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
[PyCon JP 2019] 新米Pythonistaが贈るAirflow入門&活用事例紹介
Search
Naoki Matsuda
September 17, 2019
Technology
7k
2
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
[PyCon JP 2019] 新米Pythonistaが贈るAirflow入門&活用事例紹介
PyCon JP 2019の発表資料です。
Naoki Matsuda
September 17, 2019
More Decks by Naoki Matsuda
See All by Naoki Matsuda
Tech x Marketing #4 Airflowでもサブワークフロー単位で分割開発したい!
matsudan
0
230
Other Decks in Technology
See All in Technology
多層防御と最⼩権限で実現する、安全なAIエージェント設計パターン
lycorptech_jp
PRO
0
210
PM領域でのAI Agentの活用
lycorptech_jp
PRO
0
280
PdMをやめて、 "プロダクトビルダー"という 働き方に変えました / PdM to Product Builder
shikichee
2
730
AndroidでHDRメディアを「壊さずに」扱う
chigichan24
0
410
いま、生成AIにKaggleをどこまで 任せられるか — ROGIIコンペでの進め方とTips
k951286
3
1.4k
ペアプロの価値はコードを書くことだけじゃない
codmoninc
PRO
0
130
KPIだけでは評価できないプロダクトが考えるべき Evalsという第二の評価系 / Beyond KPIs: Evals as a Second Evaluation Framework for Products #PdEConf
aki_iinuma
4
3.7k
#jawssonic2026 あの時代が悪かった ~動かなかったSageMakerと共に迎えたイベント当日~
ktkn1129
0
130
AIで開発は速くなったのに、なぜ現場は楽にならないのか 〜あなたの組織のボトルネックを突き止めるワークショップ〜
jacopen
1
270
Oracle Cloud Infrastructure IaaS 新機能アップデート 2026/6 - 2026/8
oracle4engineer
PRO
0
110
Kiro Crewしか勝たん!?
miu_crescent
PRO
0
180
AI時代のAPI品質を支えるガードレール / API Guardrails for API quality in the AI era
yokawasa
1
140
Featured
See All Featured
Future Trends and Review - Lecture 12 - Web Technologies (1019888BNR)
signer
PRO
0
3.7k
JavaScript: Past, Present, and Future - NDC Porto 2020
reverentgeek
52
6.1k
Helping Users Find Their Own Way: Creating Modern Search Experiences
danielanewman
31
3.4k
Practical Tips for Bootstrapping Information Extraction Pipelines
honnibal
25
2.1k
