Data Processing in Google Cloud: Hadoop, Spark, and Dataflow (Cloud Next '19)

Опубликовано 11 апреля 2019, 1:07

Google Cloud is committed to making your infrastructure as easy-to-use as possible. Naturally, ""easy"" means different things to different people and organizations. In data processing, sometimes that means migrating your existing Hadoop and Spark environment to Cloud Dataproc, which delivers a familiar feel. For others, easy will mean putting Cloud Dataflow's serverless, unified batch and stream data processing into production. In this session, we'll explore the ins and ours of making this decision, with real-world experience form Qubit, who has used both Dataproc and Dataflow in production.

Big data analytics → bit.ly/2U1EY4g

Watch more:
Next '19 Data Analytics Sessions here → bit.ly/Next19DataAnalytics
Next ‘19 All Sessions playlist → bit.ly/Next19AllSessions

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Speaker(s): Sergei Sokolenko, Christopher Crosbie, Ravi Upreti


Session ID: DA203
product:Cloud Dataflow,Cloud Dataproc,BigQuery; fullname:Christopher Crosbie,Sergei Sokolenko; event: Google Cloud Next 2019; re_ty: Publish; product: Cloud - General; fullname: Sergei Sokolenko, Christopher Crosbie, Ravi Upreti;