Great job everyone! 🎉👏 Really amazing work from all of you!
Thanks. -Felix Sent from ProtonMail Mobile On Thu, Dec 17, 2020 at 18:59, Jarek Potiuk <jarek.pot...@polidea.com> wrote: > WOHOO! > > On Thu, Dec 17, 2020 at 6:54 PM Shaw, Damian P. > <damian.sha...@credit-suisse.com> wrote: > >> Great news! Is there a single web page that highlights these major features >> as you’ve listed them? >> >> Damian >> >> From: Ash Berlin-Taylor <a...@apache.org> >> Sent: Thursday, December 17, 2020 12:36 >> To: us...@airflow.apache.org >> Cc: annou...@apache.org; dev@airflow.apache.org >> Subject: Apache Airflow 2.0.0 is released! >> >> I am proud to announce that Apache Airflow 2.0.0 has been released. >> >> The source release, as well as the binary "wheel" release (no sdist this >> time), are available here >> >> We also made this version available on PyPi for convenience (`pip install >> apache-airflow`): >> >> 📦 PyPI: https://pypi.org/project/apache-airflow/2.0.0 >> >> The documentation is available on: >> >> https://airflow.apache.org/ >> >> 📚 Docs: http://airflow.apache.org/docs/apache-airflow/2.0.0/ >> >> Docker images will be available shortly -- check out >> https://hub.docker.com/r/apache/airflow/tags?page=1&ordering=last_updated&name=2.0.0 >> for it to appear >> >> The full changelog is about 3,000 lines long (already excluding everything >> backported to 1.10), so for now I’ll simply share some of the major features >> in 2.0.0 compared to 1.10.14: >> >> A new way of writing dags: the TaskFlow API (AIP-31) >> >> (Known in 2.0.0alphas as Functional DAGs.) >> >> DAGs are now much much nicer to author especially when using PythonOperator. >> Dependencies are handled more clearly and XCom is nicer to use >> >> Read more here: >> >> [TaskFlow API >> Tutorial](http://airflow.apache.org/docs/apache-airflow/stable/tutorial_taskflow_api.html) >> >> [TaskFlow API >> Documentation](https://airflow.apache.org/docs/apache-airflow/stable/concepts.html#decorated-flows) >> >> A quick teaser of what DAGs can now look like: >> >> ``` >> >> from airflow.decorators import dag, task >> from airflow.utils.dates import days_ago >> >> @dag(default_args={'owner': 'airflow'}, schedule_interval=None, >> start_date=days_ago(2)) >> def tutorial_taskflow_api_etl(): >> @task >> def extract(): >> return {"1001": 301.27, "1002": 433.21, "1003": 502.22} >> >> @task >> def transform(order_data_dict: dict) -> dict: >> total_order_value = 0 >> >> for value in order_data_dict.values(): >> total_order_value += value >> >> return {"total_order_value": total_order_value} >> >> @task() >> def load(total_order_value: float): >> >> print("Total order value is: %.2f" % total_order_value) >> >> order_data = extract() >> order_summary = transform(order_data) >> load(order_summary["total_order_value"]) >> >> tutorial_etl_dag = tutorial_taskflow_api_etl() >> >> ``` >> >> Fully specified REST API (AIP-32) >> >> We now have a fully supported, no-longer-experimental API with a >> comprehensive OpenAPI specification >> >> Read more here: >> >> [REST API >> Documentation](http://airflow.apache.org/docs/apache-airflow/stable/stable-rest-api-ref.html). >> >> Massive Scheduler performance improvements >> >> As part of AIP-15 (Scheduler HA+performance) and other work Kamil did, we >> significantly improved the performance of the Airflow Scheduler. It now >> starts tasks much, MUCH quicker. >> >> Over at Astronomer.io we’ve [benchmarked the scheduler—it’s >> fast](https://www.astronomer.io/blog/airflow-2-scheduler) (we had to triple >> check the numbers as we don’t quite believe them at first!) >> >> Scheduler is now HA compatible (AIP-15) >> >> It’s now possible and supported to run more than a single scheduler >> instance. This is super useful for both resiliency (in case a scheduler goes >> down) and scheduling performance. >> >> To fully use this feature you need Postgres 9.6+ or MySQL 8+ (MySQL 5, and >> MariaDB won’t work with more than one scheduler I’m afraid). >> >> There’s no config or other set up required to run more than one >> scheduler—just start up a scheduler somewhere else (ensuring it has access >> to the DAG files) and it will cooperate with your existing schedulers >> through the database. >> >> For more information, read the [Scheduler HA >> documentation](http://airflowapache.org/docs/apache-airflow/stable/scheduler.html#running-more-than-one-scheduler). >> >> Task Groups (AIP-34) >> >> SubDAGs were commonly used for grouping tasks in the UI, but they had many >> drawbacks in their execution behaviour (primarirly that they only executed a >> single task in parallel!) To improve this experience, we’ve introduced “Task >> Groups”: a method for organizing tasks which provides the same grouping >> behaviour as a subdag without any of the execution-time drawbacks. >> >> SubDAGs will still work for now, but we think that any previous use of >> SubDAGs can now be replaced with task groups. If you find an example where >> this isn’t the case, please let us know by opening an issue on GitHub >> >> For more information, check out the [Task Group >> documentation](http://airflow.apache.org/docs/apache-airflow/stable/concepts.html#taskgroup). >> >> Refreshed UI >> >> We’ve given the Airflow UI a visual refresh and updated some of the styling. >> Check out the [UI section of the >> docs](http://0.0.0.0:8000/docs/apache-airflow/stable/ui.html) for >> screenshots. >> >> We have also added an option to auto-refresh task states in Graph View so >> you no longer need to continuously press