## Problem
We have a scale test for the storage controller which also acts as a
good stress test for scheduling stability. However, it created nodes
with no AZs set.
## Summary of changes
- Bump node count to 6 and set AZs on them.
This is a precursor to other AZ-related PRs, to make sure any new code
that's landed is getting scale tested in an AZ-aware environment.
## Problem
we tried different parallelism settings for ingest bench
## Summary of changes
the following settings seem optimal after merging
- SK side Wal filtering
- batched getpages
Settings:
- effective_io_concurrency 100
- concurrency limit 200 (different from Prod!)
- jobs 4, maintenance workers 7
- 10 GB chunk size
## Problem
```
2024-12-03T15:42:46.5978335Z + poetry run python /__w/neon/neon/scripts/ingest_perf_test_result.py --ingest /__w/neon/neon/test_runner/perf-report-local
2024-12-03T15:42:49.5325077Z Traceback (most recent call last):
2024-12-03T15:42:49.5325603Z File "/__w/neon/neon/scripts/ingest_perf_test_result.py", line 165, in <module>
2024-12-03T15:42:49.5326029Z main()
2024-12-03T15:42:49.5326316Z File "/__w/neon/neon/scripts/ingest_perf_test_result.py", line 155, in main
2024-12-03T15:42:49.5326739Z ingested = ingest_perf_test_result(cur, item, recorded_at_timestamp)
2024-12-03T15:42:49.5327488Z ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
2024-12-03T15:42:49.5327914Z File "/__w/neon/neon/scripts/ingest_perf_test_result.py", line 99, in ingest_perf_test_result
2024-12-03T15:42:49.5328321Z psycopg2.extras.execute_values(
2024-12-03T15:42:49.5328940Z File "/github/home/.cache/pypoetry/virtualenvs/non-package-mode-_pxWMzVK-py3.11/lib/python3.11/site-packages/psycopg2/extras.py", line 1299, in execute_values
2024-12-03T15:42:49.5335618Z cur.execute(b''.join(parts))
2024-12-03T15:42:49.5335967Z psycopg2.errors.InvalidTextRepresentation: invalid input syntax for type numeric: "concurrent-futures"
2024-12-03T15:42:49.5336287Z LINE 57: 'concurrent-futures',
2024-12-03T15:42:49.5336462Z ^
```
## Summary of changes
- `test_page_service_batching`: save non-numeric params as `labels`
- Add a runtime check that `metric_value` is NUMERIC
Before this PR, some override callbacks used `.default()`, others
used `.setdefault()`.
As of this PR, all callbacks use `.setdefault()` which I think is least
prone to failure.
Aligning on a single way will set the right example for future tests
that need such customization.
The `test_pageserver_getpage_throttle.py` technically is a change in
behavior: before, it replaced the `tenant_config` field, now it just
configures the throttle. This is what I believe is intended anyway.
## Problem
`test_sharded_ingest` ingests a lot of data, which can cause shutdown to
be slow e.g. due to local "S3 uploads" or compactions. This can cause
test flakes during teardown.
Resolves#9740.
## Summary of changes
Perform an immediate shutdown of the cluster.
This PR
- fixes smgr metrics https://github.com/neondatabase/neon/issues/9925
- adds an additional startup log line logging the current batching
config
- adds a histogram of batch sizes global and per-tenant
- adds a metric exposing the current batching config
The issue described #9925 is that before this PR, request latency was
only observed *after* batching.
This means that smgr latency metrics (most importantly getpage latency)
don't account for
- `wait_lsn` time
- time spent waiting for batch to fill up / the executor stage to pick
up the batch.
The fix is to use a per-request batching timer, like we did before the
initial batching PR.
We funnel those timers through the entire request lifecycle.
I noticed that even before the initial batching changes, we weren't
accounting for the time spent writing & flushing the response to the
wire.
This PR drive-by fixes that deficiency by dropping the timers at the
very end of processing the batch, i.e., after the `pgb.flush()` call.
I was **unable to maintain the behavior that we deduct
time-spent-in-throttle from various latency metrics.
The reason is that we're using a *single* counter in `RequestContext` to
track micros spent in throttle.
But there are *N* metrics timers in the batch, one per request.
