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Python Streaming Pipelines with Beam on Flink
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This a talk by Thomas Weise presented at SF Big Analytics meetup in Feb 2019 at Lyft HQ in San Francisco.
Apache Beam established a unified programming model for data processing. Its vision bridges not only the gap between batch and streaming, but also across languages (Java, Python, Go, ..) and various execution engines. To accomplish all of this, Beam requires cross-language support.
Over the past year, the Beam community has leaped closer towards realizing the cross-language support and enabled processing pipelines written in Python to run on Apache Flink. Lyft has contributed to this effort and is about to launch the first production Python streaming use case on this new stack.
Python running natively with all its libraries & with the JVM based Flink runner? Let’s take a look at how the magic works and what comes next!
Thomas Weise is Software Engineer, Streaming Platform at Lyft. He is Flink committer, PMC member of Apache Apex & Beam, and has contributed to several more of the ecosystem projects.
Apache Beam established a unified programming model for data processing. Its vision bridges not only the gap between batch and streaming, but also across languages (Java, Python, Go, ..) and various execution engines. To accomplish all of this, Beam requires cross-language support.
Over the past year, the Beam community has leaped closer towards realizing the cross-language support and enabled processing pipelines written in Python to run on Apache Flink. Lyft has contributed to this effort and is about to launch the first production Python streaming use case on this new stack.
Python running natively with all its libraries & with the JVM based Flink runner? Let’s take a look at how the magic works and what comes next!
Thomas Weise is Software Engineer, Streaming Platform at Lyft. He is Flink committer, PMC member of Apache Apex & Beam, and has contributed to several more of the ecosystem projects.
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