the refresh button :). >> >> ## Smart Sensors for reduced load from sensors (AIP-17) >> >> If you make heavy use of sensors in your Airflow cluster, you might find >> that sensor execution takes up a significant proportion of your cluster even >> with “reschedule” mode. To improve this, we’ve added a new mode called >> “Smart Sensors”. >> >> This feature is in “early-access”: it’s been well-tested by AirBnB and is >> “stable”/usable, but we reserve the right to make backwards incompatible >> changes to it in a future release (if we have to. We’ll try very hard not >> to!) >> >> Read more about it in the [Smart Sensors >> documentation](https://airflow.apache.org/docs/apache-airflow/stable/smart-sensor.html). >> >> Simplified KubernetesExecutor >> >> For Airflow 2.0, we have re-architected the KubernetesExecutor in a fashion >> that is simultaneously faster, easier to understand, and more flexible for >> Airflow users. Users will now be able to access the full Kubernetes API to >> create a .yaml pod_template_file instead of specifying parameters in their >> airflow.cfg. >> >> We have also replaced the executor_config dictionary with the pod_override >> parameter, which takes a Kubernetes V1Pod object for a 1:1 setting override. >> These changes have removed over three thousand lines of code from the >> KubernetesExecutor, which makes it run faster and creates fewer potential >> errors. >> >> Read more here: >> >> Docs on >> [pod_template_file](https://airflow.apache.org/docs/apache-airflow/stable/executor/kubernetes.html?highlight=pod_override#pod-template-file) >> >> Docs on >> [pod_override](https://airflow.apache.org/docs/apache-airflow/stable/executor/kubernetes.html?highlight=pod_override#pod-override) >> >> Airflow core and providers: Splitting Airflow into 60+ packages >> >> Airflow 2.0 is not a monolithic “one to rule them all” package. We’ve split >> Airflow into core and 61 (for now) provider packages. Each provider package >> is for either a particular external service (Google, Amazon, Microsoft, >> Snowflake), a database (Postgres, MySQL), or a protocol (HTTP/FTP). Now you >> can create a custom Airflow installation from “building” blocks and choose >> only what you need, plus add whatever other requirements you might have. >> Some of the common providers are installed automatically (ftp, http, imap, >> sqlite) as they are commonly used. Other providers are automatically >> installed when you choose appropriate extras when installing Airflow. >> >> The provider architecture should make it much easier to get a fully >> customized, yet consistent runtime with the right set of Python dependencies. >> >> But that’s not all: you can write your own custom providers and add things >> like custom connection types, customizations of the Connection Forms, and >> extra links to your operators in a manageable way. You can build your own >> provider and install it as a Python package and have your customizations >> visible right in the Airflow UI. >> >> Our very own Jarek Potiuk has written about [providers in much more >> detail](https://www.polidea.com/blog/airflow-2-providers/) on the Polidea >> blog. >> >> Docs on the [providers concept and writing custom >> providers](http://airflow.apache.org/docs/apache-airflow-providers/) >> >> Docs on the [all providers packages >> available](http://airflow.apache.org/docs/apache-airflow-providers/packages-ref.html) >> >> Security >> >> As part of Airflow 2.0 effort, there has been a conscious focus on Security >> and reducing areas of exposure. This is represented across different >> functional areas in different forms. For example, in the new REST API, all >> operations now require authorization. Similarly, in the configuration >> settings, the Fernet key is now required to be specified. >> >> Configuration >> >> Configuration in the form of the airflow.cfg file has been rationalized >> further in distinct sections, specifically around “core”. Additionally, a >> significant amount of configuration options have been deprecated or moved to >> individual component-specific configuration files, such as the >> pod-template-file for Kubernetes execution-related configuration. >> >> Thanks to all of you >> >> We’ve tried to make as few breaking changes as possible and to provide >> deprecation path in the code, especially in the case of anything called in >> the DAG. That said, please read throughUPDATING.md to check what might >> affect you. For example: r We re-organized the layout of operators (they now >> all live under airflow.providers.*) but the old names should continue to >> work - you’ll just notice a lot of DeprecationWarnings that need to be fixed >> up. >> >> Thank you so much to all the contributors who got us to this point, in no >> particular order: Kaxil Naik, Daniel Imberman, Jarek Potiuk, Tomek Urbaszek, >> Kamil Breguła, Gerard Casas Saez, Xiaodong DENG, Kevin Yang, James Timmins, >> Yingbo Wang, Qian Yu, Ryan Hamilton and the 100s of others who keep making >> Airflow better for everyone. >> >> ============================================================================== >> Please access the attached hyperlink for an important electronic >> communications disclaimer: >> http://www.credit-suisse.com/legal/en/disclaimer_email_ib.html >> ============================================================================== > > -- > > Jarek Potiuk > [Polidea](https://www.polidea.com/) | Principal Software Engineer > > M: [+48 660 796 129](tel:+48660796129) > [Polidea](https://www.polidea.com/)
