՝Λղফ͢Δ࣮܈ – $PMPTTVT .FHBTUPSF 4QBOOFS 'MVNF+BWB %SFNFM طʹ(PPHMFࣾ #JH%BUB4UBDLͩ ͱ͔͍͏ͪΒ΄Β
#JH2VFSZͷٕज़ελοΫ (PPHMF'JMF4ZTUFN ('4 $PMPTTVT'JMF4ZTUFN $'4 $PMVNO*0 %SFNFM ࢄ'4
('4ͷվྑܕ'4 ৄࡉඇެ։ #JH2VFSZͷͨΊͷྻࢦϑΝΠϧ ϑΥʔϚοτ ฒྻ42-࣮ߦΤϯδϯ σʔληϯλʔΛ·͍ͨͰ ࢄ͞ΕͯΔσʔλΛฒྻ ͔ͭߴʹऔಘͰ͖ΔΒ͠ ͍
$PMVNO*0 Dremel: InteracIve Analysis of Web-‐Scale Datasets h;p://research.google.com/pubs/archive/36632.pdf ߦͰͳ͘ྻ୯ҐͰɻಛ
ఆྻΛγʔέϯγϟϧʹ ಡΊΔͭ$PMPTTVT ͰฒྻಡΈࠐΈ
%SFNFM Dremel: InteracIve Analysis of Web-‐Scale Datasets h;p://research.google.com/pubs/archive/36632.pdf
Root Mixer Mixer 1 Shard 0-‐8 Mixer 1
Shard 9-‐16 Mixer 1 Shard 17-‐24 Shard 0 Shard 10 Shard 12 Shard 20 Shard 24 Distributed Storage (e.g., CFS) Dremel serving tree Google BigQuery AnalyIcs P.284 Chapter 9 Understanding Query ExecuIon ࢄ
Root Mixer Mixer 1 Shard 0-‐8 Mixer 1
Shard 9-‐16 Mixer 1 Shard 17-‐24 Shard 0 Shard 10 Shard 12 Shard 20 Shard 24 Distributed Storage (e.g., CFS) Dremel serving tree Google BigQuery AnalyIcs P.284 Chapter 9 Understanding Query ExecuIon $'4 $PMVNO*0Ͱಛ ఆྻͷσʔλ͕Ұ෦ฦͬ ͯ͘Δ ࢄ ू
Root Mixer Mixer 1 Shard 0-‐8 Mixer 1
Shard 9-‐16 Mixer 1 Shard 17-‐24 Shard 0 Shard 10 Shard 12 Shard 20 Shard 24 Distributed Storage (e.g., CFS) Dremel serving tree Google BigQuery AnalyIcs P.284 Chapter 9 Understanding Query ExecuIon $'4 $PMVNO*0Ͱಛ ఆྻͷσʔλ͕Ұ෦ฦͬ ͯ͘Δ ྻΛॱ൪ʹಡΈߦ Λऔಘɻ8)&3&۟ͳ ͲΛݟͯඞཁͳߦͷΈ ʹߜΓϝϞϦͰอ࣋ ࢄ ू
Root Mixer Mixer 1 Shard 0-‐8 Mixer 1
Shard 9-‐16 Mixer 1 Shard 17-‐24 Shard 0 Shard 10 Shard 12 Shard 20 Shard 24 Distributed Storage (e.g., CFS) Dremel serving tree Google BigQuery AnalyIcs P.284 Chapter 9 Understanding Query ExecuIon $'4 $PMVNO*0Ͱಛ ఆྻͷσʔλ͕Ұ෦ฦͬ ͯ͘Δ ྻΛॱ൪ʹಡΈߦ Λऔಘɻ8)&3&۟ͳ ͲΛݟͯඞཁͳߦͷΈ ʹߜΓϝϞϦͰอ࣋ ֤TIBSE͔ΒσʔλΛू ɻྫ͑ιʔτ-*.*5 ͷߜΓࠐΈͳͲ͢Δ ࢄ ू
Root Mixer Mixer 1 Shard 0-‐8 Mixer 1
