How Pinterest Uses Apache Spark
8 engineering articles about Apache Spark from Pinterest's engineering team
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The article discusses Pinterest's transition to a next-generation database ingestion framework designed to address the limitations of legacy systems.
Pinterest Engineering
10 min read
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PinLanding is a multimodal AI pipeline developed by Pinterest to generate shopping collections from billions of products.
Pinterest Engineering
8 min read
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The article discusses how Pinterest enhances its machine learning feature iterations through an effective backfill process.
Pinterest Engineering
14 min read
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The article discusses the transition from Apache Hadoop YARN to Apache YuniKorn for resource management in Pinterest's batch processing platform, Monarch, now rebranded as Moka.
Pinterest Engineering
10 min read
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This article discusses the implementation of Ray Batch Inference at Pinterest, highlighting its advantages over previous solutions like Apache Spark and Torch Dataloader.
Pinterest Engineering
11 min read
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The article discusses how Pinterest improved its machine learning (ML) dataset iteration speed using Ray, an open-source framework for scaling AI and ML workloads.
Pinterest Engineering
9 min read
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The article discusses how Pinterest utilizes Apache Spark SQL for interactive querying, detailing the architecture, challenges faced, and solutions implemented to enhance user experience.
Pinterest Engineering
18 min read
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The article discusses the implementation of a real-time metrics dashboard for monitoring A/B experiments at Pinterest.
Pinterest Engineering
5 min read
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