Predicting Query Execution time for JIT Compiled Database Engines
Summary: JIT-Prediction: a lightweight analytical cost model for JIT code‑generation DB engines that models memory access and branch misprediction to estimate query execution time. Leverages active learning to minimize training overhead and avoid heavy ML while improving accuracy. (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
Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,101 | Generic Database Cost Models for Hierarchical Memory Systems | 2002 | VLDB | 0.00014070632 |
| 8,096 | Micro-architectural Analysis of OLAP: Limitations and Opportunities | 2020 | VLDB | 4.5860565e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 438 | Query Optimization for Parallel Execution | 1992 | SIGMOD | 0.00023199245 |
| 5,637 | Database Workload Characterization with Query Plan Encoders | 2022 | VLDB | 5.3979505e-05 |
| 8,956 | T3: Accurate and Fast Performance Prediction for Relational Database Systems With Compiled Decision Trees | 2025 | SIGMOD | 4.4214154e-05 |
| 884 | Plan-Structured Deep Neural Network Models for Query Performance Prediction | 2019 | VLDB | 0.00015654004 |
| 6,278 | Uncertainty Aware Query Execution Time Prediction | 2014 | VLDB | 5.1309442e-05 |
| 718 | Performance Prediction for Concurrent Database Workloads | 2011 | SIGMOD | 0.0001763106 |
| 4,376 | Just-in-time compilation for SQL query processing | 2013 | VLDB | 6.2424797e-05 |
| 3,580 | Query Performance Prediction for Concurrent Queries using Graph Embedding | 2020 | VLDB | 6.9500996e-05 |
| 5,473 | Facilitating SQL Query Composition and Analysis | 2020 | SIGMOD | 5.4885366e-05 |
| 4,088 | Towards Predicting Query Execution Time for Concurrent and Dynamic Database Workloads | 2013 | VLDB | 6.4603918e-05 |