Presented By O’Reilly and Cloudera
Make Data Work
21–22 May 2018: Training
22–24 May 2018: Tutorials & Conference
London, UK
Eugene Kirpichov

Eugene Kirpichov
Staff Software Engineer, Google

Eugene Kirpichov is a staff software engineer on the Cloud Dataflow team at Google, where he works on the Apache Beam programming model and APIs. Previously, Eugene worked on Cloud Dataflow’s autoscaling and straggler elimination techniques. He is interested in programming language theory, data visualization, and machine learning.

Sessions

14:55–15:35 Thursday, 24 May 2018
Radically modular data ingestion APIs in Apache Beam
Big data and data science in the cloud, Data engineering and architecture, Streaming systems and real-time applications
 Location: Capital Suite 8/9 Level: Advanced
Secondary topics:  Data Integration and Data Pipelines sessions
Eugene Kirpichov (Google)
Average rating: ****.
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Apache Beam offers users a novel programming model in which the classic batch-streaming dichotomy is erased and ships with a rich set of I/O connectors to popular storage systems. Eugene Kirpichov explains why Beam has made these connectors flexible and modular—a key component of which is Splittable DoFn, a novel programming model primitive that unifies data ingestion between batch and streaming. Read more.