This PR commits the benchmarks I ran to qualify concurrent IO before we
released it.
Changes:
- Add `l0stack` fixture; a reusable abstraction for creating a stack of
L0 deltas
each of which has 1 Value::Delta per page.
- Such a stack of L0 deltas is a good and understandable demo for
concurrent IO
because to reconstruct any page, $layer_stack_height` Values need to be
read.
Before concurrent IO, the reads were sequential.
With concurrent IO, they are executed concurrently.
- So, switch `test_latency` to use the l0stack.
- Teach `pagebench`, which is used by `test_latency`, to limit itself to
the blocks of the relation created by the l0stack abstraction.
- Additional parametrization of `test_latency` over dimensions
`ps_io_concurrency,l0_stack_height,queue_depth`
- Use better names for the tests to reflect what they do, leave
interpretation of the (now quite high-dimensional) results to the reader
- `test_{throughput => postgres_seqscan}`
- `test_{latency => random_reads}`
- Cut down on permutations to those we use in production. Runtime is
about 2min.
Refs
- concurrent IO epic https://github.com/neondatabase/neon/issues/9378
- batching task: fixes https://github.com/neondatabase/neon/issues/9837
---------
Co-authored-by: Peter Bendel <peterbendel@neon.tech>
## Problem
Imports don't support schema evolution nicely. If we want to change the
stuff we keep in storcon,
we'd have to carry the old cruft around.
## Summary of changes
Version import progress. Note that the import progress version
determines the version of the import
job split and execution. This means that we can also use it as a
mechanism for deploying new import
implementations in the future.
## Problem
Timeline imports do not have progress checkpointing. Any time that the
tenant is shut-down, all progress is lost
and the import restarts from the beginning when the tenant is
re-attached.
## Summary of changes
This PR adds progress checkpointing.
### Preliminaries
The **unit of work** is a `ChunkProcessingJob`. Each
`ChunkProcessingJob` deals with the import for a set of key ranges. The
job split is done by using an estimation of how many pages each job will
produce.
The planning stage must be **pure**: given a fixed set of contents in
the import bucket, it will always yield the same plan. This property is
enforced by checking that the hash of the plan is identical when
resuming from a checkpoint.
The storage controller tracks the progress of each shard in the import
in the database in the form of the **latest
job** that has has completed.
### Flow
This is the high level flow for the happy path:
1. On the first run of the import task, the import task queries storcon
for the progress and sees that none is recorded.
2. Execute the preparatory stage of the import
3. Import jobs start running concurrently in a `FuturesOrdered`. Every
time the checkpointing threshold of jobs has been reached, notify the
storage controller.
4. Tenant is detached and re-attached
5. Import task starts up again and gets the latest progress checkpoint
from the storage controller in the form of a job index.
6. The plan is computed again and we check that the hash matches with
the original plan.
7. Jobs are spawned from where the previous import task left off. Note
that we will not report progress after the completion of each job, so
some jobs might run twice.
Closes https://github.com/neondatabase/neon/issues/11568
Closes https://github.com/neondatabase/neon/issues/11664
## Problem
Import up-calls did not enforce the usage of the latest generation. The
import might have finished in one previous generation, but not in the
latest one. Hence, the controller might try to activate a timeline
before it is ready. In theory, that would be fine, but it's tricky to
reason about.
## Summary of Changes
Pageserver provides the current generation in the upcall to the storage
controller and the later validates the generation. If the generation is
stale, we return an error which stops progress of the import job. Note
that the import job will retry the upcall until the stale location is
detached.
I'll add some proper tests for this as part of the [checkpointing
PR](https://github.com/neondatabase/neon/pull/11862).
Closes https://github.com/neondatabase/neon/issues/11884
## Problem
```
Error when evaluating 'strategy' for job 'build-pgxn'. neondatabase/neon/.github/workflows/build-macos.yml@7907a9e2bf898f3d22b98d9d4d2c6ffc4d480fc3 (Line: 45, Col: 27): Matrix vector 'postgres-version' does not contain any values
```
See
https://github.com/neondatabase/neon/actions/runs/15039594216/job/42268015127?pr=11929
## Summary of changes
- Fix typo: `.chnages` -> `.changes`
- Ensure JSON is JSON by moving step output to env variable
## Problem
close https://github.com/neondatabase/neon/issues/11159 ; we get
occasional wrong deletions of layer files being used and errors in
staging. This patch fixed it.
Example errors:
```
Timeline metadata errors: ["index_part.json contains a layer .... (shard 0000) that is not present in remote storage (layer_is_l0: false) with error: Failed to download a remote file: s3 head object\n\nCaused by:\n 0: dispatch failure\n 1: timeout\n 2: error trying to connect: HTTP connect timeout occurred after 3.1s\n
```
This error should not be fired because the file could exist, but we
cannot know if it exists due to head request failure.
## Summary of changes
Only generate cannot find layer errors when the head_object return type
is `NotFound`.
Signed-off-by: Alex Chi Z <chi@neon.tech>
Use the current production config for batching & concurrent IO.
Remove the permutation testing for unit tests from CI.
(The pageserver unit test matrix takes ~10min for debug builds).
Drive-by-fix use of `if cfg!(test)` inside crate `pageserver_api`.
It is ineffective for early-enabling new defaults for pageserver unit
tests only.
The reason is that the `test` cfg is only set for the crate under test
but not its dependencies.
So, `cargo test -p pageserver` will build `pageserver_api` with
`cfg!(test) == false`.
Resort to checking for feature flag `testing` instead, since all our
unit tests are run with `--feature testing`.
refs
- `scattered-lsn` batching has been implemented and rolled out in all
envs, cf https://github.com/neondatabase/neon/issues/10765
- preliminary for https://github.com/neondatabase/neon/pull/10466
- epic https://github.com/neondatabase/neon/issues/9377
- epic https://github.com/neondatabase/neon/issues/9378
- drive-by fix
https://neondb.slack.com/archives/C0277TKAJCA/p1746821515504219
## Problem
The regression test on extensions relied on the admin API to set the
default endpoint settings, which is not stable and requires admin
privileges. Specifically:
- The workflow was using `default_endpoint_settings` to configure
necessary PostgreSQL settings like `DateStyle`, `TimeZone`, and
`neon.allow_unstable_extensions`
- This approach was failing because the API endpoint for setting
`default_endpoint_settings` was changed (referenced in a comment as
issue #27108)
- The admin API requires special privileges.
## Summary of changes
We get rid of the admin API dependency and use ALTER DATABASE statements
instead:
**Removed the default_endpoint_settings mechanism:**
- Removed the default_endpoint_settings input parameter from the
neon-project-create action
- Removed the API call that was attempting to set these settings at the
project level
- Completely removed the default_endpoint_settings configuration from
the cloud-extensions workflow
**Added database-level settings:**
- Created a new `alter_db.sh` script that applies the same settings
directly to each test database
- Modified all extension test scripts to call this script after database
creation
## Problem
Hopefully resolves `test_gc_feedback` flakiness.
