## Problem
`TYPE_CHECKING` is used inconsistently across Python tests.
## Summary of changes
- Update `ruff`: 0.7.0 -> 0.11.2
- Enable TC (flake8-type-checking):
https://docs.astral.sh/ruff/rules/#flake8-type-checking-tc
- (auto)fix all new issues
## Problem
In https://github.com/neondatabase/neon/pull/8103 we changed the test
case to have more test coverage of gc_compaction. Now that we have
`test_gc_compaction_smoke`, we can revert this test case to serve its
original purpose and revert the parameter changes.
part of https://github.com/neondatabase/neon/issues/9114
## Summary of changes
* Revert pitr_interval from 60s to 10s.
* Assert the physical/logical size ratio in the benchmark.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
Co-authored-by: Arpad Müller <arpad-m@users.noreply.github.com>
Add wrappers for a few commands that didn't have them before. Move the
logic to generate tenant and timeline IDs from NeonCli to the callers,
so that NeonCli is more purely just a type-safe wrapper around
'neon_local'.
Adds manual compaction trigger; add gc compaction to test_gc_feedback
Part of https://github.com/neondatabase/neon/issues/8002
```
test_gc_feedback[debug-pg15].logical_size: 50 Mb
test_gc_feedback[debug-pg15].physical_size: 2269 Mb
test_gc_feedback[debug-pg15].physical/logical ratio: 44.5302
test_gc_feedback[debug-pg15].max_total_num_of_deltas: 7
test_gc_feedback[debug-pg15].max_num_of_deltas_above_image: 2
test_gc_feedback[debug-pg15].logical_size_after_bottom_most_compaction: 50 Mb
test_gc_feedback[debug-pg15].physical_size_after_bottom_most_compaction: 287 Mb
test_gc_feedback[debug-pg15].physical/logical ratio after bottom_most_compaction: 5.6312
test_gc_feedback[debug-pg15].max_total_num_of_deltas_after_bottom_most_compaction: 4
test_gc_feedback[debug-pg15].max_num_of_deltas_above_image_after_bottom_most_compaction: 1
```
## Summary of changes
* Add the manual compaction trigger
* Use in test_gc_feedback
* Add a guard to avoid running it with retain_lsns
* Fix: Do `schedule_compaction_update` after compaction
* Fix: Supply deltas in the correct order to reconstruct value
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
A simple API to collect some statistics after compaction to easily
understand the result.
The tool reads the layer map, and analyze range by range instead of
doing single-key operations, which is more efficient than doing a
benchmark to collect the result. It currently computes two key metrics:
* Latest data access efficiency, which finds how many delta layers /
image layers the system needs to iterate before returning any key in a
key range.
* (Approximate) PiTR efficiency, as in
https://github.com/neondatabase/neon/issues/7770, which is simply the
number of delta files in the range. The reason behind that is, assume no
image layer is created, PiTR efficiency is simply the cost of collect
records from the delta layers, and the replay time. Number of delta
files (or in the future, estimated size of reads) is a simple yet
efficient way of estimating how much effort the page server needs to
reconstruct a page.
Signed-off-by: Alex Chi Z <chi@neon.tech>
It's been dead-code-at-runtime for 9 months, let's remove it.
We can always re-introduce it at a later point.
Came across this while working on #6861, which will touch
`time_for_new_image_layer`. This is an opporunity to make that function
simpler.
## Describe your changes
Right now the only criteria for image layer generation is number of
delta layer since last image layer.
If we have "stairs" layout of delta layers (see link below) then it can
happen that there a lot of old delta layers which can not be reclaimed
by GC because are not fully covered with image layers.
This PR constructs list of "wanted" image layers in GC (which image
layers are needed to be able to remove old layers)
and pass this list to compaction task which performs generation of image
layers.
So right now except deltas count criteria we also take in account
"wishes" of GC.
## Issue ticket number and link
See
https://neondb.slack.com/archives/C033RQ5SPDH/p1676914249982519
## Checklist before requesting a review
- [ ] I have performed a self-review of my code.
- [ ] If it is a core feature, I have added thorough tests.
- [ ] Do we need to implement analytics? if so did you add the relevant
metrics to the dashboard?
- [ ] If this PR requires public announcement, mark it with
/release-notes label and add several sentences in this section.
---------
Co-authored-by: Joonas Koivunen <joonas@neon.tech>
Co-authored-by: Heikki Linnakangas <heikki@neon.tech>
