Cover
Template
1.
DBMS Workload Modeling & Machine Provisioning
1.1.
ICAC'11 - Modeling Workloads using Gaussian Process
1.2.
SIGMOD'18 - P-Store
2.
DBMS Data Partitioning
3.
DBMS Query Processing
4.
DBMS Scalability
4.1.
VLDB'19 - Star
4.2.
TKDE'20 - Hihooi
5.
Deterministic DBMS
5.1.
VLDB'14 - Advantages and Disadvantages of Deterministic DBMS
5.2.
VLDB'20 - Aria
5.3.
SIGMOD'22 - Snapper
6.
DBMS + AI
6.1.
SIGMOD'17 - OtterTune
6.2.
CIDR'19 - Query Optimizer through DL
6.3.
TKDE'20 - Database Meets AI: A Survey
6.4.
SIGMOD'21 - MB2
6.5.
SIGMOD'21 - Scalable Multi-Query Execution using Reinforcement Learning
6.6.
VLDB'21 - CGPTuner
6.7.
CIDR'22 - Zero-Shot Learning on DBMS
6.8.
SIGMOD'22 - Balsa
6.9.
SIGMOD'22 - TScout
7.
DBMS Experiments
7.1.
VLDB'22 - A Study of Database Performance Sensitivity to Experiment Settings
8.
Reinforcement Learning to Rank
8.1.
WWW'20 - RLIRank
Light (default)
Rust
Coal
Navy
Ayu
Paper Notes
DBMS Scalability
VLDB'19 - STAR: Scaling Transactions through Asymmetric Replication
TKDE'20 - Hihooi: A Database Replication Middleware forScaling Transactional Databases Consistently