Video description
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.
O'Reilly Case Studies explore how organizations have overcome common challenges in business and technology through a series of one-hour interactive events. You’ll engage in a live conversation with experts, sharing your questions and challenges while hearing their unique perspectives, insights, and lessons learned.
Product information
- Title: Case Study: How Pinterest Built a Stream Processing Platform with Apache Flink
- Author(s):
- Release date: January 2022
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 0636920672357
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