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Recently I did many Profile-Guided Optimization (PGO) benchmarks on multiple projects (including many databases like PostgreSQL, ClickHouse, Redis, MongoDB, etc.) - the results are available here. So that's why I think it's worth trying to apply PGO to OpenMLDB to improve the database performance further.
I can suggest the following things to do:
Evaluate PGO's results on OpenMLDB.
If PGO helps to achieve better performance - add a note to OpenMLDB's documentation about that (probably somewhere in the README file). In this case, users and maintainers will be aware of another optimization opportunity for OpenMLDB.
Provide PGO integration into the build scripts. It can help users and maintainers easily apply PGO for their own workloads.
Optimize prebuilt binaries with PGO.
Here are some examples of how PGO is already integrated into other projects' build scripts:
Hi!
Recently I did many Profile-Guided Optimization (PGO) benchmarks on multiple projects (including many databases like PostgreSQL, ClickHouse, Redis, MongoDB, etc.) - the results are available here. So that's why I think it's worth trying to apply PGO to OpenMLDB to improve the database performance further.
I can suggest the following things to do:
Here are some examples of how PGO is already integrated into other projects' build scripts:
configure
scriptAfter PGO, I can suggest evaluating LLVM BOLT as an additional optimization step after PGO.
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