GoCache: Accelerating Out-Of-Core Graph Queries with Pattern-Driven Caching

Modern graph applications require low-latency query processing, but the increasing scale of graph data forces the use of out-of-core processing. Conventional cache designs perform poorly in this setting, causing severe throughput degradation and low SSD utilization. Our analysis of the LDBC SNB benchmark traces these issues to two root causes: the inefficient handling of warm data and the underutilization of I/O parallelism inherent in graph traversals. This paper presents GoCache, a high-performance userspace cache that accelerates out-of-core graph queries through two key innovations: (1) dSIEVE, a two-layer eviction policy that protects warm data from premature eviction, significantly reducing miss rates; and (2) an intelligent I/O subsystem that exploits inherent parallelism in graph traversals by injecting batched I/O operations into query execution plans, dramatically improving SSD bandwidth utilization and reducing I/O latency. Implemented in 3,900 lines of C++ and integrated with GraphScope, GoCache achieves 37-80% higher throughput than MMAP and 89-118% higher than TriCache, effectively alleviating the I/O bottleneck in large-scale graph processing. We hope the results demonstrates its effectiveness as a deployable, high-performance caching solution for large-scale graph query workloads. We plan to open-source the system upon acceptance.