Stochastic Database Cracking: Towards Robust Adaptive Indexing in Main-Memory Column-Stores
Summary: Introduces stochastic cracking, an adaptive indexing scheme for main-memory column stores that randomizes reorganization decisions rather than blindly cracking every query range. This avoids pathological workloads and delivers robust performance under changing, unknown query patterns. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Felix Halim (National University of Singapore)
- 2. Stratos Idreos (Centrum Wiskunde & Informatica)
- 3. Panagiotis Karras (Rutgers University)
- 4. Roland H. C. Yap (National University of Singapore)
BibTeX Citation
@article{halim_vldb12,
title = {{Stochastic Database Cracking: Towards Robust Adaptive Indexing in Main-Memory Column-Stores}},
author = {Halim, Felix and Idreos, Stratos and Karras, Panagiotis and Yap, Roland H. C.},
journal = {PVLDB},
series = {{VLDB} '12},
volume = {5},
number = {6},
pages = {502--513},
doi = {10.14778/2168651.2168652},
url = {https://doi.org/10.14778/2168651.2168652},
year = {2012}
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