Fusion: An Analytics Object Store Optimized for Query Pushdown
Jianan Lu, Ashwini Raina, Asaf Cidon, Michael J. Freedman · 2025
The prevalence of disaggregated storage in public clouds has led to increased latency in modern OLAP cloud databases, particularly when handling ad-hoc and highly-selective queries on large objects. To address this, cloud databases have adopted computation pushdown, executing query predicates closer to the storage layer. However, existing pushdown solutions are inefficient in erasure-coded storage. Cloud storage employs erasure coding that partitions analytics file objects into fixed-sized blocks and distributes them across storage nodes. Consequently, when a specific part of the object is queried, the storage system must reassemble the object across nodes, incurring significant network latency.