Apache Zeppelin: A friendlier way to Flink
summary
Shows a Zeppelin notebook workflow running Flink examples end to end: a quick word count from local mini-cluster, loading jars to call FlinkML and Mahout for OLS regression (observes sum of squared residuals drop after changing a step size), graph processing in Gelly exported as JSON and visualized with d3.js/AngularJS, and a live Twitter streaming demo that windows tweets in 2‑minute sliding windows offset every 30s and counts occurrences. Notes: ResourcePools pass small objects between interpreters, streaming paragraphs run indefinitely until killed, and YARN support is not yet available.
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chapters (15)
- 0:00Introduction and setup pain
- 3:31Big data for everyone
- 5:42What is Apache Zeppelin
- 8:35Getting started with Flink
- 11:09Data science and ML in Zeppelin
- 15:24Resource pools and sharing
- 19:19Visualizing graphs with Zeppelin
- 21:46Streaming with Flink
- 25:01Zeppelin for demos and meetups
- 26:56Future of Zeppelin and community
- 27:38Q&A on resource pools
- 30:08Q&A on streaming interpreter
- 33:01Q&A on execution engine
- 36:47Q&A on Zeppelin roadmap
- 42:33Q&A wrap-up and closing
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