| 18 |
On Random Sampling over Joins |
1999 |
SIGMOD |
0.00092385438 |
| 28 |
Accurate Estimation Of The Number Of Tuples Satisfying A Condition |
1984 |
SIGMOD |
0.00080435857 |
| 204 |
Learned Cardinalities: Estimating Correlated Joins with Deep Learning |
2019 |
CIDR |
0.00034784455 |
| 211 |
Join Synopses for Approximate Query Answering |
1999 |
SIGMOD |
0.00033981214 |
| 217 |
Ripple Joins for Online Aggregation |
1999 |
SIGMOD |
0.00033536712 |
| 405 |
Approximate Query Processing Using Wavelets |
2000 |
VLDB |
0.00024057494 |
| 514 |
An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning |
2019 |
SIGMOD |
0.0002124895 |
| 608 |
DeepDB: Learn from Data, not from Queries! |
2020 |
VLDB |
0.00019235898 |
| 739 |
Congressional Samples for Approximate Answering of Group-By Queries |
2000 |
SIGMOD |
0.00017401518 |
| 782 |
QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning |
2019 |
VLDB |
0.00016729063 |
| 806 |
An End-to-End Learning-based Cost Estimator |
2020 |
VLDB |
0.00016434274 |
| 943 |
Wander Join: Online Aggregation via Random Walks |
2016 |
SIGMOD |
0.00015145883 |
| 967 |
Aqua: A Fast Decision Support System Using Approximate Query Answers |
1999 |
VLDB |
0.00014959939 |
| 1,204 |
VerdictDB: Universalizing Approximate Query Processing |
2018 |
SIGMOD |
0.00013319541 |
| 1,323 |
Quickr: Lazily Approximating Complex AdHoc Queries in BigData Clusters |
2016 |
SIGMOD |
0.00012601997 |
| 1,369 |
Random Sampling over Joins Revisited |
2018 |
SIGMOD |
0.00012339777 |
| 1,703 |
Are We Ready For Learned Cardinality Estimation? |
2021 |
VLDB |
0.00010836769 |
| 2,129 |
IDEBench: A Benchmark for Interactive Data Exploration |
2020 |
SIGMOD |
9.480002e-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 |
| 2,580 |
Sample + Seek: Approximating Aggregates with Distribution Precision Guarantee |
2016 |
SIGMOD |
8.5058814e-05 |
| 3,333 |
SnappyData: A Unified Cluster for Streaming, Transactions, and Interactive Analytics |
2017 |
CIDR |
7.2093479e-05 |
| 3,449 |
Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation |
2022 |
VLDB |
7.0824319e-05 |
| 3,835 |
I've Seen "Enough": Incrementally Improving Visualizations to Support Rapid Decision Making |
2017 |
VLDB |
6.7163364e-05 |
| 3,924 |
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation |
2021 |
SIGMOD |
6.6271553e-05 |
| 3,944 |
AQP++: Connecting Approximate Query Processing With Aggregate Precomputation for Interactive Analytics |
2018 |
SIGMOD |
6.6078243e-05 |
| 3,990 |
FactorJoin: A New Cardinality Estimation Framework for Join Queries |
2023 |
SIGMOD |
6.5581983e-05 |
| 5,469 |
Learned Cardinality Estimation for Similarity Queries |
2021 |
SIGMOD |
5.4898192e-05 |
| 5,868 |
ABS: a System for Scalable Approximate Queries with Accuracy Guarantees |
2014 |
SIGMOD |
5.2959352e-05 |
| 6,230 |
Learned Approximate Query Processing: Make it Light, Accurate and Fast |
2021 |
CIDR |
5.145989e-05 |
| 7,645 |
Selectivity Estimation on Streaming Spatio-Textual Data Using Local Correlations |
2015 |
VLDB |
4.6896215e-05 |
| 7,914 |
Efficient Approximate Algorithms for Empirical Entropy and Mutual Information |
2021 |
SIGMOD |
4.6179608e-05 |
| 8,384 |
Consistent and Flexible Selectivity Estimation for High-Dimensional Data |
2021 |
SIGMOD |
4.5304673e-05 |
| 8,715 |
Data Driven Approximation with Bounded Resources |
2017 |
VLDB |
4.4619052e-05 |
| 9,757 |
Efficient Insights Discovery through Conditional Generative Model based Query Approximation |
2022 |
SIGMOD |
4.2893233e-05 |
| 9,924 |
On Saving Outliers for Better Clustering over Noisy Data |
2021 |
SIGMOD |
4.2544238e-05 |