| 71 |
How Good Are Query Optimizers, Really? |
2016 |
VLDB |
0.00059038975 |
| 204 |
Learned Cardinalities: Estimating Correlated Joins with Deep Learning |
2019 |
CIDR |
0.00034784455 |
| 342 |
EmptyHeaded: A Relational Engine for Graph Processing |
2016 |
SIGMOD |
0.00026795977 |
| 461 |
Graphs-at-a-time: Query Language and Access Methods for Graph Databases |
2008 |
SIGMOD |
0.00022499343 |
| 608 |
DeepDB: Learn from Data, not from Queries! |
2020 |
VLDB |
0.00019235898 |
| 612 |
Taming Verification Hardness: An Efficient Algorithm for Testing Subgraph Isomorphism |
2008 |
VLDB |
0.0001920234 |
| 758 |
Deep Unsupervised Cardinality Estimation |
2020 |
VLDB |
0.0001706608 |
| 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 |
| 1,180 |
Efficient Subgraph Matching by Postponing Cartesian Products |
2016 |
SIGMOD |
0.00013456907 |
| 1,193 |
Join Size Estimation Subject to Filter Conditions |
2015 |
VLDB |
0.00013414989 |
| 1,254 |
Selectivity Estimation for Range Predicates using Lightweight Models |
2019 |
VLDB |
0.00013027411 |
| 1,328 |
Hypertree Decompositions: Questions and Answers |
2016 |
PODS |
0.00012565612 |
| 1,333 |
Optimizing Subgraph Queries by Combining Binary and Worst-Case Optimal Joins |
2019 |
VLDB |
0.00012523806 |
| 1,369 |
Random Sampling over Joins Revisited |
2018 |
SIGMOD |
0.00012339777 |
| 1,442 |
What do Shannon-type Inequalities, Submodular Width, and Disjunctive Datalog have to do with one another? |
2017 |
PODS |
0.00011956109 |
| 1,474 |
Homogeneous Network Embedding for Massive Graphs via Reweighted Personalized PageRank |
2020 |
VLDB |
0.00011825229 |
| 1,561 |
Efficient Subgraph Matching: Harmonizing Dynamic Programming, Adaptive Matching Order, and Failing Set Together |
2019 |
SIGMOD |
0.00011358946 |
| 1,775 |
CECI: Compact Embedding Cluster Index for Scalable Subgraph Matching |
2019 |
SIGMOD |
0.00010602927 |
| 1,924 |
In-Memory Subgraph Matching: An In-depth Study |
2020 |
SIGMOD |
0.00010077055 |
| 1,953 |
Distributed Evaluation of Subgraph Queries Using Worst-case Optimal Low-Memory Dataflows |
2018 |
VLDB |
9.9665955e-05 |
| 2,142 |
Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities |
2019 |
SIGMOD |
9.4507296e-05 |
| 2,364 |
Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries |
2020 |
SIGMOD |
8.9554751e-05 |
| 2,501 |
DBEst: Revisiting Approximate Query Processing Engines with Machine Learning Models |
2019 |
SIGMOD |
8.6453446e-05 |
| 2,969 |
Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models |
2017 |
VLDB |
7.7974762e-05 |
| 3,142 |
Active Learning for ML Enhanced Database Systems |
2020 |
SIGMOD |
7.4815444e-05 |
| 3,410 |
Motivo: fast motif counting via succinct color coding and adaptive sampling |
2019 |
VLDB |
7.1253867e-05 |
| 3,646 |
G-CARE: A Framework for Performance Benchmarking of Cardinality Estimation Techniques for Subgraph Matching |
2020 |
SIGMOD |
6.8853079e-05 |