¶Abstract

The physical memory layout of a tree-based index structure deteriorates over time as it sustains more updates; such that sequential scans on the physical level become non-sequential, and therefore slower. Packed Memory Arrays (PMAs) prevent this by managing all data in a sequential sparse array. PMAs have been studied mostly theoretically but suffer from practical problems, as we show in this paper. We study and fix these problems, resulting in an improved data structure: the Rewired Memory Array (RMA). We compare RMA with the main previous PMA implementations as well as state-of-the-art tree index structures and show on a wide variety of data and query distributions that RMA can reach competitive update and point lookup performance, while always providing superior scan performance - close to dense column scans.

¶BiBTeX

@INPROCEEDINGS{DeLeo2019,
  author={De Leo, Dean and Boncz, Peter},
  booktitle={2019 IEEE 35th International Conference on Data Engineering (ICDE)}, 
  title={Packed Memory Arrays - Rewired}, 
  year={2019},
  volume={},
  number={},
  pages={830-841},
  keywords={Arrays;Vegetation;Indexes;Complexity theory;Adaptive arrays;Engines;Indexing;Data structure;PMA;Sparse array},
  doi={10.1109/ICDE.2019.00079}}