As a consequence, the practice of consuming the counter in the drop
handler of each timer no longer works because all but the first timer
will encounter error `close() called on closed state`.
A failed attempt to maintain the current behavior can be found in
https://github.com/neondatabase/neon/pull/9951.
So, this PR remvoes the deduction behavior from all metrics.
I started a discussion on Slack about it the implications this has for
our internal SLO calculation:
https://neondb.slack.com/archives/C033RQ5SPDH/p1732910861704029
# Refs
- fixes https://github.com/neondatabase/neon/issues/9925
- sub-issue https://github.com/neondatabase/neon/issues/9377
- epic: https://github.com/neondatabase/neon/issues/9376
Improves `wait_until` by:
* Use `timeout` instead of `iterations`. This allows changing the
timeout/interval parameters independently.
* Make `timeout` and `interval` optional (default 20s and 0.5s). Most
callers don't care.
* Only output status every 1s by default, and add optional
`status_interval` parameter.
* Remove `show_intermediate_error`, this was always emitted anyway.
Most callers have been updated to use the defaults, except where they
had good reason otherwise.
# Problem
The timeout-based batching adds latency to unbatchable workloads.
We can choose a short batching timeout (e.g. 10us) but that requires
high-resolution timers, which tokio doesn't have.
I thoroughly explored options to use OS timers (see
[this](https://github.com/neondatabase/neon/pull/9822) abandoned PR).
In short, it's not an attractive option because any timer implementation
adds non-trivial overheads.
# Solution
The insight is that, in the steady state of a batchable workload, the
time we spend in `get_vectored` will be hundreds of microseconds anyway.
If we prepare the next batch concurrently to `get_vectored`, we will
have a sizeable batch ready once `get_vectored` of the current batch is
done and do not need an explicit timeout.
This can be reasonably described as **pipelining of the protocol
handler**.
# Implementation
We model the sub-protocol handler for pagestream requests
(`handle_pagrequests`) as two futures that form a pipeline:
2. Batching: read requests from the connection and fill the current
batch
3. Execution: `take` the current batch, execute it using `get_vectored`,
and send the response.
The Reading and Batching stage are connected through a new type of
channel called `spsc_fold`.
See the long comment in the `handle_pagerequests_pipelined` for details.
# Changes
- Refactor `handle_pagerequests`
- separate functions for
- reading one protocol message; produces a `BatchedFeMessage` with just
one page request in it
- batching; tried to merge an incoming `BatchedFeMessage` into an
existing `BatchedFeMessage`; returns `None` on success and returns back
the incoming message in case merging isn't possible
- execution of a batched message
- unify the timeline handle acquisition & request span construction; it
now happen in the function that reads the protocol message
- Implement serial and pipelined model
- serial: what we had before any of the batching changes
- read one protocol message
- execute protocol messages
- pipelined: the design described above
- optionality for execution of the pipeline: either via concurrent
futures vs tokio tasks
- Pageserver config
- remove batching timeout field
- add ability to configure pipelining mode
- add ability to limit max batch size for pipelined configurations
(required for the rollout, cf
https://github.com/neondatabase/cloud/issues/20620 )
- ability to configure execution mode
- Tests
- remove `batch_timeout` parametrization
- rename `test_getpage_merge_smoke` to `test_throughput`
- add parametrization to test different max batch sizes and execution
moes
- rename `test_timer_precision` to `test_latency`
- rename the test case file to `test_page_service_batching.py`
- better descriptions of what the tests actually do
## On the holding The `TimelineHandle` in the pending batch
While batching, we hold the `TimelineHandle` in the pending batch.
Therefore, the timeline will not finish shutting down while we're
batching.
This is not a problem in practice because the concurrently ongoing
`get_vectored` call will fail quickly with an error indicating that the
timeline is shutting down.
This results in the Execution stage returning a `QueryError::Shutdown`,
which causes the pipeline / entire page service connection to shut down.
This drops all references to the
`Arc<Mutex<Option<Box<BatchedFeMessage>>>>` object, thereby dropping the
contained `TimelineHandle`s.
- => fixes https://github.com/neondatabase/neon/issues/9850
# Performance
Local run of the benchmarks, results in [this empty
commit](1cf5b1463f)
in the PR branch.
