This adds node id parameter to pageserver configuration. Also I use a
simple builder to construct pageserver config struct to avoid setting
node id to some temporary invalid value. Some of the changes in test
fixtures are needed to split init and start operations for envrionment.
The first COPY generates about 230 MB of write I/O, but the second
COPY, after deleting most of the rows and vacuuming the rows away,
generates 370 MB of writes. Both COPYs insert the same amount of data,
so they should generate roughly the same amount of I/O. This commit
doesn't try to fix the issue, just adds a test case to demonstrate it.
Add a new 'checkpoint' command to the pageserver API. Previously,
we've used 'do_gc' for that, but many tests, including this new one,
really only want to perform a checkpoint and don't care about GC. For
now, I only used the command in the new test, though, and didn't
convert any existing tests to use it.
* change zenith-perf-data checkout ref to be main
* set cluster id through secrets so there is no code changes required
when we wipe out clusters on staging
* display full pgbench output on error
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
This is in preparation for supporting read-only nodes. You can launch
multiple read-only nodes on the same brach, so we need an identifier
for each node, separate from the branch name.
* 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
When a WAL record affects multiple pages, we currently duplicate the
record for each affected page. That's a bit wasteful, but not too bad
for b-tree splits and non-hot heap updates that affect two pages. But
buffering GiST index build WAL-logs the whole relation in 32 page chunks,
with one giant WAL record for each 32-page chunk. Currently we duplicate
that giant record for each of the 32 pages, which is really wasteful.
Github issue https://github.com/zenithdb/zenith/issues/720 tracks the
problem. This commit adds a test case for it to demonstrate it.
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.
