On Thu, Jul 01 2021, ZheNing Hu via GitGitGadget wrote:

From: ZheNing Hu <redacted>

In order to let cat-file use ref-filter logic, let's do the
following:

1. Change the type of member `format` in struct `batch_options`
to `ref_format`, we will pass it to ref-filter later.
2. Let `batch_objects()` add atoms to format, and use
`verify_ref_format()` to check atoms.
3. Use `format_ref_array_item()` in `batch_object_write()` to
get the formatted data corresponding to the object. If the
return value of `format_ref_array_item()` is equals to zero,
use `batch_write()` to print object data; else if the return
value is less than zero, use `die()` to print the error message
and exit; else if return value is greater than zero, only print
the error message, but don't exit.
4. Use free_ref_array_item_value() to free ref_array_item's
value.

Most of the atoms in `for-each-ref --format` are now supported,
such as `%(tree)`, `%(parent)`, `%(author)`, `%(tagger)`, `%(if)`,
`%(then)`, `%(else)`, `%(end)`. But these atoms will be rejected:
`%(refname)`, `%(symref)`, `%(upstream)`, `%(push)`, `%(worktreepath)`,
`%(flag)`, `%(HEAD)`, because these atoms are unique to those objects
that pointed to by a ref, "for-each-ref"'s family can naturally use
these atoms, but not all objects are pointed to be a ref, so "cat-file"
will not be able to use them.

The performance for `git cat-file --batch-all-objects
--batch-check` on the Git repository itself with performance
testing tool `hyperfine` changes from 669.4 ms ±  31.1 ms to
1.134 s ±  0.063 s.

The performance for `git cat-file --batch-all-objects --batch

quoted

/dev/null` on the Git repository itself with performance testing

tool `time` change from "27.37s user 0.29s system 98% cpu 28.089
total" to "33.69s user 1.54s system 87% cpu 40.258 total".

This new feature is really nice, but that's a really bad performance
regression. A lot of software in the wild relies on "cat-file --batch"
to be *the* performant interface to git for mass-extrction of object
data.

That's in increase of ~70% and ~20%, respectively. Have you dug into
(e.g. with a profiler) where we're now spending all this time?