## Summary of changes
`accumulated_values` should not exceed 512MB to avoid OOM. Previously we
only use number of items, which is not a good estimation.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
Lifetime of imported timelines (and implicitly the import background
task) has some shortcomings:
1. Timeline activation upon import completion is tricky. Previously, a
timeline that finished importing
after a tenant detach would not get activated and there's concerns about
the safety of activating
concurrently with shut-down.
2. Import jobs can prevent tenant shut down since they hold the tenant
gate
## Summary of Changes
Track the import tasks in memory and abort them explicitly on tenant
shutdown.
Integrate more closely with the storage controller:
1. When an import task has finished all of its jobs, it notifies the
storage controller, but **does not** mark the import as done in the
index_part. When all shards have finished importing, the storage
controller will call the `/activate_post_import` idempotent endpoint for
all of them. The handler, marks the import complete in index part,
resets the tenant if required and checks if the timeline is active yet.
2. Not directly related, but the import job now gets the starting state
from the storage controller instead of the import bucket. This paves the
way for progress checkpointing.
Related: https://github.com/neondatabase/neon/issues/11568
## Problem
It's difficult to understand where proxy spends most of cpu and memory.
## Summary of changes
Expose cpu and heap profiling handlers for continuous profiling.
neondatabase/cloud#22670
## Problem
Prefetched and LFC results are not checked in DEBUG_COMPARE_LOCAL mode
## Summary of changes
Add check for this results as well.
---------
Co-authored-by: Konstantin Knizhnik <knizhnik@neon.tech>
Bump all minor versions.
the only conflict was
src/backend/storage/smgr/smgr.c in v17
where our smgr changes conflicted with
ee578921b6
but it was trivial to resolve.
## Problem
1. Safekeeper selection on the pageserver side isn't very dynamic. Once
you connect to one safekeeper, you'll use that one for as long as the
safekeeper keeps the connection alive. In principle, we could be more
eager, since the wal receiver connection can be cancelled but we don't
do that. We wait until the "session" is done and then we pick a new SK.
2. Picking a new SK is quite conservative. We will switch if:
a. We haven't received anything from the SK within the last 10 seconds
(wal_connect_timeout) or
b. The candidate SK is 1GiB ahead or
c. The candidate SK is in the same AZ as the PS or d. There's a
candidate that is ahead and we've not had any WAL within the last 10
seconds (lagging_wal_timeout)
Hence, we can end up with pageservers that are requesting WAL which
their safekeeper hasn't seen yet.
## Summary of changes
Downgrade warning log to info.
## Problem
part of https://github.com/neondatabase/neon/issues/11813
## Summary of changes
Add a lite PostHog client that only uses the local flag evaluation
functionality. Added a test case that parses an example feature flag and
gets the evaluation result.
TODO: support boolean flag, remote config; implement all operators in
PostHog.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
We implemented the retry logic in AWS S3 but not in Azure. Therefore, if
there is an error during Azure listing, we will return an Err to the
caller, and the stream will end without fetching more tenants.
Part of https://github.com/neondatabase/neon/issues/11159
Without this fix, listing tenant will stop once we hit an error (could
be network errors -- that happens more frequent on Azure). If we happen
to stop at a point that we only listed part of the shards, we will hit
the "missed shards" error or even remove layers being used.
This bug (for Azure listing) was introduced as part of
https://github.com/neondatabase/neon/pull/9840
There is also a bug that stops the stream for AWS when there's a timeout
-- this is fixed along with this patch.
## Summary of changes
Retry the request on error. In the future, we should make such streams
return something like `Result<Result<T>>` where the outer result is the
error that ends the stream and the inner one is the error that should be
retried by the caller.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
For `StoreCancelKey`, we were inserting 2 commands, but we were not
inserting two replies. This mismatch leads to errors when decoding the
response.
## Summary of changes
Abstract the command + reply pipeline so that commands and replies are
registered at the same time.
## Problem
When aborting a split, the code accidentally removes all other tenant
shards from the in-memory map that have the same shard count as the
aborted split, causing "tenant not found" errors. It will recover on a
storcon restart, when it loads the persisted state. This issue has been
present for at least a year.
Resolves https://github.com/neondatabase/cloud/issues/28589.
## Summary of changes
Only remove shards belonging to the relevant tenant when aborting a
split.
Also adds a regression test.
## Problem
We didn't consider tombstones in replorigin read path in the past. This
was fine because tombstones are stored as LSN::Invalid before we
universally define what the tombstone is for sparse keyspaces.
Now we remove non-inherited keys during detach ancestor and write the
universal tombstone "empty image". So we need to consider it across all
the read paths.
related: https://github.com/neondatabase/neon/pull/11299
## Summary of changes
Empty value gets ignored for replorigin scans.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
If all batched requests are excluded from the query by
`Timeine::get_rel_page_at_lsn_batched` (e.g. because they are past the
end of the relation), the read path would panic since it doesn't expect
empty queries. This is a change in behaviour that was introduced with
the scattered query implementation.
## Summary of Changes
Handle empty queries explicitly.
## Problem
https://github.com/neondatabase/neon/actions/runs/14538136318/job/40790985693?pr=11645
failed, even though the relevant parts of the CI had passed and
auto-merge determined the PR is ready to merge. After that, commenting
failed.
## Summary of changes
- set GH_TOKEN for commenting after fast-forward failure
- allow merging with mergeable_state unstable
(cherry picked from commit 04370b48b3)
Conflicts:
storage_controller/src/service.rs
Because `release` head doesn't yet have
`storcon: timetime table, creation and deletion (#11058)`
## Problem
As part of the disaster recovery tool. Partly for
https://github.com/neondatabase/neon/issues/9114.
## Summary of changes
* Add a new pageserver API to force patch the fields in index_part and
modify the timeline internal structures.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
Shard zero needs to track the start LSN of the latest record
in adition to the LSN of the next record to ingest. The former
is included in basebackup persisted by the compute in WAL.
Previously, empty records were skipped for all shards. This caused
the prev LSN tracking on the PS to fall behind and led to logical
replication
issues.
## Summary of changes
Shard zero now receives emtpy interpreted records for LSN tracking
purposes.
A test is included too.
## Problem
On unarchival, we update the previous heatmap with all visible layers.
When the primary generates a new heatmap it includes all those layers,
so the secondary will download them. Since they're not actually resident
on the primary (we didn't call the warm up API), they'll never be
evicted, so they remain in the heatmap.
