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.

About

This is for SIGMOD submission "Learning-based Progressive Cardinality Estimation for End-to-end Query Execution"

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