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Case Study: How Pinterest Built a Stream Processing Platform with Apache Flink
case study

Case Study: How Pinterest Built a Stream Processing Platform with Apache Flink

by Chen Qin
January 2022
Intermediate
58m
English
O'Reilly Media, Inc.
Closed Captioning available in German, English, Spanish, French, Japanese, Korean, Portuguese (Portugal, Brazil), Chinese (Simplified), Chinese (Traditional)

Overview

Facing rapid growth and competition in its online business, Pinterest had to evolve its data stack from offline-only ETL batch jobs to near-real-time big data applications. But stateful stream processing is a relatively new technology in the big data field, and there are many offerings to choose from, each with its own pros and cons.

Join us for this Case Study with Pinterest tech lead Chen Qin to learn how the company chose Apache Flink as the technology behind its stream processing platform. You’ll see how the platform has enabled critical use cases and a user base that scaled out and evolved along with product innovation—and hear some lessons learned while implementing and growing the platform.

Recorded on January 11, 2022. See the original event page for resources for further learning or watch recordings of other past events.

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Publisher Resources

ISBN: 0636920672371