Upgrade to PRO for Only $50/Year—Limited-Time Offer! 🔥
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
DigdagでETL処理をする
Search
tosametal
July 19, 2019
Technology
0
4.1k
DigdagでETL処理をする
データとML周辺エンジニアリングを考える会 #2
https://data-engineering.connpass.com/event/136756/
#data_ml_engineering
tosametal
July 19, 2019
Tweet
Share
More Decks by tosametal
See All by tosametal
マイクロアドのアドテクを支える技術
tosametal
1
190
Qiita Career Meetup for Server Side Engineers
tosametal
4
4.2k
Other Decks in Technology
See All in Technology
品質のための共通認識
kakehashi
PRO
3
220
[CMU-DB-2025FALL] Apache Fluss - A Streaming Storage for Real-Time Lakehouse
jark
0
110
バグハンター視点によるサプライチェーンの脆弱性
scgajge12
3
1k
ML PM Talk #1 - ML PMの分類に関する考察
lycorptech_jp
PRO
1
720
[デモです] NotebookLM で作ったスライドの例
kongmingstrap
0
100
Uncertainty in the LLM era - Science, more than scale
gaelvaroquaux
0
810
Debugging Edge AI on Zephyr and Lessons Learned
iotengineer22
0
120
チーリンについて
hirotomotaguchi
3
830
pmconf2025 - 他社事例を"自社仕様化"する技術_iRAFT法
daichi_yamashita
0
790
Playwrightのソースコードに見る、自動テストを自動で書く技術
yusukeiwaki
13
4.9k
世界最速級 memcached 互換サーバー作った
yasukata
0
330
Snowflakeでデータ基盤を もう一度作り直すなら / rebuilding-data-platform-with-snowflake
pei0804
2
740
Featured
See All Featured
The World Runs on Bad Software
bkeepers
PRO
72
12k
KATA
mclloyd
PRO
32
15k
Fantastic passwords and where to find them - at NoRuKo
philnash
52
3.5k
Building Flexible Design Systems
yeseniaperezcruz
330
39k
Large-scale JavaScript Application Architecture
addyosmani
515
110k
Faster Mobile Websites
deanohume
310
31k
10 Git Anti Patterns You Should be Aware of
lemiorhan
PRO
659
61k
The Success of Rails: Ensuring Growth for the Next 100 Years
eileencodes
47
7.8k
Code Review Best Practice
trishagee
74
19k
Become a Pro
speakerdeck
PRO
31
5.7k
What's in a price? How to price your products and services
michaelherold
246
12k
Bash Introduction
62gerente
615
210k
Transcript
DigdagͰETLॲཧΛ͢Δ σʔλͱMLपลΤϯδχΞϦϯάΛߟ͑Δձ #2 2019.07.19 தᠳଠ(@tosametal) גࣜձࣾϚΠΫϩΞυ ΞϓϦέʔγϣϯΤϯδχΞ
ϚΠΫϩΞυʹ͓͚Δػցֶश ࠂ৴γεςϜʹ͓͚ΔCTR༧ଌɺCVR༧ଌɺෆਖ਼ΫϦοΫͷݕग़ͳͲ
ϩάج൫ͷߏ Imp Server Click Server RTB Server Kafka Hadoop (σʔλΣΞϋε)
Digdag Hadoop (ੳج൫)
ϩάج൫ͷߏ Imp Server Click Server RTB Server Kafka Hadoop (σʔλΣΞϋε)
Digdag Hadoop (ੳج൫) at least once ϢχʔΫͳIDʹΑΔॏෳഉআ sessionͰཧ ႈͳॲཧ Kafka secondaryͰ kafkaΛࢦఆ jsonܗࣜͷ ߏԽσʔλ
Digdagͱ digϑΝΠϧʹએݴతʹϫʔΫϑϩʔΛهड़ Workflow as code εέδϡʔϧ࣮ߦɺϦΧόϦ UI͔Βਐḿͷ֬ೝ࠶࣮ߦ͕Մೳ ΦϖϨʔλΛࣗ࡞Մೳ
PostgreSQL ࣮ߦཤྺͳͲΛอଘ Task͝ͱʹhadoopΫϥΠΞϯτ ͱͳΔίϯςφΛ্ཱͪ͛Δ εέʔϧΞτՄೳ όον࣮ߦج൫ߏ
ෳࡶͳґଘؔΛ੍ޚͭͭ͠ ϫʔΫϑϩʔͷՄಡੑΛอͭ
ϓϩδΣΫτΛػೳ୯ҐͰׂ ϓϩδΣΫτͱ In Digdag, workflows are packaged together with other
files used in the workflows. The files can be anything such as SQL scripts, Python/Ruby/Shell scripts, configuration files, etc. This set of the workflow definitions is called project. ެࣜυΩϡϝϯτ(http://docs.digdag.io/)ΑΓҾ༻ ϚΠΫϩΞυͰݱࡏ60ݸͷϓϩδΣΫτ͕ಈ͍͍ͯΔ
ϓϩδΣΫτͷґଘؔ schedule: daily>: 12:00:00 +task1: _parallel: true +subtask1: call>: subtask1.dig
+subtask2: call>: subtask2.dig +task2: echo>: task finished successfully •callΦϖϨʔλΛ͏͜ͱͰdigϑΝΠϧ ͷׂΛߦ͏͜ͱ͕Մೳ •requireΛ͏ͱ͏গ͠ෳࡶͳDAGͷ දݱՄೳ subtask1 subtask2 task2
ϓϩδΣΫτؒͷґଘؔ ϓϩδΣΫτA ϓϩδΣΫτB ଞͷϓϩδΣ Ϋτͷ݁ՌΛݟΔ ͜ͱग़དྷͳ͍
ϓϩδΣΫτؒͷґଘؔ +touch_task: s3_touch>: bucket/flag/fileX +wait_task: s3_wait>: bucket/flag/fileX ϓϩδΣΫτB ϓϩδΣΫτA fileX
ࣗ࡞ΦϖϨʔλ ࢀߟ:https://github.com/ tosametal/digdag-plugins
ͦͷଞ ϫʔΫϑϩʔશମΛႈʹ͢Δ • hiveΫΤϦinsert overwrite • distcpoverwrite deleteΦϓγϣϯΛࢦఆ ϦτϥΠΛઃఆ͢Δ •
exponential interval
·ͱΊ • ϓϩδΣΫτංେԽ͠ͳ͍Α͏ʹػೳͰׂ • ϓϩδΣΫτؒͷґଘs3_waitͰղܾ • Α͘͏ػೳϓϥάΠϯΛ࡞Ζ͏
None