The Organizational Zoo: Understanding Human Behavior Agility Through Metaphoric Constructive Conversations (based on the works of Arthur Shelley, Ph.D)
kimpetersen
PRO
0
440
SEOcharity - Dark patterns in SEO and UX: How to avoid them and build a more ethical web
sarafernandez
0
270
Bioeconomy Workshop: Dr. Julius Ecuru, Opportunities for a Bioeconomy in West Africa
akademiya2063
PRO
1
340
Speed Design
sergeychernyshev
33
2.1k
Optimising Largest Contentful Paint
csswizardry
37
3.9k
Hiding What from Whom? A Critical Review of the History of Programming languages for Music
tomoyanonymous
3
1.2k
Color Theory Basics | Prateek | Gurzu
gurzu
0
460
GraphQLとの向き合い方2022年版
quramy
50
15k
Transcript
৽ถPythonista͕ଃΔAirflowೖ & ׆༻ࣄྫհ PyCon JP 2019 2019.9.17 Naoki Matsuda
Agenda 0. ࣗݾհ 1. Airflowͷ֓ཁ 2. Airflowͷࣾࣄྫհ - ։ൃϓϩμΫτ֓ཁͱ՝, Airflowͷڥ
3. AirflowͰͭ·͍ͮͨ - λεΫؒͷσʔλͷΓͱΓ - DAGಈ࡞֬ೝ ~ dockerͰϩʔΧϧ։ൃڥߏங
ࣗݾհ দా थ (·ͭͩ ͳ͓͖) - ॴଐɿגࣜձࣾ ి௨σδλϧ - ۀɿόοΫΤϯυαʔϏεɺETLपΓͷ։ൃ
- 2018ೖࣾ
1. Airflowͷ֓ཁ
Apache Airflow֓ཁ όονॲཧ͔ΒͳΔϫʔΫϑϩʔͷεέδϡʔϦϯάˍϞχλ Ϧϯά͕ՄೳͳϓϥοτϑΥʔϜ - Airbnbࣾ - Φʔϓϯιʔε (Apache software
foundationͷincubation project)1,2 - PythonͰ࣮͞Ε͍ͯΔ3 - ։ൃίϛϡχςΟ͕׆ൃ3 IUUQTJODVCBUPSBQBDIFPSHQSPKFDUTBJSGMPXIUNM IUUQTBJSGMPXBQBDIFPSHMJDFOTFIUNM IUUQTHJUIVCDPNBQBDIFBJSGMPX
։ൃίϛϡχςΟͷ׆ൃ͞(2019.9.9࣌)
Apache AirflowͰͰ͖Δ͜ͱ - PythonίʔυͰϫʔΫϑϩʔ(DAG)Λఆٛ - ґଘؔʹج͍ͮͨλεΫͷ࣮ߦ - ϫʔΫϑϩʔͷεέδϡʔϦϯά - ϦονͳWeb
UI - DAG࣮ߦεςʔλεͷϞχλϦϯά - λεΫͷϩά֬ೝ - ґଘؔͷՄࢹԽ ͳͲ
PythonίʔυͰϫʔΫϑϩʔఆٛ(DAGͷ࡞) λεΫؒґଘؔͷఆٛ λεΫ1 λεΫ2 DAGͷڞ௨ઃఆ ࣮ߦස, ࣮ߦظؒ, λΠϜΞτ࣌ؒͳͲ
ϫʔΫϑϩʔΛߏ͢ΔλεΫͷ࡞ ≈ - ϫʔΫϑϩʔOperatorͱݺΕΔλεΫʹΑΓߏ͞ΕΔ1 - 1ͭͷOperatorͰ1ͭͷλεΫΛهड़ OperatorͷҾɻ ֤Operator͕ԿͷҾΛ ͱΔ͔υΩϡϝϯτࢀর2 IUUQTBJSGMPXBQBDIFPSHDPODFQUTIUNMPQFSBUPST
IUUQTBJSGMPXBQBDIFPSH@BQJBJSGMPXPQFSBUPSTJOEFYIUNM
ϫʔΫϑϩʔΛߏ͢ΔλεΫͷ࡞ - BashίϚϯυ࣮ߦ: BashOperator - Python࣮ؔߦ: PythonOperator - SQL࣮ߦ: MySqlOperator,
