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Diving Deep into Apache Flink with Robert Metzger | Ep. 14

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Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | New episodes every Monday! In part two of the "Real-Time Analytics" podcast, Robert Metzger, the PMC chair of Apache Flink, elaborates on using Flink as a developer. Metzger discusses the spectrum of APIs in Flink, ranging from expressive APIs to easy-to-use APIs. He mentions the process function, a low-level, flexible API that exposes basic building blocks of Flink, such as real-time events, state, and event time. Metzger also speaks about the windowing API of Flink and the Async I/O operator. He further details how Flink users can work with a combination of SQL and Java code in the data stream API. You won't want to miss this episode!
Flink Deployments At Decodable: https://www.decodable.co/blog/flink-deployments-at-decodable
3 Reasons Why You Need Apache Flink for Stream Processing: https://thenewstack.io/3-reasons-why-you-need-apache-flink-for-stream-processing/#:~:text=For%20example%2C%20Uber%20uses%20Flink,streaming%20data%20at%20massive%20scale.

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60 episoade

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Content provided by StarTree, founded by the creators of Apache Pinot™ and Founded by the creators of Apache Pinot™. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by StarTree, founded by the creators of Apache Pinot™ and Founded by the creators of Apache Pinot™ or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.

Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | New episodes every Monday! In part two of the "Real-Time Analytics" podcast, Robert Metzger, the PMC chair of Apache Flink, elaborates on using Flink as a developer. Metzger discusses the spectrum of APIs in Flink, ranging from expressive APIs to easy-to-use APIs. He mentions the process function, a low-level, flexible API that exposes basic building blocks of Flink, such as real-time events, state, and event time. Metzger also speaks about the windowing API of Flink and the Async I/O operator. He further details how Flink users can work with a combination of SQL and Java code in the data stream API. You won't want to miss this episode!
Flink Deployments At Decodable: https://www.decodable.co/blog/flink-deployments-at-decodable
3 Reasons Why You Need Apache Flink for Stream Processing: https://thenewstack.io/3-reasons-why-you-need-apache-flink-for-stream-processing/#:~:text=For%20example%2C%20Uber%20uses%20Flink,streaming%20data%20at%20massive%20scale.

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