LPCE

This is for SIGMOD 2023 paper: "Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation".

LPCE-I

• In LPCE-I directory, please check the README for how to train and test LPCE-I model.

LPCE-R

• In LPCE-R directory, please check the README for how to train and test LPCE-R model.

Workload

• In Workload directory, please check the join-six.sql and join-eight.sql for experiments.

Distill

• In Distill directory, please check the README for how to distill LPCE model.

Use LPCE in Postgres

• In LPCE_inPostgres directory, please check how to adopt LPCE in PostgreSQL for query speedup.

Technical report

• techreport.pdf fills in some details not shown in SIGMOD paper due to the limited space.

From author

• Current release is adopting LPCE-I in PostgreSQL. We will release the adoption of LPCE-R in PostgreSQL soon.
• Current release was tested on PostgreSQL 13.0 version.