Key take-aways:
* `concurrent-futures` and `tasks` deliver identical `batching_factor`
* tail latency impact unknown, cf
https://github.com/neondatabase/neon/issues/9837
* `concurrent-futures` has higher throughput than `tasks` in all
workloads (=lower `time` metric)
* In unbatchable workloads, `concurrent-futures` has 5% higher
`CPU-per-throughput` than that of `tasks`, and 15% higher than that of
`serial`.
* In batchable-32 workload, `concurrent-futures` has 8% lower
`CPU-per-throughput` than that of `tasks` (comparison to tput of
`serial` is irrelevant)
* in unbatchable workloads, mean and tail latencies of
`concurrent-futures` is practically identical to `serial`, whereas
`tasks` adds 20-30us of overhead
Overall, `concurrent-futures` seems like a slightly more attractive
choice.
# Rollout
This change is disabled-by-default.
Rollout plan:
- https://github.com/neondatabase/cloud/issues/20620
# Refs
- epic: https://github.com/neondatabase/neon/issues/9376
- this sub-task: https://github.com/neondatabase/neon/issues/9377
- the abandoned attempt to improve batching timeout resolution:
https://github.com/neondatabase/neon/pull/9820
- closes https://github.com/neondatabase/neon/issues/9850
- fixes https://github.com/neondatabase/neon/issues/9835
Adds a benchmark for logical message WAL ingestion throughput
end-to-end. Logical messages are essentially noops, and thus ignored by
the Pageserver.
Example results from my MacBook, with fsync enabled:
```
postgres_ingest: 14.445 s
safekeeper_ingest: 29.948 s
pageserver_ingest: 30.013 s
pageserver_recover_ingest: 8.633 s
wal_written: 10,340 MB
message_count: 1310720 messages
postgres_throughput: 715 MB/s
safekeeper_throughput: 345 MB/s
pageserver_throughput: 344 MB/s
pageserver_recover_throughput: 1197 MB/s
```
See
https://github.com/neondatabase/neon/issues/9642#issuecomment-2475995205
for running analysis.
Touches #9642.
## Problem
https://github.com/neondatabase/neon/pull/9746 lifted decoding and
interpretation of WAL to the safekeeper.
This reduced the ingested amount on the pageservers by around 10x for a
tenant with 8 shards, but doubled
the ingested amount for single sharded tenants.
Also, https://github.com/neondatabase/neon/pull/9746 uses bincode which
doesn't support schema evolution.
Technically the schema can be evolved, but it's very cumbersome.
## Summary of changes
This patch set addresses both problems by adding protobuf support for
the interpreted wal records and adding compression support. Compressed
protobuf reduced the ingested amount by 100x on the 32 shards
`test_sharded_ingest` case (compared to non-interpreted proto). For the
1 shard case the reduction is 5x.
Sister change to `rust-postgres` is
[here](https://github.com/neondatabase/rust-postgres/pull/33).
## Links
Related: https://github.com/neondatabase/neon/issues/9336
Epic: https://github.com/neondatabase/neon/issues/9329
## Problem
ingest benchmark tests project migration to Neon involving steps
- COPY relation data
- create indexes
- create constraints
Previously we used only 4 copy jobs, 4 create index jobs and 7
maintenance workers. After increasing effective_io_concurrency on
compute we see that we can sustain more parallelism in the ingest bench
## Summary of changes
Increase copy jobs to 8, create index jobs to 8 and maintenance workers
to 16
## Problem
For any given tenant shard, pageservers receive all of the tenant's WAL
from the safekeeper.
This soft-blocks us from using larger shard counts due to bandwidth
concerns and CPU overhead of filtering
out the records.
## Summary of changes
This PR lifts the decoding and interpretation of WAL from the pageserver
into the safekeeper.
A customised PG replication protocol is used where instead of sending
raw WAL, the safekeeper sends
filtered, interpreted records. The receiver drives the protocol
selection, so, on the pageserver side, usage
of the new protocol is gated by a new pageserver config:
`wal_receiver_protocol`.
More granularly the changes are:
1. Optionally inject the protocol and shard identity into the arguments
used for starting replication
2. On the safekeeper side, implement a new wal sending primitive which
decodes and interprets records
before sending them over
3. On the pageserver side, implement the ingestion of this new
replication message type. It's very similar
to what we already have for raw wal (minus decoding and interpreting).
