Upgrade to PRO for Only $50/Year—Limited-Time Offer! 🔥
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Google BigQuery の話 #gcpja
Search
Naoya Ito
September 17, 2014
Technology
17
5.8k
Google BigQuery の話 #gcpja
gcp ja night で話した BigQuery のスライド。YAPC::Asia のものに数枚だけスライドを追加したもので、ほぼ同じです。
Naoya Ito
September 17, 2014
Tweet
Share
More Decks by Naoya Ito
See All by Naoya Ito
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
7k
Functional TypeScript
naoya
17
6.5k
TypeScript 関数型スタイルでバックエンド開発のリアル
naoya
75
36k
シェルの履歴とイクンリメンタル検索を使う
naoya
16
6.4k
20230227-engineer-type-talk.pdf
naoya
91
79k
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
36k
フロントエンドのパラダイムを参考にバックエンド開発を再考する / TypeScript による GraphQL バックエンド開発
naoya
67
24k
「問題から目を背けず取り組む」 一休の開発チームが6年間で学んだこと
naoya
144
60k
Other Decks in Technology
See All in Technology
なぜ使われないのか?──定量×定性で見極める本当のボトルネック
kakehashi
PRO
1
760
Introduction to Sansan, inc / Sansan Global Development Center, Inc.
sansan33
PRO
0
2.9k
Docker, Infraestructuras seguras y Hardening
josejuansanchez
0
150
ページの可視領域を算出する方法について整理する
yamatai1212
0
160
.NET 10 のパフォーマンス改善
nenonaninu
2
4.7k
形式手法特論:CEGAR を用いたモデル検査の状態空間削減 #kernelvm / Kernel VM Study Hokuriku Part 8
ytaka23
1
140
Design System Documentation Tooling 2025
takanorip
1
930
freeeにおけるファンクションを超えた一気通貫でのAI活用
jaxx2104
3
600
MAP-7thplaceSolution
yukichi0403
2
250
AIにおける自由の追求
shujisado
3
470
履歴テーブル、今回はこう作りました 〜 Delegated Types編 〜 / How We Built Our History Table This Time — With Delegated Types
moznion
15
9.4k
Product Engineer
resilire
0
130
Featured
See All Featured
Product Roadmaps are Hard
iamctodd
PRO
55
12k
個人開発の失敗を避けるイケてる考え方 / tips for indie hackers
panda_program
120
20k
Fight the Zombie Pattern Library - RWD Summit 2016
marcelosomers
234
17k
Site-Speed That Sticks
csswizardry
13
990
Building Better People: How to give real-time feedback that sticks.
wjessup
370
20k
Scaling GitHub
holman
464
140k
Building a Scalable Design System with Sketch
lauravandoore
463
34k
A designer walks into a library…
pauljervisheath
210
24k
Save Time (by Creating Custom Rails Generators)
garrettdimon
PRO
32
1.8k
BBQ
matthewcrist
89
9.9k
RailsConf 2023
tenderlove
30
1.3k
The Language of Interfaces
destraynor
162
25k
Transcript
(PPHMF#JH2VFSZͷ /BPZB*UP ,"*;&/QMBUGPSN*OD HDQKBOJHIU
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 – ΫΤϦ࣮ߦ࣌ͷΦʔόʔϔου͕NTʙඵ – 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
͍҆ νέοτΒ͍·ͨ͠
#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$POOFDUPSGPS&YDFMCZ(PPHMF – ϐϘοτੳʹ • %0.0 #*
– FYQFSJNFOUBMͳ#JH2VFSZΠϯλϑΣʔε ͋ͬͨ – 5BCMFBVϝδϟʔͲ͜ΖରԠ࢝͠ΊͯΔ
໘ͳͱ͜Ζ • qVFOUEQMVHJOCJHRVFSZ͕εΩʔϚϑΝΠϧΛཁٻ ͢Δ – ͕͔ͩ͠͠IBLPCFSB͞Μ͕QBUDIΛॻ͍ͯ͘Εͨ – W͔ΒGFUDI@TDIFNBػೳ͕͑ΔΑ • ࣍ݩςʔϒϧͷߋ৽
– 61%"5&Ͱ͖ͳ͍ͷͰ – ؒͱ͔ʹҰճফͯ͠࡞ΔɺΈ͍ͨͳ – 1SFTUPΈ͍ͨʹҧ͏σʔλιʔεΛ+0*/Ͱ͖ͨΓ͢Δͱخ ͍͠ͷ͕ͩŋŋŋ
࢛ํࢁͦͷ • 42-ͱ͍ͬͯඪ४42-͡Όͳ͍Α – 3&(&91@."5$) ͱ͔3&(&91@&953"$5 ͱ͔+40/ ͱ ͔501 ͱ͔
• ʮͲ͏ͤϑϧεΩϟϯͯ͠Δ͠ʯͱ͍͏લఏʹཱͭͱΑ ͍ – -&'5 '03."5@65$@64&$ UJNF BTEBZ (3061#:EBZͱ͔ – 3&(&91@&953"$5 UJUMF S aX BTGSBHNFOU(3061#: GSBHNFOU03%&3#:GSBHNFOU@DPVOUEFTDͱ͔ – αϒΫΤϦ7JFX
࢛ํࢁͦͷ • 61%"5&%&-&5&ͳ͍ – ཁΒͳ͍ΧϥϜʹOVMM • ΧϥϜܕ͔ͩΒOVMMͳΒ༰ྔ৯Θͳ͍ – εΩʔϚՃ؆୯ • ߋ৽جຊআͯ͠࡞Γ͠
࢛ํࢁͦͷ • (PPHMF"OBMZUJDT #JH2VFSZศརͦ͏ – ("ͷੜϩάΛ#JH2VFSZͰղੳͰ͖ΔΦϓγϣϯ – ͨͩ͠("ͷ༗ྉαʔϏε • Ͱ͔͍σʔλͷΠϯϙʔτ
– (PPHMF%BUB4UPSFʹஔ͍͔ͯΒΠϯϙʔτ͢Δͱߴ • 5BCMF%FDPSBUPST – σʔλͷ࣌ؒൣғΛࢦఆͯ͠ΫΤϦɻεΩϟϯରͷσʔλ͕খ͘͞ͳ ΔͷͰΫΤϦඅ༻ΛઅͰ͖Δ • +0*/੍ݶ.#ੲͷ – +0*/&"$)Λ͏ͱ.BQ3FEVDFͷTIV⒐FΈ͍ͨͳॲཧͰڊ େͳ+0*/ ԯYԯͱ͔ŋŋŋ ͯ͘͠ΕΔΑ
·ͱΊ • #JH2VFSZϑϧεΩϟϯͰͰ͔͍σʔλͷ 42-͕ඵͳαʔϏε • ΫιΫΤϦྗۀͰॲཧͪ͠Ό͏ΧοίΠΠ • ׂ౷࣏ (PPHMFͷ%$نͰ֖ͳ͍ ฒྻॲཧܥ
• όονɺϩάղੳͳΜ͔ʹ͑·͢ • ࢲ(PPHMFࣾͷճ͠ऀͰ͍͟͝·ͤΜ
5IBOLT ֆCZ͋ΘΏ͖