This leads to oversized secondary locations like we saw in pre-prod.
## Summary of changes
Gate the loading of the previous heatmaps and the heatmap generation on
unarchival behind configuration
flags. They are disabled by default, but enabled in tests.
## Problem
`wait_for_active_tenant()`, used when starting background tasks, has a
race condition that can cause it to wait forever (until cancelled). It
first checks the current tenant state, and then subscribes for state
updates, but if the state changes between these then it won't be
notified about it.
We've seen this wedge compaction tasks, which can cause unbounded layer
file buildup and read amplification.
## Summary of changes
Use `watch::Receiver::wait_for()` to check both the current and new
tenant states.
## Problem
JWT tokens aren't in place, so all SK heartbeats fail. This is
equivalent to a wait before applying the PS heartbeats and makes things
more flaky.
## Summary of Changes
Add a flag that skips loading SKs from the db on start-up and at
runtime.
## Problem
The storage controller treats durations in the tenant config as strings.
These are loaded from the db.
The pageserver maps these durations to a seconds only format and we
always get a mismatch compared
to what's in the db.
## Summary of changes
Treat durations as durations inside the storage controller and not as
strings.
Nothing changes in the cross service API's themselves or the way things
are stored in the db.
I also added some logging which I would have made the investigation a
10min job:
1. Reason for why the reconciliation was spawned
2. Location config diff between the observed and wanted states
## Problem
Read errors during repartition should be a critical error.
## Summary of changes
<del>We only have one call site</del> We have two call sites of
`repartition` where one of them is during the initial image upload
optimization and another is during image layer creation, so I added a
`critical!` here instead of inside `collect_keyspace`.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
This reverts commit 443c8d0b4b.
## Problem
We observe a massive amount of compaction errors.
## Summary of changes
If the tenant did not write any L1 layers (i.e., they accumulate L0
layers where number of them is below L0 threshold), image creation will
always fail. Therefore, it's not correct to simply use the
disk_consistent_lsn or L0/L1 boundary for the image creation.
## Problem
In #10707 some new fields were introduced in TimelineInfo.
I forgot that we do not only use TimelineInfo for encoding, but also
decoding when the storage controller calls into a pageserver, so this
broke some calls from controller to pageserver while in a mixed-version
state.
## Summary of changes
- Make new fields have default behavior so that they are optional
## Problem
Some situations may produce a large number of pending reconciles. If we
experience an issue where reconciles are processed more slowly than
expected, that can prevent us responding promptly to user requests like
tenant/timeline CRUD.
This is a cleaner implementation of the hotfix in
https://github.com/neondatabase/neon/pull/10815
## Summary of changes
- Introduce a second semaphore for high priority tasks, with
configurable units (default 256). The intent is that in practical
situations these user-facing requests should never have to wait.
- Use the high priority semaphore for: tenant/timeline CRUD, and shard
splitting operations. Use normal priority for everything else.
## Problem
We had code for stripping IDs out of proxied paths to reduce cardinality
of metrics, but it was only stripping out tenant IDs, and leaving in
timeline IDs and query parameters (e.g. LSN in lsn->timestamp lookups).
## Summary of changes
- Use a more general regex approach.
There is still some risk that a future pageserver API might include a
parameter in `/the/path/`, but we control that API and it is not often
extended. We will also alert on metrics cardinality in staging so that
if we made that mistake we would notice.
# Problem
Say we have a batch of 10 responses to send out.
Then, even with
- #10728
we've still only called observe_execution_end_flush_start for the first
3 responses.
The remaining 7 response timers are still ticking.
When compute now closes the connection, the waiting flush fails with an
error and we `drop()` the remaining 7 responses' smgr op timers. The
`impl Drop for SmgrOpTimer` will observe an execution time that includes
the flush time.
In practice, this is supsected to produce the `+Inf` observations in the
smgr op latency histogram we've seen since the introduction of
pipelining, even after shipping #10728.
refs:
- fixup of https://github.com/neondatabase/neon/pull/10042
- fixup of https://github.com/neondatabase/neon/pull/10728
- fixes https://github.com/neondatabase/neon/issues/10754
## Problem
Since enabling continuous profiling in staging, we've seen frequent seg
faults. This is suspected to be because jemalloc and pprof-rs take a
stack trace at the same time, and the handlers aren't signal safe.
jemalloc does this probabilistically on every allocation, regardless of
whether someone is taking a heap profile, which means that any CPU
profile has a chance to cause a seg fault.
Touches #10225.
## Summary of changes
For now, just disable heap profiles -- CPU profiles are more important,
and we need to be able to take them without risking a crash.
## Problem
With pipelining enabled, the time a request spends in the batcher stage
counts towards the smgr op latency.
If pipelining is disabled, that time is not accounted for.
In practice, this results in a jump in smgr getpage latencies in various
dashboards and degrades the internal SLO.
## Solution
In a similar vein to #10042 and with a similar rationale, this PR stops
counting the time spent in batcher stage towards smgr op latency.
The smgr op latency metric is reduced to the actual execution time.
Time spent in batcher stage is tracked in a separate histogram.
I expect to remove that histogram after batching rollout is complete,
but it will be helpful in the meantime to reason about the rollout.
## Problem
Protobuf doesn't support 128 bit integers, so we encode the keys as two
64 bit integers. Issue is that when we split the 128 bit compact key we
use signed 64 bit integers to represent the two halves. This may result
in a negative lower half when relnode is larger than `0x00800000`. When
we convert the lower half to an i128 we get a negative `CompactKey`.
## Summary of Changes
Use unsigned integers when encoding into Protobuf.
## Deployment
* Prod: We disabled the interpreted proto, so no compat concerns.
* Staging: Disable the interpreted proto, do one release, and then
release the fixed version.
We do this because a negative int32 will convert to a large uint32 value
and could give
a key in the actual pageserver space. In production we would around this
by adding new
fields to the proto and deprecating the old ones, but we can make our
lives easy here.
* Pre-prod: Same as staging
Removes some unnecessary initdb arguments, and fixes Neon for MacOS
since it doesn't seem to ship a C.UTF-8 locale.
Signed-off-by: Tristan Partin <tristan@neon.tech>
Perf benchmarks produce a lot of layers.
## Summary of changes
Bumping the threshold and ignore the warning.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
storage hotfix release 2024-09-20
This storage hotfix release adds valuable metrics to pageserver.
We will only deploy this hotfix manually to a dedicated pageserver that is currently empty.
Context https://neondb.slack.com/archives/C07MU9ES6NP/p1726827244185729
Created using
```
git switch -c releases/2024-09-20-hotfix
git reset --hard origin/release
git merge ec5dce04eb
```
Merge main into release with merge commit.
