Update NDP: On Offloading Modifications to Smart Storage with Transactional Guarantees in Near-Data Processing DBMS

The performance and scalability of modern data-intensive systems processing large datasets are limited by unnecessary data movement. Even though near-data processing (NDP) can provably reduce data transfers and increase performance, at present, NDP is utilized primarily in read-only settings. Near-data execution of data-intensive modification operations is currently infeasible due to the lack of transactional consistency and the absence of practicable low-latency synchronization mechanisms between the host database engine and the NDP-engine on smart storage. In this article, we introduce update NDP as an approach to offloading modifications to computational storage with transactional guarantees in an NDP database system called neoDBMS . To ensure consistency, we introduce a low-latency shared lock table between the host and computational storage, based on novel cache-coherent interconnects . We also introduce a novel locking protocol that seamlessly integrates the shared lock table within the lock manager of the host NDP-engine. To handle failure recovery, while preserving high and robust performance, we introduce novel extended locking and logging mechanisms that allow the host and computational storage to perform useful work during log-movement. Our evaluation indicates that in-storage modifications in neoDBMS in mixed workload settings are ≥ 6.52× faster than host-only executions and exhibit robust performance due to lower data movement and better resource utilization.