Kuaishou’s Practices for Large‑Scale Model Data Processing and Storage

This article shares Kuaishou’s real‑time, massive‑scale model data processing pipeline, covering model scenarios, recommendation workflow complexity, large‑scale data storage, streaming joins, feature computation, NVM‑based storage solutions, strong consistency mechanisms, and future outlook for AI recommendation systems.

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Kuaishou’s Practices for Large‑Scale Model Data Processing and Storage

DataFunTalk

Feb 7, 2024 · Big Data

Kuaishou's Practices for Large‑Scale Model Data Processing, Real‑Time Feature Handling, and Storage

This article presents Kuaishou's end‑to‑end engineering solutions for handling massive, real‑time recommendation model data, covering scenario description, complex business pipelines, trillion‑parameter model storage, high‑throughput processing with Flink and NVM, and future directions for cloud‑native scalability.

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Kuaishou's Practices for Large‑Scale Model Data Processing, Real‑Time Feature Handling, and Storage