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zhengtongyan's Projects

cyp2sql-1 icon cyp2sql-1

Cypher to SQL translation tool - (for Part II project)

database-courses icon database-courses

This repository contains the famous courses about databases, such as the courses of MIT, CMU, and TiDB.

database-sql-joins-algorithm icon database-sql-joins-algorithm

An implementation of the algorithms presented in the paper "Cardinality Estimation Done Right: Index-Based Join Sampling"

datacorrelationpredictionwithnlp icon datacorrelationpredictionwithnlp

In this project, I try to predict data correlations by analyzing column names. Such methods can be useful, for instance, for database tuning as correlations make optimization hard. I use pre-trained language models, based on the transformer architecture, for the prediction.

dataeng icon dataeng

Repository fo Data Engineering Course

db-engine-paradigms icon db-engine-paradigms

Collection of experiments to carve out the differences between two types of relational query processing engines: Vectorizing (interpretation based) engines and compiling engines.

db-gpt icon db-gpt

AI Native Data App Development framework with AWEL(Agentic Workflow Expression Language) and Agents

db-learning-material icon db-learning-material

📚 CMU 15-721 & MIT 6.824 & Advanced topics about databases and distributed system.🔎

dbbert icon dbbert

DB-BERT is a database tuning tools that exploits natural language text as additional input. It extracts recommendations for database parameter settings from tuning-related text via natural language analysis. It optimizes parameter settings for a given workload and performance metric using reinforcement learning.

dbt-mysql icon dbt-mysql

dbt-mysql contains all of the code enabling dbt to work with MySQL and MariaDB

dbtune icon dbtune

A customized and efficient database tuning system [VLDB'22]

deepdb-public icon deepdb-public

Implementation of DeepDB: Learn from Data, not from Queries!

deeprl icon deeprl

Deep Reinforcement Learning Lab, a platform designed to make DRL technology and fun for everyone

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