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

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. Cloud Scale Log Threats → https://bit.ly/2TWj6a4 Watch more: Next '19 Data Analytics Sessions here → https://bit.ly/Next19DataAnalytics Next ‘19 All Sessions playlist → https://bit.ly/Next19AllSessions Subscribe to the G Suite Channel → https://bit.ly/G-Suite1 Speaker(s): Sergei Sokolenko, Christopher Crosbie, Ravi Upreti Session ID: DA203 product:BigQuery,Cloud Pub/Sub,Cloud Dataflow http://bit.ly/2Z4ep1W G Suite April 10, 2019 at 09:05PM