| 18 |
On Random Sampling over Joins |
1999 |
SIGMOD |
0.00092569117 |
| 28 |
Accurate Estimation Of The Number Of Tuples Satisfying A Condition |
1984 |
SIGMOD |
0.00080571183 |
| 203 |
Learned Cardinalities: Estimating Correlated Joins with Deep Learning |
2019 |
CIDR |
0.00034868567 |
| 212 |
Join Synopses for Approximate Query Answering |
1999 |
SIGMOD |
0.00033997204 |
| 216 |
Ripple Joins for Online Aggregation |
1999 |
SIGMOD |
0.00033560137 |
| 416 |
Approximate Query Processing Using Wavelets |
2000 |
VLDB |
0.00023773968 |
| 510 |
An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning |
2019 |
SIGMOD |
0.00021420477 |
| 606 |
DeepDB: Learn from Data, not from Queries! |
2020 |
VLDB |
0.00019251186 |
| 736 |
Congressional Samples for Approximate Answering of Group-By Queries |
2000 |
SIGMOD |
0.00017414831 |
| 779 |
QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning |
2019 |
VLDB |
0.00016719473 |
| 804 |
An End-to-End Learning-based Cost Estimator |
2020 |
VLDB |
0.0001643674 |
| 941 |
Wander Join: Online Aggregation via Random Walks |
2016 |
SIGMOD |
0.00015147831 |
| 960 |
Aqua: A Fast Decision Support System Using Approximate Query Answers |
1999 |
VLDB |
0.00015031055 |
| 1,161 |
VerdictDB: Universalizing Approximate Query Processing |
2018 |
SIGMOD |
0.00013579831 |
| 1,320 |
Quickr: Lazily Approximating Complex AdHoc Queries in BigData Clusters |
2016 |
SIGMOD |
0.00012606067 |
| 1,372 |
Random Sampling over Joins Revisited |
2018 |
SIGMOD |
0.0001233325 |
| 1,699 |
Are We Ready For Learned Cardinality Estimation? |
2021 |
VLDB |
0.00010848882 |
| 2,126 |
IDEBench: A Benchmark for Interactive Data Exploration |
2020 |
SIGMOD |
9.4814404e-05 |
| 2,254 |
Two-Level Sampling for Join Size Estimation |
2017 |
SIGMOD |
9.1871115e-05 |
| 2,494 |
DBEst: Revisiting Approximate Query Processing Engines with Machine Learning Models |
2019 |
SIGMOD |
8.6457436e-05 |
| 2,583 |
Sample + Seek: Approximating Aggregates with Distribution Precision Guarantee |
2016 |
SIGMOD |
8.4973431e-05 |
| 3,335 |
SnappyData: A Unified Cluster for Streaming, Transactions, and Interactive Analytics |
2017 |
CIDR |
7.2023806e-05 |
| 3,455 |
Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation |
2022 |
VLDB |
7.0760196e-05 |
| 3,841 |
I've Seen "Enough": Incrementally Improving Visualizations to Support Rapid Decision Making |
2017 |
VLDB |
6.7090738e-05 |
| 3,924 |
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation |
2021 |
SIGMOD |
6.6227223e-05 |
| 3,944 |
AQP++: Connecting Approximate Query Processing With Aggregate Precomputation for Interactive Analytics |
2018 |
SIGMOD |
6.6056349e-05 |
| 3,992 |
FactorJoin: A New Cardinality Estimation Framework for Join Queries |
2023 |
SIGMOD |
6.5519369e-05 |
| 5,477 |
Learned Cardinality Estimation for Similarity Queries |
2021 |
SIGMOD |
5.4856699e-05 |
| 5,799 |
Learned Approximate Query Processing: Make it Light, Accurate and Fast |
2021 |
CIDR |
5.3219666e-05 |
| 5,867 |
ABS: a System for Scalable Approximate Queries with Accuracy Guarantees |
2014 |
SIGMOD |
5.2933639e-05 |
| 7,644 |
Selectivity Estimation on Streaming Spatio-Textual Data Using Local Correlations |
2015 |
VLDB |
4.6853638e-05 |
| 7,915 |
Efficient Approximate Algorithms for Empirical Entropy and Mutual Information |
2021 |
SIGMOD |
4.6135329e-05 |
| 8,383 |
Consistent and Flexible Selectivity Estimation for High-Dimensional Data |
2021 |
SIGMOD |
4.5261239e-05 |
| 8,712 |
Data Driven Approximation with Bounded Resources |
2017 |
VLDB |
4.4578168e-05 |
| 9,759 |
Efficient Insights Discovery through Conditional Generative Model based Query Approximation |
2022 |
SIGMOD |
4.2852133e-05 |
| 9,923 |
On Saving Outliers for Better Clustering over Noisy Data |
2021 |
SIGMOD |
4.2503475e-05 |