Woot!!! Wonderful work everyone. A truly long-awaited milestone for the project -- almost since the beginning of incubation itself!
-s On Thu, Dec 17, 2020 at 2:14 PM Aizhamal Nurmamat kyzy <aizha...@apache.org> wrote: > Thanks to everyone who put an incredible amount of work into making this > happen! 🎉 🎊 > > On Thu, Dec 17, 2020 at 1:58 PM Xinbin Huang <bin.huan...@gmail.com> > wrote: > >> Amazing to see this! 🎉 🎉 🎉 🎉 🎉 🎉 >> >> On Thu, Dec 17, 2020 at 1:54 PM kumar pavan <pavankumar5...@gmail.com> >> wrote: >> >>> Congrats EveryOne >>> >>> >>> Thanks & Regards >>> Pavan >>> >>> >>> On Thu, Dec 17, 2020 at 12:36 PM Ash Berlin-Taylor <a...@apache.org> >>> wrote: >>> >>>> 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. >>>> >>>