PostgresOperator, … - HTTPϦΫΤετૹ৴: SimpleHttpOperator - ͦͷଞΫϥυܥͳͲ: BigQueryOperator, AWSAthenaOperator, … - ಛఆ݅Ληϯγϯά: Sensor IUUQTBJSGMPXBQBDIFPSHDPODFQUTIUNMPQFSBUPST IUUQTBJSGMPXBQBDIFPSH@BQJBJSGMPXPQFSBUPSTJOEFYIUNM
2. ࣾࣄྫհ - ։ൃϓϩμΫτ֓ཁͱ՝, Airflowͷߏ
։ൃ৫ͱϓϩμΫτʹ͍ͭͯ ɾɾɾ ࠂ৴ σʔλ ϓϥϯφʔ Ӧۀ - ڈ7~9݄, - GoogleDispla
y - ҿྉۀք imp 100000 clicks 5000 cv 700 cost ɾɾɾ ϝσΟΞ ։ൃ৫ νʔϜنɿσʔλΤϯδχΞ ໊ σʔλαΠΤϯςΟετͳͲ໊ d ϓϩμΫτ ͚ࣾσδλϧࠂϓϥϯχϯάπʔϧ ࣾͰѻ͏ϝσΟΞɾΫϥΠΞϯτͷࠂ৴࣮σʔλΛՄࢹԽˍ༧ଌ ϓϩμΫτ (PPHMF :BIPP 5XJUUFS 'BDFCPPL -*/&
։ൃϓϩμΫτʹ͓͚Δ՝ - σʔλ͕RDBʹೖͬͯͳ͍ ৴Ϩϙʔτσʔλ͕ੳ༻ͷྻࢤσʔλϕʔεʹ ͋ͬͨΓɺϚελσʔλ͕εϓϨουγʔτʹ͋ͬͨΓ… - ඞཁͳใΛՃ͢ΔͨΊʹଟ͘ͷϦϨʔγϣϯΛͨͲΔ
։ൃϓϩμΫτʹ͓͚Δ՝ - σʔλ͕RDBʹೖͬͯͳ͍ ৴Ϩϙʔτσʔλ͕ੳ༻ͷྻࢤσʔλϕʔεʹ ͋ͬͨΓɺϚελσʔλ͕εϓϨουγʔτʹ͋ͬͨΓ… - ඞཁͳใΛՃ͢ΔͨΊʹଟ͘ͷϦϨʔγϣϯΛͨͲΔ → ։ൃϓϩμΫτ༻ʹσʔλϚʔτ࡞ RDBʹϑΝΫτ,
σΟϝϯγϣϯςʔϒϧΛETLͰ࡞
Airflowߏ apache-airflow 1.10.2 web worker scheduler Amazon S3 Amazon RDS
Airflow AWS Fargate Amazon ElastiCache Redis Elastic Load Balancing flower DAGs - AWS FargateʹAirflowΛσϓϩΠ ≈ ≈
docker-airflow https://github.com/puckel/docker-airflow
ߏஙͨ͠σʔλϑϩʔ ֤ϝσΟΞࠂ৴σʔλ ϦϨʔγϣϯςʔϒϧܥ JOIN ΫϥΠΞϯτใܥ ʜ ΧϥϜ໊ دͤͳͲ ≈ Amazon
Athena Backend service INSERT "JSGMPX͕࣮ߦ͢ΔλεΫ INSERT
3. AirflowͰͭ·͍ͮͨ - λεΫؒͷσʔλͷΓͱΓ - DAGಈ࡞֬ೝ ~dockerͰϩʔΧϧ։ൃڥߏங
λεΫؒͷσʔλͷΓͱΓ λεΫؒͷσʔλΓͱΓXComΛ͏ - XComͷ͍ํ - XComσʔλΛpush - ؔͰreturn - ؔͰkwargs['task_instance’].
xcom_push(value=hoge, key=‘huga’) - Λฦ͢Operator ྫ: BigqueryGetDataOperator - XCom͔ΒσʔλΛpull - kwargs['task_instance’].xcom_pull() metadata database
λεΫؒͷσʔλͷΓͱΓ BigQuery͔ΒςʔϒϧσʔλΛऔಘͯͦ͠ͷσʔλΛՃ͢Δྫ
λεΫؒͷσʔλͷΓͱΓ BQςʔϒϧ͔Βσʔλऔಘ # XComʹpush͞ΕΔ BigQuery͔ΒςʔϒϧσʔλΛऔಘͯͦ͠ͷσʔλΛՃ͢Δྫ
λεΫؒͷσʔλͷΓͱΓ BQςʔϒϧ͔Βσʔλऔಘ # XComʹpush͞ΕΔ transpose_dataؔΛ࣮ߦ BigQuery͔ΒςʔϒϧσʔλΛऔಘͯͦ͠ͷσʔλΛՃ͢Δྫ
