Tiered-Indexing: Optimizing Access Methods for Skew

Abstract Real-world DBMS workloads invariably exhibit skewed access patterns, where a small number of "hot" records are accessed much more frequently than the remaining "cold" records. Page-oriented data structures, such as B+trees, dynamic hash tables, heap files, and LSM-tree, are sub-optimal in terms of memory utilization under skewed access conditions. Hot records might be co-located with cold ones on pages in the data structure. Caching those lukewarm pages in the buffer pool lowers memory utilization due to the mismatch of caching granularity (page) and access granularity (record), leading to sub-optimal performance. Recently, the 2-Tree approach was proposed to improve caching efficiency for B+trees using record-level migration. In this paper, we generalize the 2-Tree approach to Tiered-Indexing that can be applied to common buffer-managed data structures to efficiently handle skew using record migration. Using this architecture, we extend hash tables, heap files, and LSM-trees with I/O-efficient record migration. Moreover, we design a general mechanism to ensure data structure consistency for Tiered-Indexing data structures during record migration using optimistic lock coupling. Compared to traditional 1-Tier and state-of-the-art record-caching designs, we observe significant throughput and memory utilization improvement across B+tree, hash table, heap file, and LSM-tree under skewed workloads.