The world of big data involves an ever-changing field of players. Much as SQL is a lingua franca for declarative data analysis, Apache Beam aims to provide a portable standard for expressing robust, out-of-order data processing pipelines in a variety of languages across a variety of platforms. Tyler Akidau explains how this vision has been realized and discusses the challenges that lie ahead.
Tyler Akidau is a senior staff software engineer at Google Seattle, where he leads technical infrastructure internal data processing teams for MillWheel and Flume. Tyler is a founding member of the Apache Beam PMC and has spent the last seven years working on massive-scale data processing systems. Though deeply passionate and vocal about the capabilities and importance of stream processing, he is also a firm believer that batch and streaming are two sides of the same coin and that the real endgame for data processing systems is the seamless merging between the two. He is the author of the 2015 “Dataflow Model” paper and “Streaming 101” and “Streaming 102” blog posts. His preferred mode of transportation is by cargo bike, with his two young daughters in tow.
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