This article presents ByteDance's evolution of data lake indexing built on Apache Hudi, detailing traditional update challenges, Hudi's index mechanisms, the introduction of bucket and extensible hash indexes, query optimizations, and upcoming multi‑modal and range index innovations.
Introducing Hudi’s Bucket Index, a hash‑based indexing module that replaces Bloom Filter and HBase indexes, dramatically reducing file reads and writes, improving upsert performance, enabling efficient bucket pruning and joins, and offering practical guidance on design, implementation, and future extensions.
This article explains the background, design, and practical benefits of Hudi's Bucket Index—a hash‑based indexing mechanism that reduces unnecessary file reads and writes, improves upsert speed on terabyte‑scale datasets, and enables query optimizations such as bucket pruning and bucket join.
This article presents ByteDance’s ByteLake, a real‑time data lake platform built on Apache Hudi, covering Hudi fundamentals, ByteLake’s use cases, the platform’s architectural optimizations, new features such as a commit‑based metastore and bucket indexing, and future roadmap plans.
