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SIGMOD2023顶会

BtrBlocks: Efficient Columnar Compression for Data Lakes

Maximilian Kuschewski, David Sauerwein, Adnan Alhomssi, Viktor Leis

2023年份
47被引次数
27顶会引用

摘要

Analytics is moving to the cloud and data is moving into data lakes. These reside on object storage services like S3 and enable seamless data sharing and system interoperability. To support this, many systems build on open storage formats like Apache Parquet. However, these formats are not optimized for remotely-accessed data lakes and today's high-throughput networks. Inefficient decompression makes scans CPU-bound and thus increases query time and cost. With this work we present BtrBlocks, an open columnar storage format designed for data lakes. BtrBlocks uses a set of lightweight encoding schemes, achieving fast and efficient decompression and high compression ratios.

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