Fast Copy-On-Write within Apache Parquet for Data Lakehouse ACID Upserts

摘要

With the evolution of storage table formats Apache Hudi®, Apache Iceberg®, and Delta Lake™, more and more companies are building up their lakehouse on top of these formats for many use cases, like incremental ingestion. But the speed of upserts sometimes is still a problem when the data volumes go up.

In storage tables, Apache Parquet is used as the main file format. In this article, we will discuss how we built a row-level secondary index and the innovations we introduced in Apache Parquet to speed up the upsert data inside a Parquet file. We will also demonstrate benchmarking results that show much faster speeds than traditional copy-on-write in Delta Lake and Hudi.

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