Shard 9-‐16 Mixer 1 Shard 17-‐24 Shard 0 Shard 10 Shard 12 Shard 20 Shard 24 Distributed Storage (e.g., CFS) Dremel serving tree Google BigQuery AnalyIcs P.284 Chapter 9 Understanding Query ExecuIon $'4 $PMVNO*0Ͱಛ ఆྻͷσʔλ͕Ұ෦ฦͬ ͯ͘Δ ྻΛॱ൪ʹಡΈߦ Λऔಘɻ8)&3&۟ͳ ͲΛݟͯඞཁͳߦͷΈ ʹߜΓϝϞϦͰอ࣋ ֤TIBSE͔ΒσʔλΛू ɻྫ͑ιʔτ-*.*5 ͷߜΓࠐΈͳͲ͢Δ ूͨ݁͠Ռ ΛDBMMFSʹฦ͢ ࢄ ू
#JH2VFSZͷ͍͢͝ॴ • ΧϥϜܕ*0ɺ42-ͷׂ౷࣏ – Ͱ͜Εɺ.11తʹ͘͠ͳ͍ • ͡Ό͋ɺ#JH2VFSZͷԿ͕͍͔͢͝ – (PPHMFͷͰ͔͍Πϯϑϥ
ׂͱ֖ͳ͍ŋŋŋ
͜ΜͳΫιΫΤϦͰඵɺ̐ඵͩ
,"*;&/QMBUGPSN*OD Ͱͷ͍Ͳ͜Ζ
Ϣʔεέʔε • ΞΫηεϩάͷอଘௐࠪ • ΞϓϦέʔγϣϯϩάͷղੳ %BUBXBSF )PVTF • "#ςετͷ༗ҙࠩఆ
ΞΫηεϩά
ΞΫηεϩά #JH2VFSZ • /HJOYͷϩάΛqVFOUQMVHJOCJHRVFSZͰ ૹΓଓ͚Δ – &&Ͱ҉߸Խ͞ΕͯΔΑ • Կ͔༻͕͋ͬͨΒ42-Ͱղੳ –
%BJMZ8FFLMZ.POUIMZ17 – ϓϩμΫγϣϯͷσόοά
qVFOUQMVHJOCJHRVFSZ • CZUBHPNPSJT͞ΜɺZVHVJ͞Μଞ • ઌ͔Β,"*;&/QMBUGPSN*OD͕ϝ ϯςφʹ – ࣮࣭ɺԶ QBUDIFTXFMDPNF Ͱ͢
ΞϓϦέʔγϣϯͷϩάղੳ
ϩάΛඈ͢ • 3BJMT͔ΒUEMPHHFSSVCZͰqVFOUE • qVFOUEQMVHJOCJHRVFSZͰ#2ʹඈ͢
ϩάΛඈ͢ܖػ • ϦΫΤετຖ – "QQMJDBUJPO$POUSPMMFS – ϩάΠϯϢʔβͷଐੑΛඈ͢ˠ%"6."6ͷ ࢉग़ʹ • Ϟσϧͷঢ়ଶมߋ࣌
– "DUJWF3FDPSE0CTFSWFS – ϞσϧຖʹదͳଐੑΛݟસͬͯඈ͢ – #JH2VFSZෳࡶͳ42-Ͱී௨ʹԠ͢Δ㱺ϓ ϩμΫτϚωʔδϟ͕ؾܰʹ42-ॻ͍ͯΔ
ਖ਼نԽ͋·Γ͠ͳ͍ • ελʔεΩʔϚ – %8)ͷఆ൪ͷϞσϦϯά • ϑΝΫτςʔϒϧŋŋŋϩά • ࣍ݩςʔϒϧŋŋŋϚελʔσʔλ ސ٬໊ͱ͔
– ਖ਼نԽ͠ͳ͍ͷ͕ηΦϦʔ
"#ςετ༗ҙࠩఆ • "#ςετͷαʔϏεͳͷͰ͆ • ৄࡉൿີ • SFRTFDͱ͔qVUFOEͰૹͬͯΔ ͚ͲͬͪΌΒ͞ – ˞SFRTFDͷ)551SFRVFTUqVFOUE͕όοϑΝϦϯά͢ΔͷͰ
#JH2VFSZͷ"1*ίʔϧͣͬͱগͳ͍
֎෦πʔϧͱͷଓ • ΤΫηϧ – #JH2VFSZ$POOFDUPSGPS&YDFMCZ(PPHMF – ϐϘοτੳʹ • %0.0 #*
– FYQFSJNFOUBMͳ#JH2VFSZΠϯλϑΣʔε ͋ͬͨ – 5BCMFBVϝδϟʔͲ͜ΖରԠ࢝͠ΊͯΔ
໘ͳͱ͜Ζ • qVFOUEQMVHJOCJHRVFSZ͕εΩʔϚϑΝΠϧΛཁٻ ͢Δ – ͕͔ͩ͠͠IBLPCFSB͞Μ͕QBUDIΛॻ͍ͯ͘Εͨ – W͔ΒGFUDI@TDIFNBػೳ͕͑ΔΑ • ࣍ݩςʔϒϧͷߋ৽
– 61%"5&Ͱ͖ͳ͍ͷͰ – ؒͱ͔ʹҰճফͯ͠࡞ΔɺΈ͍ͨͳ – 1SFTUPΈ͍ͨʹҧ͏σʔλιʔεΛ+0*/Ͱ͖ͨΓ͢Δͱخ ͍͠ͷ͕ͩŋŋŋ
࢛ํࢁ • (PPHMF"OBMZUJDT #JH2VFSZศརͦ͏ – ("ͷੜϩάΛ#JH2VFSZͰղੳͰ͖ΔΦϓγϣϯ – ͨͩ͠("ͷ༗ྉαʔϏε • Ͱ͔͍σʔλͷΠϯϙʔτ
– (PPHMF%BUB4UPSFʹஔ͍͔ͯΒΠϯϙʔτ͢Δͱߴ • 5BCMF%FDPSBUPST – σʔλͷ࣌ؒൣғΛࢦఆͯ͠ΫΤϦɻεΩϟϯରͷσʔλ͕খ͘͞ͳ ΔͷͰΫΤϦඅ༻ΛઅͰ͖Δ • +0*/੍ݶ.#ੲͷ – +0*/&"$)Λ͏ͱ.BQ3FEVDFͷTIV⒐FΈ͍ͨͳॲཧͰڊ େͳ+0*/ ԯYԯͱ͔ŋŋŋ ͯ͘͠ΕΔΑ
·ͱΊ • #JH2VFSZϑϧεΩϟϯͰͰ͔͍σʔλͷ 42-͕ඵͳαʔϏε • ΫιΫΤϦྗۀͰॲཧͪ͠Ό͏ΧοίΠΠ • ׂ౷࣏ (PPHMFͷ%$نͰ֖ͳ͍ ฒྻॲཧܥ
• όονɺϩάղੳͳΜ͔ʹ͑·͢ • ࢲ(PPHMFࣾͷճ͠ऀͰ͍͟͝·ͤΜ
5IBOLT ֆCZ͋ΘΏ͖