期刊
PROCEEDINGS OF THE VLDB ENDOWMENT
卷 11, 期 11, 页码 1702-1714出版社
ASSOC COMPUTING MACHINERY
DOI: 10.14778/3236187.3236216
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Database systems use many pointer-based data structures, including hash tables and B+-trees, which require extensive pointerchasing. Each pointer dereference, e.g., during a hash probe or a B+-tree traversal, can result in a CPU cache miss, stalling the CPU. Recent work has shown that CPU stalls due to main memory accesses are a significant source of overhead, even for cache-conscious data structures, and has proposed techniques to reduce this overhead, by hiding memory-stall latency. In this work, we compare and contrast the state-of-the-art approaches to reduce CPU stalls due to cache misses for pointer-intensive data structures. We present an in-depth experimental evaluation and a detailed analysis using four popular data structures: hash table, binary search, Masstree, and Bw-tree. Our focus is on understanding the practicality of using coroutines to improve throughput of such data structures. The implementation, experiments, and analysis presented in this paper promote a deeper understanding of how to exploit coroutines-based approaches to build highly efficient systems.
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