LiquidCache: Efficient Pushdown Caching for Cloud-Native Data Analytics

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Abstract

We present LiquidCache , a novel pushdown-based disaggregated caching system that evaluates filters on cache servers before transmitting data to compute nodes. Our key observation is that data decoding, not filter evaluation, is the primary bottleneck in existing systems. To address this challenge, we transcode Parquet data into a lightweight “Liquid” format and cache it for efficient filter evaluation. The Liquid format resides solely in the cache layer, requiring no changes to existing deployments and enabling easy adoption of new encodings without breaking compatibility. Through integration with Apache DataFusion and evaluation with ClickBench and TPC-H, we demonstrate that LiquidCache reduces cache CPU time by up to 10× without increasing memory footprint, and reduces network traffic by two orders of magnitudes compared to non-pushdown systems.