close https://github.com/neondatabase/neon/issues/9160
For whatever reason, pg17's WAL pattern seems different from others,
which triggers some flaky behavior within the compaction smoke test.
## Summary of changes
* Run L0 compaction before proceeding with the read benchmark.
* So that we can ensure the num of L0 layers is 0 and test the
compaction behavior only with L1 layers.
We have a threshold for triggering L0 compaction. In some cases, the
test case did not produce enough L0 layers to do a L0 compaction,
therefore leaving the layer map with 3+ L0 layers above the L1 layers.
This increases the average read depth for the timeline.
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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>
