Stream processing has fundamentally changed the way we build and think about data pipelines — but the technologies that unlock the value of this powerful paradigm haven’t always been friendly to non-Java/Scala developers. Apache Flink has recently introduced PyFlink, allowing developers to tap into streaming data in real-time with the flexibility of Python and its wide ecosystem for data analytics and Machine Learning. In this talk, we will explore the basics of PyFlink and showcase how developers can make use of a simple tool like interactive notebooks to harness the full power of an advanced stream processor like Apache Flink.
|Change Data Capture with Flink SQL and Debezium||ApacheCon||September 2020|
|Building an End-to-End Analytics Pipeline with PyFlink||Flink Forward Global 2020||October 2020|
|Building an End-to-End Analytics Pipeline with PyFlink||Data Science UA||November 2020|