Non-Volatile Memory (NVM) technologies exhibit 4X the read access latency of conventional DRAM. When the working set does not fit in the processor cache, this latency gap between DRAM and NVM leads to more than 2X runtime increase for queries dominated by latency-bound operations such as index joins and tuple reconstruction. We explain how to easily hide NVM latency by interleaving the execution of parallel work in index joins and tuple reconstruction using coroutines. Our evaluation shows that interleaving applied to the non-trivial implementations of these two operations in a production-grade codebase accelerates end-to-end query runtimes on both NVM and DRAM by up to 1.7X and 2.6X respectively, thereby reducing the performance difference between DRAM and NVM by more than 60%.

Index join performance is determined by the efficiency of the lookup operation on the involved index. Although database indexes are highly optimized to leverage processor caches, main memory accesses inevitably increase lookup runtime when the index outsizes the last-level cache; hence, index join performance drops. Still, robust index join performance becomes possible with instruction stream interleaving : given a group of lookups, we can hide cache misses in one lookup with instructions from other lookups by switching among their respective instruction streams upon a cache miss. In this paper, we propose interleaving with coroutines for any type of index join. We showcase our proposal on SAP HANA by implementing binary search and CSB + -tree traversal for an instance of index join related to dictionary compression. Coroutine implementations not only perform similarly to prior interleaving techniques, but also resemble the original code closely, while supporting both interleaved and non-interleaved execution. Thus, we claim that coroutines make interleaving practical for use in real DBMS codebases.