Apache Beam is a unified model for defining both batch and streaming data-parallel processing pipelines, as well as a set of language-specific SDKs for constructing pipelines and Runners for executing them on distributed processing backends, including Apache Flink, Apache Spark, Google Cloud Dataflow and Hazelcast Jet.

Key Points

Data pipelines connect, transform data sources to data targets in batches or event streams
Beam provides high-level, portable data pipeline processing model over data services runtimes
Beam input data events can come from Spark, Flink, Kafka and more that arrive over time
Beam processing done via SDK: SQL, Java, Python, Go and ??
Beam can perform many transformations from existing libraries and new application logic
Implement batch and streaming data processing jobs that run on any execution engine.

References

Reference_description_with_linked_URLs_______________________	Notes______________________________________________________________
youtube Apache Beam overview 2019	Beam overview 2019
https://github.com/apache/beam	Beam github
https://beam.apache.org/documentation/	Beam docs
https://beam.apache.org/documentation/runtime/model/	Beam execution model
https://beam.apache.org/documentation/resources/learning-resources/	Beam learning resources - interactive examples ***
https://beam.apache.org/documentation/programming-guide/	Beam Programming Guide
https://projects.apache.org/projects.html?category	Apache Big Data projects
https://www.educba.com/my-courses/dashboard/	Data engineering education site: educfba
https://beam.apache.org/get-started/quickstart-java/	Java quickstart
https://beam.apache.org/documentation/dsls/sql/walkthrough/
https://beam.apache.org/get-started/quickstart-py/	Python quickstart