## Notes
* This PR currently uses my [branch of
rust-postgres](https://github.com/neondatabase/rust-postgres/tree/vlad/interpreted-wal-record-replication-support)
which includes the deserialization logic for the new replication message
type. PR for that is open
[here](https://github.com/neondatabase/rust-postgres/pull/32).
* This PR contains changes for both pageservers and safekeepers. It's
safe to merge because the new protocol is disabled by default on the
pageserver side. We can gradually start enabling it in subsequent
releases.
* CI tests are running on https://github.com/neondatabase/neon/pull/9747
## Links
Related: https://github.com/neondatabase/neon/issues/9336
Epic: https://github.com/neondatabase/neon/issues/9329
## Problem
close https://github.com/neondatabase/neon/issues/9761
The test assumed that no new L0 layers are flushed throughout the
process, which is not true.
## Summary of changes
Fix the test case `test_compaction_l0_memory` by flushing in-memory
layers before compaction.
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
Along with the migration to Python 3.11, I switched `C(str, Enum)` with
`C(StrEnum)`; one such example is the `PgVersion` enum.
It required more changes in `PgVersion` itself (before, it accepted both
`str` and `int`, and after it, it supports only `str`), which caused the
`test_bulk_insert` test to fail.
## Summary of changes
- `test_bulk_insert`: explicitly cast pg_version from `timeline_detail`
to str
## Problem
On Debian 12 (Bookworm), Python 3.11 is the latest available version.
## Summary of changes
- Update Python to 3.11 in build-tools
- Fix ruff check / format
- Fix mypy
- Use `StrEnum` instead of pair `str`, `Enum`
- Update docs
## Problem
The first version of the ingest benchmark had some parsing and reporting
logic in shell script inside GitHub workflow.
it is better to move that logic into a python testcase so that we can
also run it locally.
## Summary of changes
- Create new python testcase
- invoke pgcopydb inside python test case
- move the following logic into python testcase
- determine backpressure
- invoke pgcopydb and report its progress
- parse pgcopydb log and extract metrics
- insert metrics into perf test database
- add additional column to perf test database that can receive endpoint
ID used for pgcopydb run to have it available in grafana dashboard when
retrieving other metrics for an endpoint
## Example run
https://github.com/neondatabase/neon/actions/runs/11860622170/job/33056264386
## Problem
Due to #9471 , the scale test occasionally gets 404s while trying to
modify the config of a timeline that belongs to a tenant being migrated.
We rarely see this narrow race in the field, but the test is quite good
at reproducing it.
## Summary of changes
- Ignore 404 errors in this test.
Analysis of the LR benchmarking tests indicates that in the duration of
test_subscriber_lag, a leftover 'slotter' replication slot can lead to
retained WAL growing on the publisher. This replication slot is not used
by any subscriber. The only purpose of the slot is to generate snapshot
files for the puspose of test_snap_files.
Signed-off-by: Tristan Partin <tristan@neon.tech>
psycopg2 has the following warning related to autocommit:
> By default, any query execution, including a simple SELECT will start
> a transaction: for long-running programs, if no further action is
> taken, the session will remain “idle in transaction”, an undesirable
> condition for several reasons (locks are held by the session, tables
> bloat…). For long lived scripts, either ensure to terminate a
> transaction as soon as possible or use an autocommit connection.
In the 2.9 release notes, psycopg2 also made the following change:
> `with connection` starts a transaction on autocommit transactions too
Some of these connections are indeed long-lived, so we were retaining
tons of WAL on the endpoints because we had a transaction pinned in the
past.
Link: https://www.psycopg.org/docs/news.html#what-s-new-in-psycopg-2-9
Link: https://github.com/psycopg/psycopg2/issues/941
Signed-off-by: Tristan Partin <tristan@neon.tech>
## Problem
Running `pytest.skip(...)` in a test body instead of marking the test
with `@pytest.mark.skipif(...)` makes all fixtures to be initialised,
which is not necessary if the test is going to be skipped anyway.
Also, some tests are unnecessarily skipped (e.g. `test_layer_bloating`
on Postgres 17, or `test_idle_reconnections` at all) or run (e.g.