This is a no-op PR which will incorporate into release branch last commits from main under their original SHA to prevent merge conflicts when doing release.
Noticed this while debugging a test failure in #8673 which only occurs
with real S3 instead of mock S3: if you authenticate to S3 via
`AWS_PROFILE`, then it requires the `HOME` env var to be set so that it
can read inside the `~/.aws` directory.
The scrubber abstraction `StorageScrubber::scrubber_cli` in
`neon_fixtures.py` would otherwise not work. My earlier PR #6556 has
done similar things for the `neon_local` wrapper.
You can try:
```
aws sso login --profile dev
export ENABLE_REAL_S3_REMOTE_STORAGE=y REMOTE_STORAGE_S3_BUCKET=neon-github-ci-tests REMOTE_STORAGE_S3_REGION=eu-central-1 AWS_PROFILE=dev
RUST_BACKTRACE=1 BUILD_TYPE=debug DEFAULT_PG_VERSION=16 ./scripts/pytest -vv --tb=short -k test_scrubber_tenant_snapshot
```
before and after this patch: this patch fixes it.
## Problem
This page had many dead links, and was confusing for folks looking for
documentation about our product.
Closes: https://github.com/neondatabase/neon/issues/8535
## Summary of changes
- Add a link to the product docs up top
- Remove dead/placeholder links
## Problem
We install and try to use `cachepot`. But it is not configured correctly
and doesn't work (after https://github.com/neondatabase/neon/pull/2290)
## Summary of changes
- Remove `cachepot`
## 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
This type of error can happen during shutdown & was triggering a circuit
breaker alert.
## Summary of changes
- Map NotIntialized::Stopped to CompactionError::ShuttingDown, so that
we may handle it cleanly
## Problem
Azure login fails in `pin-build-tools-image` workflow because the job
doesn't have the required permissions.
```
Error: Please make sure to give write permissions to id-token in the workflow.
Error: Login failed with Error: Error message: Unable to get ACTIONS_ID_TOKEN_REQUEST_URL env variable. Double check if the 'auth-type' is correct. Refer to https://github.com/Azure/login#readme for more information.
```
## Summary of changes
- Add `id-token: write` permission to `pin-build-tools-image`
- Add an input to force image tagging
- Unify pushing to Docker Hub with other registries
- Split the job into two to have less if's
part of https://github.com/neondatabase/neon/issues/8653
Disable create tablespace stmt. It turns out it requires much less
effort to do the regress test mode flag than patching the test cases,
and given that we might need to support tablespaces in the future, I
decided to add a new flag `regress_test_mode` to change the behavior of
create tablespace.
Tested manually that without setting regress_test_mode, create
tablespace will be rejected.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
Co-authored-by: Heikki Linnakangas <heikki@neon.tech>
This reverts #8076 - which was already reverted from the release branch
since forever (it would have been a breaking change to release for all
users who currently set TimeZone options). It's causing conflicts now so
we should revert it here as well.
## Problem
Latency from one cloud provider to another one is higher than within the
same cloud provider.
Some of our benchmarks are latency sensitive - we run a pgbench or psql
in the github action runner and the system under test is running in Neon
(database project).
For realistic perf tps and latency results we need to compare apples to
apples and run the database client in the same "latency distance" for
all tests.
## Summary of changes
Move job steps that test Neon databases deployed on Azure into Azure
action runners.
- bench strategy variant using azure database
- pgvector strategy variant using azure database
- pgbench-compare strategy variants using azure database
## Test run
https://github.com/neondatabase/neon/actions/runs/10314848502
## Problem
We're adding more third party dependencies to support more diverse +
realistic test cases in `test_runner/logical_repl`. I ❤️ these
tests, they are a good thing.
The slight glitch is that python packaging is hard, and some third party
python packages have issues. For example the current kafka dependency
doesn't work on latest python. We can mitigate that by only importing
these more specialized dependencies in the tests that use them.
## Summary of changes
- Move the `kafka` import into a test body, so that folks running the
regular `test_runner/regress` tests don't have to have a working kafka
client package.
## Problem
This code was to mitigate risk in
https://github.com/neondatabase/neon/pull/8427
As expected, we did not hit this code path - the new continuous updates
of gc_info are working fine, we can remove this code now.
## Summary of changes
- Remove block that double-checks retain_lsns
avoid "leaking" the completions of BackgroundPurges by:
1. switching it to TaskTracker for provided close+wait
2. stop using tokio::fs::remove_dir_all which will consume two units of
memory instead of one blocking task
Additionally, use more graceful shutdown in tests which do actually some
background cleanup.
## Problem
See
https://neondb.slack.com/archives/C03QLRH7PPD/p1723038557449239?thread_ts=1722868375.476789&cid=C03QLRH7PPD
Logical replication subscription by default use `synchronous_commit=off`
which cause problems with safekeeper
## Summary of changes
Set `synchronous_commit=on` for logical replication subscription in
test_subscriber_restart.py
## 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.
## Checklist before merging
- [ ] Do not forget to reformat commit message to not include the above
checklist
---------
Co-authored-by: Konstantin Knizhnik <knizhnik@neon.tech>
Co-authored-by: Heikki Linnakangas <heikki@neon.tech>
## Problem
Some developers build on MacOS, which doesn't have io_uring.
## Summary of changes
- Add `io_engine_for_bench`, which on linux will give io_uring or panic
if it's unavailable, and on MacOS will always panic.
We do not want to run such benchmarks with StdFs: the results aren't
interesting, and will actively waste the time of any developers who
start investigating performance before they realize they're using a
known-slow I/O backend.
Why not just conditionally compile this benchmark on linux only? Because
even on linux, I still want it to refuse to run if it can't get
io_uring.
Part of #8130, [RFC: Direct IO For Pageserver](https://github.com/neondatabase/neon/blob/problame/direct-io-rfc/docs/rfcs/034-direct-io-for-pageserver.md)
## Description
Add pageserver config for evaluating/enabling direct I/O.
- Disabled: current default, uses buffered io as is.
- Evaluate: still uses buffered io, but could do alignment checking and
perf simulation (pad latency by direct io RW to a fake file).
- Enabled: uses direct io, behavior on alignment error is configurable.
Signed-off-by: Yuchen Liang <yuchen@neon.tech>
Earlier I was thinking we'd need a (ancestor_lsn, timeline_id) ordered
list of reparented. Turns out we did not need it at all. Replace it with
an unordered hashset. Additionally refactor the reparented direct
children query out, it will later be used from more places.
Split off from #8430.
Cc: #6994
Ephemeral files cleanup on drop but did not delay shutdown, leading to
problems with restarting the tenant. The solution is as proposed:
- make ephemeral files carry the gate guard to delay `Timeline::gate`
closing
- flush in-memory layers and strong references to those on
`Timeline::shutdown`
The above are realized by making LayerManager an `enum` with `Open` and
`Closed` variants, and fail requests to modify `LayerMap`.