λεΫؒͷσʔλͷΓͱΓ 1. task1Ͱpush͞ΕͨXcomͷ σʔλΛpullͯ͠ 2. ςʔϒϧͷσʔλΛసஔ BQςʔϒϧ͔Βσʔλऔಘ # XComʹpush͞ΕΔ transpose_dataؔΛ࣮ߦ
BigQuery͔ΒςʔϒϧσʔλΛऔಘͯͦ͠ͷσʔλΛՃ͢Δྫ
λεΫؒͷσʔλͷΓͱΓ provide_contextΛTrueʹ͠ͳ͍ͱkwargs[‘task_intance’]ͰKeyError - provide_context=False (default) kwargs : {} - provide_context=True
kwargs: { 'dag': <DAG: sample>, 'ds': '2019-09-10’, 'next_ds': '2019-09-10’, … 'task_instance’: <TaskInstance: sample.task1_2 …> … }
λεΫؒͷσʔλͷΓͱΓ - PythonOperatorͷҾͰTrue OR - default_argsͰઃఆ
DAGಈ࡞֬ೝ ~ϩʔΧϧ։ൃڥߏங - ࡞ͨ͠ϫʔΫϑϩʔ(DAG)ͷςετͲ͏Δʁ എܠɿ - Ϋϥυ্devڥͰͷDAGಈ࡞֬ೝͰS3upload͢Δखؒ - ଞͷਓ͕ಉ͡λΠϛϯάͰ։ൃ͍ͯ͠ΔͱΓͮΒ͍… →
ϩʔΧϧͰDAGͷಈ࡞֬ೝ͍ͨ͠ʂ
DAGಈ࡞֬ೝ ~ϩʔΧϧ։ൃڥߏங → dockerͰAirflowΛϩʔΧϧʹ্ཱͪ͛Δ - ࡞ͨ͠ϫʔΫϑϩʔ(DAG)ͷςετͲ͏Δʁ എܠɿ - Ϋϥυ্devڥͰͷDAGಈ࡞֬ೝͰS3upload͢Δखؒ -
ଞͷਓ͕ಉ͡λΠϛϯάͰ։ൃ͍ͯ͠ΔͱΓͮΒ͍… → ϩʔΧϧͰDAGͷಈ࡞֬ೝ͍ͨ͠ʂ
DAGಈ࡞֬ೝ ~ϩʔΧϧ։ൃڥߏங
DAGಈ࡞֬ೝ ~ϩʔΧϧ։ൃڥߏங LocalExecutorΛ༻
DAGಈ࡞֬ೝ ~ϩʔΧϧ։ൃڥߏங LocalExecutorΛ༻ dagsσΟϨΫτϦΛvolumeͱ͠ ͯϚϯτ
DAGಈ࡞֬ೝ ~ϩʔΧϧ։ൃڥߏங - dockerͷvolumeͱͯ͠dagsσΟϨΫτϦΛϚϯ τ͍ͯ͠ΔͷͰॻ͖͑ͨΒ͙͢ʹө - Web UIʹ͕ࣗ࡞ͨ͠DAGͷΈ͕දࣔ͞ΕΔ - ECR͔ΒimageΛऔͬͯ͘ΔΑ͏ʹͯ͠ຊ൪ͱಉ͡
ڥͰಈ࡞֬ೝͰ͖Δ
·ͱΊ - ETL͕ඞཁͳࣾ։ൃϓϩμΫτʹ͓͍ͯAirflowΛ ͍·ͨ͠ɻ - ຊ൪ڥͷAirflowECS FargateʹσϓϩΠ͠·ͨ͠ɻ - ϩʔΧϧ։ൃڥʹdockerΛ༻ͯ͠։ൃָ͕ʹͳΓ ·ͨ͠ɻ
We are hiring ! https://bit.ly/2UqWPGO
supplementary information
λεΫؒґଘؔͷఆٛ - Ϗοτγϑτԋࢉࢠ(>>, <<)Λ͍λεΫͷґଘؔΛද͢ - ޙଓλεΫͷ࣮ߦ݅શͯͷઌߦλεΫޭ͕σϑΥϧτઃఆ1 - શOperator͕࣋ͭtrigger_ruleҾͰ࣮ߦ݅ΛมߋՄೳ1 IUUQTBJSGMPXBQBDIFPSHDPODFQUTIUNMUSJHHFSSVMFT
- γϯϓϧͳґଘؔ task1 >> task2 - λεΫάϧʔϓ͕͋Δґଘؔ task1 >> [task2-1,task2-2] >> task3
Web UI: ϞχλϦϯά - Tree View - Gantt Chart
Web UI: Variable
ฒྻઃఆ Configuring parallelism in airflow.cfg - parallelism : ࢄॲཧΫϥελશମͰ࣮ߦՄೳͳϓϩηε -
dag_concurrency : ҰͭͷϫʔΧͰಉ࣮࣌ߦՄೳͳ࠷େϓϩηε - max_active_runs_per_dag : DAG෦Ͱಉ࣮࣌ߦՄೳͳ࠷େλε Ϋ - worker_concurrency : ҰͭͷCeleryϫʔΧͰಉ࣮࣌ߦՄೳͳ࠷େ ϓϩηε IUUQTBOBMZUJDTMJWFTFOTFDPKQFOUSZ