`test_parse_project_git_version_output_positive` more than on once
configuration) according to comments.
## Summary of changes
- Move `skip_on_postgres` / `xfail_on_postgres` /
`run_only_on_default_postgres` decorators to `fixture.utils`
- Add new `skip_in_debug_build` and `skip_on_ci` decorators
- Replace `pytest.skip(...)` calls with decorators where possible
Adds a Python benchmark for sharded ingestion. This ingests 7 GB of WAL
(100M rows) into a Safekeeper and fans out to 10 shards running on 10
different pageservers. The ingest volume and duration is recorded.
## Problem
Part of https://github.com/neondatabase/neon/issues/8623
## Summary of changes
Removed all aux-v1 config processing code. Note that we persisted it
into the index part file, so we cannot really remove the field from
index part. I also kept the config item within the tenant config, but we
will not read it any more.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
We were seeing timeouts on migrations in this test.
The test unfortunately tends to saturate local storage, which is shared
between the pageservers and the control plane database, which makes the
test kind of unrealistic. We will also want to increase the scale of
this test, so it's worth fixing that.
## Summary of changes
- Instead of randomly creating timelines at the same time as the other
background operations, explicitly identify a subset of tenant which will
have timelines, and create them at the start. This avoids pageservers
putting a lot of load on the test node during the main body of the test.
- Adjust the tenants created to create some number of 8 shard tenants
and the rest 1 shard tenants, instead of just creating a lot of 2 shard
tenants.
- Use archival_config to exercise tenant-mutating operations, instead of
using timeline creation for this.
- Adjust reconcile_until_idle calls to avoid waiting 5 seconds between
calls, which causes timelines with large shard count tenants.
- Fix a pageserver bug where calls to archival_config during activation
get 404
## Problem
The path to TPC-H queries was incorrectly changed in #9306.
This path is used for `test_tpch` parameterization, so all perf tests
started to fail:
```
==================================== ERRORS ====================================
__________ ERROR collecting test_runner/performance/test_perf_olap.py __________
test_runner/performance/test_perf_olap.py:205: in <module>
@pytest.mark.parametrize("query", tpch_queuies())
test_runner/performance/test_perf_olap.py:196: in tpch_queuies
assert queries_dir.exists(), f"TPC-H queries dir not found: {queries_dir}"
E AssertionError: TPC-H queries dir not found: /__w/neon/neon/test_runner/performance/performance/tpc-h/queries
E assert False
E + where False = <bound method Path.exists of PosixPath('/__w/neon/neon/test_runner/performance/performance/tpc-h/queries')>()
E + where <bound method Path.exists of PosixPath('/__w/neon/neon/test_runner/performance/performance/tpc-h/queries')> = PosixPath('/__w/neon/neon/test_runner/performance/performance/tpc-h/queries').exists
```
## Summary of changes
- Fix the path to tpc-h queries
It didn't serve much value, and was only used twice.
Path(__file__).parent is a pretty easy invocation to use.
Signed-off-by: Tristan Partin <tristan@neon.tech>
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'.
This should generally be faster when running tests, especially those
that run with higher scales.
Ignoring test_lfc_resize since it seems like we are hitting a query
timeout for some reason that I have yet to investigate. A little bit of
improvemnt is better than none.
Signed-off-by: Tristan Partin <tristan@neon.tech>
After #8655, we needed to mark some tests to shut down immediately. To
aid these tests, try the new pattern of `flush_ep_to_pageserver`
followed by a non-compacting checkpoint. This moves the general graceful
shutdown problem of having too much to flush at shutdown into the test.
Also, add logging for how long the graceful shutdown took, if we got to
complete it for faster log eyeballing.
Fixes: #8712
Cc: #8715, #8708
## Problem
The default Postgres version is set to 15 in code, while we use 16 in
most of the other places (and Postgres 17 is coming)
## Summary of changes
- Run `benchmarks` job with Postgres 16 (instead of Postgres 14)
- Set `DEFAULT_PG_VERSION` to 16 in all places
- Remove deprecated `--pg-version` pytest argument
- Update `test_metadata_bincode_serde_ensure_roundtrip` for Postgres 16
## Problem
Current superuser check always passes because it returns a tuple like
`(False,)`, and then the `if not superuser` passes.