Additionally:
- fix too eager anyhow conversions in compaction
- unify how we freeze layers and handle errors
- optimize likely_resident_layers to read LayerFileManager hashmap
values instead of bouncing through LayerMap
Fixes: #7830
## Problem
1. Hard to correlate startup parameters with the endpoint that provided
them.
2. Some configurations are not needed in the `ProxyConfig` struct.
## Summary of changes
Because of some borrow checker fun, I needed to switch to an
interior-mutability implementation of our `RequestMonitoring` context
system. Using https://docs.rs/try-lock/latest/try_lock/ as a cheap lock
for such a use-case (needed to be thread safe).
Removed the lock of each startup message, instead just logging only the
startup params in a successful handshake.
Also removed from values from `ProxyConfig` and kept as arguments.
(needed for local-proxy config)
Timeline cancellation running in parallel with gc yields error log lines
like:
```
Gc failed 1 times, retrying in 2s: TimelineCancelled
```
They are completely harmless though and normal to occur. Therefore, only
print those messages at an info level. Still print them at all so that
we know what is going on if we focus on a single timeline.
Part of #8128.
## Problem
Currently, scrubber `scan_metadata` command will return with an error
code if the metadata on remote storage is corrupted with fatal errors.
To safely deploy this command in a cronjob, we want to differentiate
between failures while running scrubber command and the erroneous
metadata. At the same time, we also want our regression tests to catch
corrupted metadata using the scrubber command.
## Summary of changes
- Return with error code only when the scrubber command fails
- Uses explicit checks on errors and warnings to determine metadata
health in regression tests.
**Resolve conflict with `tenant-snapshot` command (after shard split):**
[`test_scrubber_tenant_snapshot`](https://github.com/neondatabase/neon/blob/yuchen/scrubber-scan-cleanup-before-prod/test_runner/regress/test_storage_scrubber.py#L23)
failed before applying 422a8443dd
- When taking a snapshot, the old `index_part.json` in the unsharded
tenant directory is not kept.
- The current `list_timeline_blobs` implementation consider no
`index_part.json` as a parse error.
- During the scan, we are only analyzing shards with highest shard
count, so we will not get a parse error. but we do need to add the
layers to tenant object listing, otherwise we will get index is
referencing a layer that is not in remote storage error.
- **Action:** Add s3_layers from `list_timeline_blobs` regardless of
parsing error
Signed-off-by: Yuchen Liang <yuchen@neon.tech>
## Problem
We lack a rust bench for the inmemory layer and delta layer write paths:
it is useful to benchmark these components independent of postgres & WAL
decoding.
Related: https://github.com/neondatabase/neon/issues/8452
## Summary of changes
- Refactor DeltaLayerWriter to avoid carrying a Timeline, so that it can
be cleanly tested + benched without a Tenant/Timeline test harness. It
only needed the Timeline for building `Layer`, so this can be done in a
separate step.
- Add `bench_ingest`, which exercises a variety of workload "shapes"
(big values, small values, sequential keys, random keys)
- Include a small uncontroversial optimization: in `freeze`, only
exhaustively walk values to assert ordering relative to end_lsn in debug
mode.
These benches are limited by drive performance on a lot of machines, but
still useful as a local tool for iterating on CPU/memory improvements
around this code path.
Anecdotal measurements on Hetzner AX102 (Ryzen 7950xd):
```
ingest-small-values/ingest 128MB/100b seq
time: [1.1160 s 1.1230 s 1.1289 s]
thrpt: [113.38 MiB/s 113.98 MiB/s 114.70 MiB/s]
Found 1 outliers among 10 measurements (10.00%)
1 (10.00%) low mild
Benchmarking ingest-small-values/ingest 128MB/100b rand: Warming up for 3.0000 s
Warning: Unable to complete 10 samples in 10.0s. You may wish to increase target time to 18.9s.
ingest-small-values/ingest 128MB/100b rand
time: [1.9001 s 1.9056 s 1.9110 s]
thrpt: [66.982 MiB/s 67.171 MiB/s 67.365 MiB/s]
Benchmarking ingest-small-values/ingest 128MB/100b rand-1024keys: Warming up for 3.0000 s
Warning: Unable to complete 10 samples in 10.0s. You may wish to increase target time to 11.0s.
ingest-small-values/ingest 128MB/100b rand-1024keys
time: [1.0715 s 1.0828 s 1.0937 s]
thrpt: [117.04 MiB/s 118.21 MiB/s 119.46 MiB/s]
ingest-small-values/ingest 128MB/100b seq, no delta
time: [425.49 ms 429.07 ms 432.04 ms]
thrpt: [296.27 MiB/s 298.32 MiB/s 300.83 MiB/s]
Found 1 outliers among 10 measurements (10.00%)
1 (10.00%) low mild
ingest-big-values/ingest 128MB/8k seq
time: [373.03 ms 375.84 ms 379.17 ms]
thrpt: [337.58 MiB/s 340.57 MiB/s 343.13 MiB/s]
Found 1 outliers among 10 measurements (10.00%)
1 (10.00%) high mild
ingest-big-values/ingest 128MB/8k seq, no delta
time: [81.534 ms 82.811 ms 83.364 ms]
thrpt: [1.4994 GiB/s 1.5095 GiB/s 1.5331 GiB/s]
Found 1 outliers among 10 measurements (10.00%)
```
## Problem
Sometimes, a layer is Covered by hasn't yet been evicted from local disk
(e.g. shortly after image layer generation). It is not good use of
resources to download these to a secondary location, as there's a good
chance they will never be read.
This follows the previous change that added layer visibility:
- #8511
Part of epic:
- https://github.com/neondatabase/neon/issues/8398
## Summary of changes
- When generating heatmaps, only include Visible layers
- Update test_secondary_downloads to filter to visible layers when
listing layers from an attached location
## Problem
In staging, we could see that occasionally tenants were wrapping their
pageserver_visible_physical_size metric past zero to 2^64.
This is harmless right now, but will matter more later when we start
using visible size in things like the /utilization endpoint.
## Summary of changes
- Add debug asserts that detect this case. `test_gc_of_remote_layers`
works as a reproducer for this issue once the asserts are added.
- Tighten up the interface around access_stats so that only Layer can
mutate it.
- In Layer, wrap calls to `record_access` in code that will update the
visible size statistic if the access implicitly marks the layer visible
(this was what caused the bug)
- In LayerManager::rewrite_layers, use the proper set_visibility layer
function instead of directly using access_stats (this is an additional
path where metrics could go bad.)
