Sharing Data and Work Across Concurrent Analytical Queries
Summary: Evaluates runtime sharing via Simultaneous Pipelining (SP) and Global Query Plans (GQP), showing their orthogonality and concurrency-dependent benefits. A pull-based SP removes low-concurrency overhead and, combined with GQP, substantially improves high-concurrency analytical workloads. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Iraklis Psaroudakis (EPFL)
- 2. Manos Athanassoulis (EPFL)
- 3. Anastasia Ailamaki (EPFL)
BibTeX Citation
@article{psaroudakis_vldb13,
title = {{Sharing Data and Work Across Concurrent Analytical Queries}},
author = {Psaroudakis, Iraklis and Athanassoulis, Manos and Ailamaki, Anastasia},
journal = {PVLDB},
series = {{VLDB} '13},
volume = {6},
number = {9},
pages = {637--648},
doi = {10.14778/2536360.2536361},
url = {https://doi.org/10.14778/2536360.2536361},
year = {2013}
}
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