## 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
halfvec data type was introduced in pgvector 0.7.0 and is popular
because
it allows smaller vectors, smaller indexes and potentially better
performance.
So far we have not tested halfvec in our periodic performance tests.
This PR adds halfvec indexing and halfvec queries to the test.
## Problem
We want to regularly verify the performance of pgvector HNSW parallel
index builds and parallel similarity search using HNSW indexes.
The first release that considerably improved the index-build parallelism
was pgvector 0.7.0 and we want to make sure that we do not regress by
our neon compute VM settings (swap, memory over commit, pg conf etc.)
## Summary of changes
Prepare a Neon project with 1 million openAI vector embeddings (vector
size 1536).
Run HNSW indexing operations in the regression test for the various
distance metrics.
Run similarity queries using pgbench with 100 concurrent clients.
I have also added the relevant metrics to the grafana dashboards pgbench
and olape
---------
Co-authored-by: Alexander Bayandin <alexander@neon.tech>
It was nice to have and useful at the time, but unfortunately the method
used to gather the profiling data doesn't play nicely with 'async'. PR
#3228 will turn 'get_page_at_lsn' function async, which will break the
profiling support. Let's remove it, and re-introduce some kind of
profiling later, using some different method, if we feel like we need it
again.
Fix `test_seqscans` by disabling statement timeout.
Also, replace increasing statement timeout with disabling it for
performance tests. This should make tests more stable and allow us to
observe performance degradation instead of test failures.
Commit 43a4f7173e fixed the case that there are extra options in the
connection string, but broke it in the case when there are not. Fix
that. But on second thoughts, it's more straightforward set the
options with ALTER DATABASE, so change the workflow yaml file to do
that instead.
In commit 6985f6cd6c, I tried passing extra GUCs in the 'options' part
of the connection string, but it didn't work because the pgbench test
overrode it with the statement_timeout. Change it so that it adds the
statement_timeout to any other options, instead of replacing them.
Also get rid if `with_safekeepers` parameter in tests.
Its meaning has changed: `False` meant "no safekeepers" which is not
supported anymore, so we assume it's always `True`.
See #1648
This depends on a hacked version of the 'pprof-rs' crate. Because of
that, it's under an optional 'profiling' feature. It is disabled by
default, but enabled for release builds in CircleCI config. It doesn't
currently work on macOS.
The flamegraph is written to 'flamegraph.svg' in the pageserver
workdir when the 'pageserver' process exits.
Add a performance test that runs the perf_pgbench test, with profiling
enabled.
- Remove batch_others/test_pgbench.py. It was a quick check that pgbench
works, without actually recording any performance numbers, but that
doesn't seem very interesting anymore. Remove it to avoid confusing it
with the actual pgbench benchmarks
- Run pgbench with "-n" and "-S" options, for two different workloads:
simple-updates, and SELECT-only. Previously, we would only run it with
the "default" TPCB-like workload. That's more or less the same as the
simple-update (-n) workload, but I think the simple-upload workload
is more relevant for testing storage performance. The SELECT-only
workload is a new thing to measure.
- Merge test_perf_pgbench.py and test_perf_pgbench_remote.py. I added
a new "remote" implementation of the PgCompare class, which allows
running the same tests against an already-running Postgres instance.
- Make the PgBenchRunResult.parse_from_output function more
flexible. pgbench can print different lines depending on the
command-line options, but the parsing function expected a particular
set of lines.
tests are based on self-hosted runner which is physically close
to our staging deployment in aws, currently tests consist of
various configurations of pgbenchi runs.
Also these changes rework benchmark fixture by removing globals and
allowing to collect reports with desired metrics and dump them to json
for further analysis. This is also applicable to usual performance tests
which use local zenith binaries.
Instead of having a lot of separate fixtures for setting up the page
server, the compute nodes, the safekeepers etc., have one big ZenithEnv
object that encapsulates the whole environment. Every test either uses
a shared "zenith_simple_env" fixture, which contains the default setup
of a pageserver with no authentication, and no safekeepers. Tests that
want to use safekeepers or authentication set up a custom test-specific
ZenithEnv fixture.
Gathering information about the whole environment into one object makes
some things simpler. For example, when a new compute node is created,
you no longer need to pass the 'wal_acceptors' connection string as
argument to the 'postgres.create_start' function. The 'create_start'
function fetches that information directly from the ZenithEnv object.
* Add yapf run to CircleCI
* Pin yapf version
* Enable `SPLIT_ALL_TOP_LEVEL_COMMA_SEPARATED_VALUES` setting
* Reformat all existing code with slight manual adjustments
* test_runner/README: note that yapf is forced
* Use logging in python tests
* Use f-strings for logs
* Don't log test output while running
* Use only pytest logging handler
* Add more info about pytest logging
Now that the page server collects this metric (since commit 212920e47e),
let's include it in the performance test results
The new metric looks like this:
performance/test_perf_pgbench.py . [100%]
--------------- Benchmark results ----------------
test_pgbench.init: 6.784 s
test_pgbench.pageserver_writes: 466 MB <---- THIS IS NEW
test_pgbench.5000_xacts: 8.196 s
test_pgbench.size: 163 MB
=============== 1 passed in 21.00s ===============
This provides a pytest fixture to record metrics from pytest tests. The
The recorded metrics are printed out at the end of the tests.
As a starter, this includes on small test, using pgbench. It prints out
three metrics: the initialization time, runtime of 5000 xacts, and the
repository size after the tests.
