Google Dataflow: The New Open Model for Batch and Stream Processing
Conference
Big Data & Machine Learning
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Room 3 (Sabre) |
Thursday from 15:50 til 16:40 |
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In 2004 Google published the MapReduce paper, a programming model that kick-started big data as we know it. Ten years later, Google introduced Dataflow - a new paradigm, integrating batch and stream processing in one common abstraction. This time the offer was more than a paper, but also an open source Java SDK and a cloud managed service to run it. In 2016 big data players like Cask, Cloudera, Data Artisans, PayPal, Slack, Talend joined Google to propose Dataflow for incubation at the Apache Software Foundation - Dataflow is here, not only unifying batch and streaming, but also the big data world. In this talk we are going to review Dataflow's differentiating elements and why they matter. We’ll demonstrate Dataflow’s capabilities through a real-time demo with practical insights on how to manage and visualize streams of data. Apache Software Foundation - Dataflow Dataflow Programming Model Big Data - How Streaming Live Coding & Demos |
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Robert Kubis
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Robert is a Developer Advocate for the Google Cloud Platform based in London specializing in Container, Storage and Scalable technologies. Before joining Google, Robert collected over 10 years of experience in Software Development and Architecture. He has driven multiple full-stack application developments at SAP with a passion for distributed systems, containers and databases. In his spare time he enjoys following tech trends, good restaurants, traveling and improving his photographing skills :) More info at https://www.linkedin.com/in/kubisrobert |