shoupzwu/UAE
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation
This project helps database administrators and performance tuners improve how quickly their database queries run. It takes your existing database schema and a collection of past queries to predict how many rows a query will return. The output is a highly accurate prediction that can be fed into a database's query optimizer, leading to faster execution times for complex queries.
No commits in the last 6 months.
Use this if you are a database administrator or performance engineer struggling with slow query performance due to inaccurate row count estimates.
Not ideal if you are looking for a general-purpose machine learning library or a tool for data analysis rather than database performance optimization.
Stars
28
Forks
12
Language
Python
License
—
Last pushed
Oct 08, 2021
Commits (30d)
0
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