Accelerating Complex Analytics using Speculation
Summary: Speculative execution for inter-dependent analytical query pipelines: use AQP to predict intermediate results and a streaming-join operator to validate speculations. On misprediction, apply incremental repair instead of discarding work, increasing task parallelism and speedups with query complexity (TPC‑DS). (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Panagiotis Sioulas (EPFL)
- 2. Viktor Sanca (EPFL)
- 3. Ioannis Mytilinis (EPFL)
- 4. Anastasia Ailamaki (EPFL; RAW Labs)
BibTeX Citation
@inproceedings{sioulas_cidr21,
address = {Amsterdam, Netherlands},
series = {{CIDR} '21},
title = {{Accelerating Complex Analytics using Speculation}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Sioulas, Panagiotis and Sanca, Viktor and Mytilinis, Ioannis and Ailamaki, Anastasia},
year = {2021}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,161 | LAQy: Efficient and Reusable Query Approximations via Lazy Sampling | 2023 | SIGMOD | 5.4752972e-05 |
| 8,674 | Boosting Efficiency of External Pipelines by Blurring Application Boundaries | 2022 | CIDR | 5.3869233e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 18 of 18 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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