- Removed unused instances of LayerAccessStats in DeltaLayer and
ImageLayer which I noticed while reviewing the code paths that call
record_access.
## 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
We need to test the logical replication with some external consumers.
## Summary of changes
A test of the logical replication with Debezium as a consumer was added.
---------
Co-authored-by: Alexander Bayandin <alexander@neon.tech>
We don't use it for packaging, and 'poetry install' will soon error
otherwise. Also remove name and version fields as these are not required for
non-packaging mode.
#8600 missed the hunk changing index_part.json informative version.
Include it in this PR, in addition add more non-warning index_part.json
versions to scrubber.
## Problem
We have been maintaining two read paths (legacy and vectored) for a
while now. The legacy read-path was only used for cross validation in some tests.
## Summary of changes
* Tweak all tests that were using the legacy read path to use the
vectored read path instead
* Remove the read path dispatching based on the pageserver configs
* Remove the legacy read path code
We will be able to remove the single blob io code in
`pageserver/src/tenant/blob_io.rs` when https://github.com/neondatabase/neon/issues/7386 is complete.
Closes https://github.com/neondatabase/neon/issues/8005
Currently, we do not have facilities to persistently block GC on a
tenant for whatever reason. We could do a tenant configuration update,
but that is risky for generation numbers and would also be transient.
Introduce a `gc_block` facility in the tenant, which manages per
timeline blocking reasons.
Additionally, add HTTP endpoints for enabling/disabling manual gc
blocking for a specific timeline. For debugging, individual tenant
status now includes a similar string representation logged when GC is
skipped.
Cc: #6994
Add dry-run mode that does not produce any image layer + delta layer. I
will use this code to do some experiments and see how much space we can
reclaim for tenants on staging. Part of
https://github.com/neondatabase/neon/issues/8002
* Add dry-run mode that runs the full compaction process without
updating the layer map. (We never call finish on the writers and the
files will be removed before exiting the function).
* Add compaction statistics and print them at the end of compaction.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## 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>
Currently if `GET
/v1/tenant/x/timeline/y?force-await-initial-logical-size=true` is
requested for a root timeline created within the current pageserver
session, the request handler panics hitting the debug assertion. These
timelines will always have an accurate (at initdb import) calculated
logical size. Fix is to never attempt prioritizing timeline size
calculation if we already have an exact value.
Split off from #8528.
## Problem
In some cases, a deadlock between `build-and-test` and
`trigger-e2e-tests` workflows can happen:
```
Build and Test
Canceling since a deadlock for concurrency group 'Build and Test-8600/merge-anysha' was detected between 'top level workflow' and 'trigger-e2e-tests'
```
I don't understand the reason completely, probably `${{ github.workflow
}}` got evaluated to the same value and somehow caused the issue.
We don't need to limit concurrency for `trigger-e2e-tests`
workflow.
See
https://neondb.slack.com/archives/C059ZC138NR/p1722869486708179?thread_ts=1722869027.960029&cid=C059ZC138NR
## Problem
We don't trigger e2e tests for draft PRs, but we do trigger them once a
PR is in the "Ready for review" state.
Sometimes, a PR can be marked as "Ready for review" before we finish
image building. In such cases, triggering e2e tests fails.
## Summary of changes
- Make `trigger-e2e-tests` job poll status of `promote-images` job from
the build-and-test workflow for the last commit. And trigger only if the
status is `success`
- Remove explicit image checking from the workflow
- Add `concurrency` for `triggere-e2e-tests` workflow to make it
possible to cancel jobs in progress (if PR moves from "Draft" to "Ready
for review" several times in a row)
## Problem
PR #7992 was merged without correspondent changes in Postgres submodules
and this is why test_oid_overflow.py is failed now.
## Summary of changes
Bump Postgres versions
## 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.
## Checklist before merging
- [ ] Do not forget to reformat commit message to not include the above
checklist
Co-authored-by: Konstantin Knizhnik <knizhnik@neon.tech>
## Problem
There is an unused safekeeper option `partial_backup_enabled`.
`partial_backup_enabled` was implemented in #6530, but this option was
always turned into enabled in #8022.
If you intended to keep this option for a specific reason, I will close
this PR.
## Summary of changes
I removed an unused safekeeper option `partial_backup_enabled`.
We've noticed increased memory usage with the latest release. Drain the
joinset of `page_service` connection handlers to avoid leaking them
until shutdown. An alternative would be to use a TaskTracker.
TaskTracker was not discussed in original PR #8339 review, so not hot
fixing it in here either.
part of https://github.com/neondatabase/neon/issues/8002
## Summary of changes
Add a `SplitImageWriter` that automatically splits image layer based on
estimated target image layer size. This does not consider compression
and we might need a better metrics.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
Co-authored-by: Arpad Müller <arpad-m@users.noreply.github.com>
We need both compaction and gc lock for gc-compaction. The lock order
should be the same everywhere, otherwise there could be a deadlock where
A waits for B and B waits for A.
We also had a double-lock issue. The compaction lock gets acquired in
the outer `compact` function. Note that the unit tests directly call
`compact_with_gc`, and therefore not triggering the issue.
## Summary of changes
Ensure all places acquire compact lock and then gc lock. Remove an extra
compact lock acqusition.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
Currently, our backward compatibility tests only look one release back.
That means, for example, that when we switch on image layer compression
by default, we'll test reading of uncompressed layers for one release,
and then stop doing it. When we make an index_part.json format change,
we'll test against the old format for a week, then stop (unless we write
separate unit tests for each old format).
The reality in the field is that data in old formats will continue to
exist for weeks/months/years. When we make major format changes, we
should retain examples of the old format data, and continuously verify
that the latest code can still read them.
This test uses contents from a new path in the public S3 bucket,
`compatibility-data-snapshots/`. It is populated by hand. The first
important artifact is one from before we switch on compression, so that
we will keep testing reads of uncompressed data. We will generate more
artifacts ahead of other key changes, like when we update remote storage
format for archival timelines.
Closes: https://github.com/neondatabase/cloud/issues/15576
This commit tries to fix regular load spikes on staging, caused by too
many eviction and partial upload operations running at the same time.
Usually it was hapenning after restart, for partial backup the load was
delayed.
- Add a semaphore for evictions (2 permits by default)
- Rename `resident_since` to `evict_not_before` and smooth out the curve
by using random duration
- Use random duration in partial uploads as well
related to https://github.com/neondatabase/neon/issues/6338
some discussion in
https://neondb.slack.com/archives/C033RQ5SPDH/p1720601531744029
Makes `flush_frozen_layer` add a barrier to the upload queue and makes
it wait for that barrier to be reached until it lets the flushing be
completed.
This gives us backpressure and ensures that writes can't build up in an
unbounded fashion.