## Summary of changes
Fixes the issue by unwrapping the tuple. Verified that it works against
a project where I don't have superuser.
It seems that some benchmarks are failing because they are simply not
stopping to ingest wal on shutdown. It might mean that the tests were
never ran on a stable pageserver situation and WAL has always been left
to be ingested on safekeepers, but let's see if this silences the
failures and "stops the bleeding".
Cc: https://github.com/neondatabase/neon/issues/8712
## Problem
Pageserver exposes some vectored get related configs which are not in
use.
## Summary of changes
Remove the following pageserver configs: get_impl, get_vectored_impl,
and `validate_get_vectored`.
They are not used in the pageserver since
https://github.com/neondatabase/neon/pull/8601.
Manual overrides have been removed from the aws repo in
https://github.com/neondatabase/aws/pull/1664.
## Problem
This test was disabled.
## Summary of changes
- Remove the skip marker.
- Explicitly avoid doing compaction & gc during checkpoints (the default
scale doesn't do anything here, but when experimeting with larger scales
it messes things up)
- Set a data size that gives a ~20s runtime on a Hetzner dev machine,
previous one gave very noisy results because it was so small
For reference on a Hetzner AX102:
```
------------------------------ Benchmark results -------------------------------
test_bulk_insert[neon-release-pg16].insert: 25.664 s
test_bulk_insert[neon-release-pg16].pageserver_writes: 5,428 MB
test_bulk_insert[neon-release-pg16].peak_mem: 577 MB
test_bulk_insert[neon-release-pg16].size: 0 MB
test_bulk_insert[neon-release-pg16].data_uploaded: 1,922 MB
test_bulk_insert[neon-release-pg16].num_files_uploaded: 8
test_bulk_insert[neon-release-pg16].wal_written: 1,382 MB
test_bulk_insert[neon-release-pg16].wal_recovery: 25.373 s
test_bulk_insert[neon-release-pg16].compaction: 0.035 s
```
## Problem
Migrations of tenant shards with cold secondaries are holding up drains
in during production deployments.
## Summary of changes
If a secondary locations is lagging by more than 256MiB (configurable,
but that's the default), then skip cutting it over to the secondary as part of the node drain.
## Problem
The controller scale test does random migrations. These mutate secondary
locations, and therefore can cause secondary optimizations to happen in
the background, violating the test's expectation that consistency_check
will work as there are no reconciliations running.
Example:
https://neon-github-public-dev.s3.amazonaws.com/reports/main/10247161379/index.html#suites/07874de07c4a1c9effe0d92da7755ebf/6316beacd3fb3060/
## Summary of changes
- Only migrate to existing secondary locations, not randomly picked
nodes, so that we can do a fast reconcile_until_idle (otherwise
reconcile_until_idle is takes a long time to create new secondary
locations).
- Do a reconcile_until_idle before consistency_check.
## Problem
> Currently, long-running LR tests recreate endpoints every night. We'd
like to have along-running buildup of history to exercise the pageserver
in this case (instead of "unit-testing" the same behavior everynight).
Closes#8317
## Summary of changes
- Update Postgres version for replication tests
- Set `BENCHMARK_PROJECT_ID_PUB`/`BENCHMARK_PROJECT_ID_SUB` env vars to
projects that were created for this purpose
---------
Co-authored-by: Sasha Krassovsky <krassovskysasha@gmail.com>
## Problem
Re-attach blocks the pageserver http server from starting up. Hence, it
can't reply to heartbeats
until that's done. This makes the storage controller mark the node
off-line (not good). We worked
around this by setting the interval after which nodes are marked offline
to 5 minutes. This isn't a
long term solution.
## Summary of changes
* Introduce a new `NodeAvailability` state: `WarmingUp`. This state
models the following time interval:
* From receiving the re-attach request until the pageserver replies to
the first heartbeat post re-attach
* The heartbeat delta generator becomes aware of this state and uses a
separate longer interval
* Flag `max-warming-up-interval` now models the longer timeout and
`max-offline-interval` the shorter one to
match the names of the states
Closes https://github.com/neondatabase/neon/issues/7552
