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Music Recommendations at Scale With Cloud Bigtable (Cloud Next '19)

Peter Sobot
ДолжностьStaff Software Engineer at Spotify
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Google Cloud Next 2019
April 9, 2019, San Francisco, United States
Google Cloud Next 2019
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Peter Sobot
ДолжностьStaff Software Engineer at Spotify

Peter Sobot is a Senior Software Engineer on Spotify's Recommendations Platform team, where he helps build scalable backend, data, and machine learning systems that tailor Spotify to every user's taste. Prior to Spotify, Peter worked at PagerDuty, building software for incident management and alerting on server, desktop, mobile, and wearable platforms. He holds a Bachelor's Degree in Software Engineering from the University of Waterloo and lives in New York City.

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About the talk

Spotify serves personalized music recommendations to hundreds of millions of happy customers worldwide, and powers a lot of this infrastructure with Google Cloud Bigtable. In this talk, we'll go into detail about how Cloud Bigtable allows us to deliver recommendations at scale, roll out experiments quickly, and ingest terabytes every day via Cloud Dataflow. We'll discuss a number of challenges we overcame when designing our recommendations infrastructure on top of Cloud Bigtable, including tips about how to design a good schema, how to avoid latency when ingesting new data, and effective caching strategies to scale to tens of millions of data points per second.

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