| 66 |
Spark SQL: Relational Data Processing in Spark |
2015 |
SIGMOD |
0.00061639801 |
| 70 |
Hive - A Warehousing Solution Over a Map-Reduce Framework |
2009 |
VLDB |
0.00059533166 |
| 183 |
Automatic Database Management System Tuning Through Large-scale Machine Learning |
2017 |
SIGMOD |
0.00036721403 |
| 514 |
An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning |
2019 |
SIGMOD |
0.0002124895 |
| 542 |
Shark: SQL and Rich Analytics at Scale |
2013 |
SIGMOD |
0.00020595648 |
| 780 |
Building a High-Level Dataflow System on top of Map-Reduce: The Pig Experience |
2009 |
VLDB |
0.00016775082 |
| 782 |
QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning |
2019 |
VLDB |
0.00016729063 |
| 1,647 |
Parametric Query Optimization for Linear and Piecewise Linear Cost Functions |
2002 |
VLDB |
0.00011033757 |
| 1,684 |
Fuxi: a Fault-Tolerant Resource Management and Job Scheduling System at Internet Scale |
2014 |
VLDB |
0.0001091857 |
| 1,902 |
Black or White? How to Develop an AutoTuner for Memory-based Analytics |
2020 |
SIGMOD |
0.00010157713 |
| 2,364 |
Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries |
2020 |
SIGMOD |
8.9554751e-05 |
| 2,568 |
Towards Cost-Optimal Query Processing in the Cloud |
2021 |
VLDB |
8.5239227e-05 |
| 2,659 |
Multi-Objective Parametric Query Optimization |
2015 |
VLDB |
8.3604734e-05 |
| 2,691 |
Greenplum: A Hybrid Database for Transactional and Analytical Workloads |
2021 |
SIGMOD |
8.2909126e-05 |
| 2,762 |
FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation |
2021 |
VLDB |
8.1585394e-05 |
| 2,783 |
Flow-Loss: Learning Cardinality Estimates That Matter |
2021 |
VLDB |
8.1293383e-05 |
| 3,216 |
WiSeDB: A Learning-based Workload Management Advisor for Cloud Databases |
2016 |
VLDB |
7.3601267e-05 |
| 3,499 |
Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation |
2021 |
VLDB |
7.0376445e-05 |
| 3,522 |
ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases |
2021 |
SIGMOD |
7.0096727e-05 |
| 3,924 |
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation |
2021 |
SIGMOD |
6.6271553e-05 |
| 4,543 |
FACE: A Normalizing Flow based Cardinality Estimator |
2022 |
VLDB |
6.1011198e-05 |
| 4,700 |
Schedule Optimization for Data Processing Flows on the Cloud |
2011 |
SIGMOD |
5.9882572e-05 |
| 4,842 |
Towards Dynamic and Safe Configuration Tuning for Cloud Databases |
2022 |
SIGMOD |
5.8826802e-05 |
| 4,874 |
Approximation Schemes for Many-Objective Query Optimization |
2014 |
SIGMOD |
5.8594632e-05 |
| 4,913 |
UDO: Universal Database Optimization using Reinforcement Learning |
2021 |
VLDB |
5.8316231e-05 |
| 5,075 |
An Incremental Anytime Algorithm for Multi-Objective Query Optimization |
2015 |
SIGMOD |
5.7172118e-05 |
| 5,368 |
Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing |
2022 |
VLDB |
5.5457532e-05 |
| 5,469 |
Learned Cardinality Estimation for Similarity Queries |
2021 |
SIGMOD |
5.4898192e-05 |
| 5,531 |
Presto: A Decade of SQL Analytics at Meta |
2023 |
SIGMOD |
5.4549499e-05 |
| 5,634 |
Intelligent Scaling in Amazon Redshift |
2024 |
SIGMOD |
5.4000904e-05 |
| 5,833 |
LOCAT: Low-Overhead Online Configuration Auto-Tuning of Spark SQL Applications |
2022 |
SIGMOD |
5.3106182e-05 |
| 6,368 |
Pre-training Summarization Models of Structured Datasets for Cardinality Estimation |
2022 |
VLDB |
5.0937722e-05 |
| 6,871 |
Towards General and Efficient Online Tuning for Spark |
2023 |
VLDB |
4.8997004e-05 |
| 7,358 |
Weighted Distinct Sampling: Cardinality Estimation for SPJ Queries |
2021 |
SIGMOD |
4.7529363e-05 |
| 8,576 |
PostCENN: PostgreSQL with Machine Learning Models for Cardinality Estimation |
2021 |
VLDB |
4.4927989e-05 |
| 9,066 |
Tempo: Robust and Self-Tuning Resource Management in Multi-tenant Parallel Databases |
2016 |
VLDB |
4.4035481e-05 |
| 9,546 |
Trident: Task Scheduling over Tiered Storage Systems in Big Data Platforms |
2021 |
VLDB |
4.3259935e-05 |
| 9,547 |
Optimistic Recovery for Iterative Dataflows in Action |
2015 |
SIGMOD |
4.3259935e-05 |
| 9,736 |
UDAO: A Next-Generation Unified Data Analytics Optimizer |
2019 |
VLDB |
4.2942813e-05 |