Fixes#7317
Chaos injection bridges the gap between automated testing (where we do
lots of different things with small, short-lived tenants), and staging
(where we do many fewer things, but with larger, long-lived tenants).
This PR adds a first type of chaos which isn't really very chaotic: it's
live migration of tenants between healthy pageservers. This nevertheless
provides continuous checks that things like clean, prompt shutdown of
tenants works for realistically deployed pageservers with realistically
large tenants.
## Problem
Previously, when we do a timeline deletion, shards will delete layers
that belong to an ancestor. That is not a correctness issue, because
when we delete a timeline, we're always deleting it from all shards, and
destroying data for that timeline is clearly fine.
However, there exists a race where one shard might start doing this
deletion while another shard has not yet received the deletion request,
and might try to access an ancestral layer. This creates ambiguity over
the "all layers referenced by my index should always exist" invariant,
which is important to detecting and reporting corruption.
Now that we have a GC mode for clearing up ancestral layers, we can rely
on that to clean up such layers, and avoid deleting them right away.
This makes things easier to reason about: there are now no cases where a
shard will delete a layer that belongs to a ShardIndex other than
itself.
## Summary of changes
- Modify behavior of RemoteTimelineClient::delete_all
- Add `test_scrubber_physical_gc_timeline_deletion` to exercise this
case
- Tweak AWS SDK config in the scrubber to enable retries. Motivated by
seeing the test for this feature encounter some transient "service
error" S3 errors (which are probably nothing to do with the changes in
this PR)
## Problem
`allure_attach_from_dir` method might create `tar.zst` archives even
if `--alluredir` is not set (i.e. Allure results collection is disabled)
## Summary of changes
- Don't run `allure_attach_from_dir` if `--alluredir` is not set
part of https://github.com/neondatabase/neon/issues/8002
Due to the limitation of the current layer map implementation, we cannot
directly replace a layer. It's interpreted as an insert and a deletion,
and there will be file exist error when renaming the newly-created layer
to replace the old layer. We work around that by changing the end key of
the image layer. A long-term fix would involve a refactor around the
layer file naming. For delta layers, we simply skip layers with the same
key range produced, though it is possible to add an extra key as an
alternative solution.
* The image layer range for the layers generated from gc-compaction will
be Key::MIN..(Key..MAX-1), to avoid being recognized as an L0 delta
layer.
* Skip existing layers if it turns out that we need to generate a layer
with the same persistent key in the same generation.
Note that it is possible that the newly-generated layer has different
content from the existing layer. For example, when the user drops a
retain_lsn, the compaction could have combined or dropped some records,
therefore creating a smaller layer than the existing one. We discard the
"optimized" layer for now because we cannot deal with such rewrites
within the same generation.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
Co-authored-by: Christian Schwarz <christian@neon.tech>
## Problem
We recently added a "visibility" state to layers, but nothing
initializes it.
Part of:
- #8398
## Summary of changes
- Add a dependency on `range-set-blaze`, which is used as a fast
incrementally updated alternative to KeySpace. We could also use this to
replace the internals of KeySpaceRandomAccum if we wanted to. Writing a
type that does this kind of "BtreeMap & merge overlapping entries" thing
isn't super complicated, but no reason to write this ourselves when
there's a third party impl available.
- Add a function to layermap to calculate visibilities for each layer
- Add a function to Timeline to call into layermap and then apply these
visibilities to the Layer objects.
- Invoke the calculation during startup, after image layer creations,
and when removing branches. Branch removal and image layer creation are
the two ways that a layer can go from Visible to Covered.
- Add unit test & benchmark for the visibility calculation
- Expose `pageserver_visible_physical_size` metric, which should always
be <= `pageserver_remote_physical_size`.
- This metric will feed into the /v1/utilization endpoint later: the
visible size indicates how much space we would like to use on this
pageserver for this tenant.
- When `pageserver_visible_physical_size` is greater than
`pageserver_resident_physical_size`, this is a sign that the tenant has
long-idle branches, which result in layers that are visible in
principle, but not used in practice.
This does not keep visibility hints up to date in all cases:
particularly, when creating a child timeline, any previously covered
layers will not get marked Visible until they are accessed.
Updates after image layer creation could be implemented as more of a
special case, but this would require more new code: the existing depth
calculation code doesn't maintain+yield the list of deltas that would be
covered by an image layer.
## Performance
This operation is done rarely (at startup and at timeline deletion), so
needs to be efficient but not ultra-fast.
There is a new `visibility` bench that measures runtime for a synthetic
100k layers case (`sequential`) and a real layer map (`real_map`) with
~26k layers.
The benchmark shows runtimes of single digit milliseconds (on a ryzen
7950). This confirms that the runtime shouldn't be a problem at startup
(as we already incur S3-level latencies there), but that it's slow
enough that we definitely shouldn't call it more often than necessary,
and it may be worthwhile to optimize further later (things like: when
removing a branch, only bother scanning layers below the branchpoint)
```
visibility/sequential time: [4.5087 ms 4.5894 ms 4.6775 ms]
change: [+2.0826% +3.9097% +5.8995%] (p = 0.00 < 0.05)
Performance has regressed.
Found 24 outliers among 100 measurements (24.00%)
2 (2.00%) high mild
22 (22.00%) high severe
min: 0/1696070, max: 93/1C0887F0
visibility/real_map time: [7.0796 ms 7.0832 ms 7.0871 ms]
change: [+0.3900% +0.4505% +0.5164%] (p = 0.00 < 0.05)
Change within noise threshold.
Found 4 outliers among 100 measurements (4.00%)
3 (3.00%) high mild
1 (1.00%) high severe
min: 0/1696070, max: 93/1C0887F0
visibility/real_map_many_branches
time: [4.5285 ms 4.5355 ms 4.5434 ms]
change: [-1.0012% -0.8004% -0.5969%] (p = 0.00 < 0.05)
Change within noise threshold.
```
Before, we had four versions of linux-raw-sys in our dependency graph:
```
linux-raw-sys@0.1.4
linux-raw-sys@0.3.8
linux-raw-sys@0.4.13
linux-raw-sys@0.6.4
```
now it's only two:
```
linux-raw-sys@0.4.13
linux-raw-sys@0.6.4
```
The changes in this PR are minimal. In order to get to its state one
only has to update procfs in Cargo.toml to 0.16 and do `cargo update -p
tempfile -p is-terminal -p prometheus`.
# Motivation
The working theory for hung systemd during PS deploy
(https://github.com/neondatabase/cloud/issues/11387) is that leftover
walredo processes trigger a race condition.
In https://github.com/neondatabase/neon/pull/8150 I arranged that a
clean Tenant shutdown does actually kill its walredo processes.
