Chao Zhang's repositories
AIDB
ai4db and db4ai work
benchmarksql
A TPC-C like test tool
CardinalityEstimationTestbed
CardinalityEstimationTestbed
ceb
Cardinality Estimation Benchmark usage tools
Dike
Dike is a new benchmark suite for benchmarking distributed transactional databases (DDBMSs), which is extended from the popular TPC-C benchmark.
dsb
The DSB benchmark is designed for evaluating both workloaddriven and traditional database systems on modern decision support workloads. DSB is adapted from the widely-used industrialstandard TPC-DS benchmark. It enhances the TPC-DS benchmark with complex data distribution and challenging yet semantically meaningful query templates. DSB also introduces configurable and dynamic workloads to assess the adaptability of database systems. Since workload-driven and traditional database systems have different performance dimensions, including the additional resources required for tuning and maintaining the systems, we provide guidelines on evaluation methodology and metrics to report.
End-to-End-CardEst-Benchmark
A new CardEst Benchmark to Bridge Algorithm and System
galaxysql
PolarDB-X is a cloud native distributed SQL Database designed for high concurrency, massive storage, complex querying scenarios.
greenplum--summarize
主要介绍作者使用过的Greenplum技术,欢迎大家交流
LEON
Pytorch implementation of LEON: A New Framework for ML-Aided Query Optimization.
multitenant
Spring Boot Multi-tenant Sample
naru
Neural Relation Understanding: neural cardinality estimators for tabular data
olxpbench
OLxPBench emphasizes that real-time queries, semantically consistent schema, and domain-specific workloads are essential in benchmarking, designing, and implementing HTAP systems.
qtune-mysql
Collaborated with Guoliang Li, Jiesi Liu, and Jianming Wu
restore
Implementation of our paper "ReStore - Neural Data Completion for Relational Databases"
sqlancer
Detecting Logic Bugs in DBMS
SubgraphMatching
In-Memory Subgraph Matching: An In-depth Study by Dr. Shixuan Sun and Prof. Qiong Luo
UAE
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation