| 1,204 |
VerdictDB: Universalizing Approximate Query Processing |
2018 |
SIGMOD |
0.00013319541 |
| 1,369 |
Random Sampling over Joins Revisited |
2018 |
SIGMOD |
0.00012339777 |
| 1,574 |
Approximate Query Processing: No Silver Bullet |
2017 |
SIGMOD |
0.00011287495 |
| 2,083 |
Towards a Learning Optimizer for Shared Clouds |
2019 |
VLDB |
9.5834572e-05 |
| 2,142 |
Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities |
2019 |
SIGMOD |
9.4507296e-05 |
| 2,254 |
Two-Level Sampling for Join Size Estimation |
2017 |
SIGMOD |
9.1897043e-05 |
| 2,501 |
DBEst: Revisiting Approximate Query Processing Engines with Machine Learning Models |
2019 |
SIGMOD |
8.6453446e-05 |
| 2,588 |
Database Learning: Toward a Database that Becomes Smarter Every Time |
2017 |
SIGMOD |
8.4909562e-05 |
| 3,944 |
AQP++: Connecting Approximate Query Processing With Aggregate Precomputation for Interactive Analytics |
2018 |
SIGMOD |
6.6078243e-05 |
| 5,150 |
Efficient Join Synopsis Maintenance for Data Warehouse |
2020 |
SIGMOD |
5.6626586e-05 |
| 5,806 |
BlinkML: Efficient Maximum Likelihood Estimation with Probabilistic Guarantees |
2019 |
SIGMOD |
5.3200643e-05 |
| 5,909 |
At-the-time and Back-in-time Persistent Sketches |
2021 |
SIGMOD |
5.2769377e-05 |
| 6,230 |
Learned Approximate Query Processing: Make it Light, Accurate and Fast |
2021 |
CIDR |
5.145989e-05 |
| 6,261 |
The Cosmos Big Data Platform at Microsoft: Over a Decade of Progress and a Decade to Look Forward |
2021 |
VLDB |
5.1350714e-05 |
| 6,493 |
Joins on Samples: A Theoretical Guide for Practitioners |
2020 |
VLDB |
5.0424713e-05 |
| 6,740 |
Combining Aggregation and Sampling (Nearly) Optimally for Approximate Query Processing |
2021 |
SIGMOD |
4.944395e-05 |
| 7,339 |
SpareLLM: Automatically Selecting Task-Specific Minimum-Cost Large Language Models under Equivalence Constraint |
2025 |
SIGMOD |
4.7579469e-05 |
| 7,358 |
Weighted Distinct Sampling: Cardinality Estimation for SPJ Queries |
2021 |
SIGMOD |
4.7529363e-05 |
| 7,714 |
Identifying Insufficient Data Coverage in Databases with Multiple Relations |
2020 |
VLDB |
4.6700455e-05 |
| 7,872 |
Probabilistic Database Summarization for Interactive Data Exploration |
2017 |
VLDB |
4.6307184e-05 |
| 8,080 |
Biathlon: Harnessing Model Resilience for Accelerating ML Inference Pipelines |
2024 |
VLDB |
4.5911668e-05 |
| 8,138 |
Fast and Reliable Missing Data Contingency Analysis with Predicate-Constraints |
2020 |
SIGMOD |
4.5771031e-05 |
| 8,240 |
Experiences with Approximating Queries in Microsoft’s Production Big-Data Clusters |
2019 |
VLDB |
4.5522563e-05 |
| 8,393 |
LAQy: Efficient and Reusable Query Approximations via Lazy Sampling |
2023 |
SIGMOD |
4.5280102e-05 |
| 8,432 |
SPRINTER: A Fast n-ary Join Query Processing Method for Complex OLAP Queries |
2020 |
SIGMOD |
4.5153924e-05 |
| 8,643 |
One Size Does Not Fit All: A Bandit-Based Sampler Combination Framework with Theoretical Guarantees |
2022 |
SIGMOD |
4.4777916e-05 |
| 8,680 |
A Practical Approach to Groupjoin and Nested Aggregates |
2021 |
VLDB |
4.4694927e-05 |
| 8,715 |
Data Driven Approximation with Bounded Resources |
2017 |
VLDB |
4.4619052e-05 |
| 9,118 |
Towards Observability for Production Machine Learning Pipelines |
2022 |
VLDB |
4.3928288e-05 |
| 9,384 |
Sapprox: Enabling Efficient and Accurate Approximations on Sub-datasets with Distribution-aware Online Sampling |
2017 |
VLDB |
4.3456129e-05 |
| 9,621 |
ShadowAQP: Efficient Approximate Group-by and Join Query via Attribute-oriented Sample Size Allocation and Data Generation |
2023 |
VLDB |
4.3167167e-05 |
| 9,652 |
Secure Sampling for Approximate Multi-party Query Processing |
2023 |
SIGMOD |
4.3109001e-05 |
| 9,696 |
The Data Interaction Game |
2018 |
SIGMOD |
4.3023337e-05 |
| 9,758 |
Practical Dynamic Extension for Sampling Indexes |
2023 |
SIGMOD |
4.2879116e-05 |
| 9,949 |
AB-tree: Index for Concurrent Random Sampling and Updates |
2022 |
VLDB |
4.2421586e-05 |
| 10,254 |
Secure Multi-Party Sampling over Joins |
2026 |
VLDB |
4.1945683e-05 |
| 10,337 |
Efficient Approximate Query Processing with Block Sampling |
2025 |
CIDR |
4.1945683e-05 |
| 10,481 |
FAAQP: Fast and Accurate Approximate Query Processing based on Bitmap-augmented Sum-Product Network |
2025 |
SIGMOD |
4.1945683e-05 |
| 10,497 |
PilotDB: Database-Agnostic Online Approximate Query Processing with A Priori Error Guarantees |
2025 |
SIGMOD |
4.1945683e-05 |
| 10,565 |
Holistic query Approximation via RL Modeling |
2025 |
VLDB |
4.1945683e-05 |
| 10,941 |
PECJ: Stream Window Join on Disorder Data Streams with Proactive Error Compensation |
2024 |
SIGMOD |
4.1945683e-05 |
| 10,981 |
Enabling Adaptive Sampling for Intra-Window Join: Simultaneously Optimizing Quantity and Quality |
2024 |
SIGMOD |
4.1945683e-05 |
| 11,194 |
A Step Toward Deep Online Aggregation |
2023 |
SIGMOD |
4.1945683e-05 |
| 11,285 |
Approximate Queries over Concurrent Updates |
2023 |
VLDB |
4.1945683e-05 |
| 11,427 |
Accelerating Complex Analytics using Speculation |
2021 |
CIDR |
4.1945683e-05 |
| 11,502 |
In the Land of Data Streams where Synopses are Missing, One Framework to Bring Them All |
2021 |
VLDB |
4.1945683e-05 |
| 11,539 |
FlashP: An Analytical Pipeline for Real-time Forecasting of Time-Series Relational Data |
2021 |
VLDB |
4.1945683e-05 |
| 11,552 |
BitGourmet: Deterministic Approximation via Optimized Bit Selection |
2020 |
CIDR |
4.1945683e-05 |
| 11,585 |
Demonstration of BitGourmet: Data Analysis via Deterministic Approximation |
2020 |
SIGMOD |
4.1945683e-05 |
| 11,650 |
Query-Driven Learning for Next Generation Predictive Modeling & Analytics |
2019 |
SIGMOD |
4.1945683e-05 |