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Why Airflow?
& What's new in
Airflow 2.3?
Kaxil Naik
ODSC 2022
Who am I?
● Committer & PMC Member of Apache Airflow
● Director of Airflow Engineering @ Astronomer
@kaxil
What is Apache Airflow?
A platform to programmatically author,
schedule, and monitor workflows
A platform to programmatically author,
schedule, and monitor workflows
A platform to programmatically author,
schedule, and monitor workflows
A platform to programmatically author,
schedule, and monitor workflows
Example DAG
Why Apache Airflow?
2k+
26.3k 6.8m+
Monthly Downloads
GitHub Stars
Contributors
23k+
Slack Members
The Community
Under …
Governed by
48
Committers
27
PMC Members
Project Management Committee
Project Management Committee
Integrations
And ……
75+ Providers
Docker Image
docker pull apache/airflow
Helm Chart
helm repo add apache-airflow https://airflow.apache.org/
helm install my-airflow apache-airflow/airflow
Conference & Meetups
13 Local Groups
3 years with min
6k-10k registrants
every year
Managed Airflow Vendors
What’s new in Airflow 2.3?
Biggest Airflow Release since 2.0
700+ commits! with 50 new features
Dynamic Task Mapping
Highlight feature of 2.3
First-class support for common ETL
pattern around dynamic tasks
Run same set of tasks for N number of
files in a bucket, DB records, ML models
where N is unpredictable.
Dynamic Task Mapping
Before After
Dynamic Task Mapping
Grid View replaces Tree View!!
Grid View replaces Tree View!!
Better support for Task Groups & Task
Mapping
Grid lines and hover effects to see which
task you are inspecting
Show durations of dag runs to quickly see
performance changes
Paves way for DAG Versioning
Create Connection in native JSON format
Create Connection in native JSON format
Create Connection in native JSON format
Create Connection in native JSON format
DB downgrades
First class support
Downgrades to a
- Airflow version
- or to a specific Alembic revision id
DB downgrades
First class support
Generate SQL for DB upgrade & downgrade
Allows DBA to run the DB Migrations ("--show-sql-only" flag)
Purge DB history
First class support
Helps reduce time when running DB
Migrations when updating Airflow version
Removes need of Maintenance DAGs!
‘--dry-run’ option to print the row
counts in the tables to be cleaned
Backup your DB before running this!
LocalKubernetesExecutor
Speed, Isolation & Simplicity packed in one!
Allows users to simultaneously run a
LocalExecutor and KubernetesExecutor.
An executor is chosen to run a task based
on the task's queue
Tasks just calling APIs + Tasks requiring
isolation due to dependencies or
computation-heavy
Slide from Jed’s Airflow’s Summit talk:
https://www.crowdcast.io/e/airflowsummit2022/35
DAG Processor separation
Standalone process for DAG parsing
“airflow dag-processor” CLI Command
Code Parsing and Callbacks (Sla + DAG’s
on_{success,failure}_callbacks)
Makes scheduler not run any user code*
First step towards multi-tenancy
Disabled by default, can be enabled by
Images from AIP-43
AIRFLOW__SCHEDULER__STANDALONE_DAG_PROCESSOR=True
Events Timetable
Run DAGs at arbitrary dates
Built-in Timetable
Useful for events which can’t be expressed
by Cron or Timedelta
Smooth Operator
Other Minor features
Minor but very handy!
● A new REST API endpoint (‘/dags’) that lets you bulk-pause/resume DAGs
● airflow dags reserialize command to delete serialized dags & reparse them
● A new listener plugin API that tracks TaskInstance state changes (used by OpenLineage)
● New Trigger Rule: all_skipped
● Doc: Single page to check Changelog & Updating Guide -> ‘Release Notes’
● (Experimental) Support for ARM Docker Images
Upgrade Now to Airflow 2.3!
Thank You
@kaxil

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Why Airflow? & What's new in Airflow 2.3?