But many prod machines don't manage to shut down all their tenants until
the 10s systemd timeout hits and, presumably, triggers the race
condition in systemd / the Linux kernel that causes the frozen systemd
# Solution
This PR bolts on a rather ugly mechanism to shut down tenant managers
out of order 8s after we've received the SIGTERM from systemd.
# Changes
- add a global registry of `Weak<WalRedoManager>`
- add a special thread spawned during `shutdown_pageserver` that sleeps
for 8s, then shuts down all redo managers in the registry and prevents
new redo managers from being created
- propagate the new failure mode of tenant spawning throughout the code
base
- make sure shut down tenant manager results in
PageReconstructError::Cancelled so that if Timeline::get calls come in
after the shutdown, they do the right thing
## Problem
In https://github.com/neondatabase/neon/pull/8241 I've accidentally
removed `create-test-report` dependency on `benchmarks` job
## Summary of changes
- Run `create-test-report` after `benchmarks` job
Uses the newly added APIs from #8541 named `stream_tenants_generic` and
`stream_objects_with_retries` and extends them with
`list_objects_with_retries_generic` and
`stream_tenant_timelines_generic` to migrate the `find-garbage` command
of the scrubber to `GenericRemoteStorage`.
Part of https://github.com/neondatabase/neon/issues/7547
## Problem
This code was confusing, untested and covered:
- an impossible case, where intent state is AttacheStale (we never do
this)
- a rare edge case (going from AttachedMulti to Attached), which we were
not testing, and in any case the pageserver internally does the same
Tenant reset in this transition as it would do if we incremented
generation.
Closes: https://github.com/neondatabase/neon/issues/8367
## Summary of changes
- Simplify the logic to only skip incrementing the generation if the
location already has the expected generation and the exact same mode.
In some cases, we can get a negative metric for replication_delay_bytes.
My best guess from all the research I've done is that we evaluate
pg_last_wal_receive_lsn() before pg_last_wal_replay_lsn(), and that by
the time everything is said and done, the replay LSN has advanced past
the receive LSN. In this case, our lag can effectively be modeled as
0 due to the speed of the WAL reception and replay.
Since the introduction of sharding, the protocol handling loop in
`handle_pagerequests` cannot know anymore which concrete
`Tenant`/`Timeline` object any of the incoming `PagestreamFeMessage`
resolves to.
In fact, one message might resolve to one `Tenant`/`Timeline` while
the next one may resolve to another one.
To avoid going to tenant manager, we added the `shard_timelines` which
acted as an ever-growing cache that held timeline gate guards open for
the lifetime of the connection.
The consequence of holding the gate guards open was that we had to be
sensitive to every cached `Timeline::cancel` on each interaction with
the network connection, so that Timeline shutdown would not have to wait
for network connection interaction.
We can do better than that, meaning more efficiency & better
abstraction.
I proposed a sketch for it in
* https://github.com/neondatabase/neon/pull/8286
and this PR implements an evolution of that sketch.
The main idea is is that `mod page_service` shall be solely concerned
with the following:
1. receiving requests by speaking the protocol / pagestream subprotocol
2. dispatching the request to a corresponding method on the correct
shard/`Timeline` object
3. sending response by speaking the protocol / pagestream subprotocol.
The cancellation sensitivity responsibilities are clear cut:
* while in `page_service` code, sensitivity to page_service cancellation
is sufficient
* while in `Timeline` code, sensitivity to `Timeline::cancel` is
sufficient
To enforce these responsibilities, we introduce the notion of a
`timeline::handle::Handle` to a `Timeline` object that is checked out
from a `timeline::handle::Cache` for **each request**.
The `Handle` derefs to `Timeline` and is supposed to be used for a
single async method invocation on `Timeline`.
See the lengthy doc comment in `mod handle` for details of the design.
part of https://github.com/neondatabase/neon/issues/8002
For child branches, we will pull the image of the modified keys from the
parant into the child branch, which creates a full history for
generating key retention. If there are not enough delta keys, the image
won't be wrote eventually, and we will only keep the deltas inside the
child branch. We could avoid the wasteful work to pull the image from
the parent if we can know the number of deltas in advance, in the future
(currently we always pull image for all modified keys in the child
branch)
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
We run regression tests on `release` & `debug` builds for each of the
three supported Postgres versions (6 in total).
With upcoming ARM support and Postgres 17, the number of jobs will jump
to 16, which is a lot.
See the internal discussion here:
https://neondb.slack.com/archives/C033A2WE6BZ/p1722365908404329
## Summary of changes
- Run `regress-tests` job in debug builds only with the latest Postgres
version
- Do not do `debug` builds on release branches
part of https://github.com/neondatabase/neon/issues/8184
# Problem
We want to bypass PS PageCache for all data block reads, but
`compact_level0_phase1` currently uses `ValueRef::load` to load the WAL
records from delta layers.
Internally, that maps to `FileBlockReader:read_blk` which hits the
PageCache
[here](e78341e1c2/pageserver/src/tenant/block_io.rs (L229-L236)).
# Solution
This PR adds a mode for `compact_level0_phase1` that uses the
`MergeIterator` for reading the `Value`s from the delta layer files.
`MergeIterator` is a streaming k-merge that uses vectored blob_io under
the hood, which bypasses the PS PageCache for data blocks.
Other notable changes:
* change the `DiskBtreeReader::into_stream` to buffer the node, instead
of holding a `PageCache` `PageReadGuard`.
* Without this, we run out of page cache slots in
`test_pageserver_compaction_smoke`.
* Generally, `PageReadGuard`s aren't supposed to be held across await
points, so, this is a general bugfix.
# Testing / Validation / Performance
`MergeIterator` has not yet been used in production; it's being
developed as part of
* https://github.com/neondatabase/neon/issues/8002
Therefore, this PR adds a validation mode that compares the existing
approach's value iterator with the new approach's stream output, item by
item.
If they're not identical, we log a warning / fail the unit/regression
test.
To avoid flooding the logs, we apply a global rate limit of once per 10
seconds.
In any case, we use the existing approach's value.
Expected performance impact that will be monitored in staging / nightly
benchmarks / eventually pre-prod:
* with validation:
* increased CPU usage
* ~doubled VirtualFile read bytes/second metric
* no change in disk IO usage because the kernel page cache will likely
have the pages buffered on the second read
* without validation:
* slightly higher DRAM usage because each iterator participating in the
k-merge has a dedicated buffer (as opposed to before, where compactions
would rely on the PS PageCaceh as a shared evicting buffer)
* less disk IO if previously there were repeat PageCache misses (likely
case on a busy production Pageserver)
* lower CPU usage: PageCache out of the picture, fewer syscalls are made
(vectored blob io batches reads)
# Rollout
The new code is used with validation mode enabled-by-default.
This gets us validation everywhere by default, specifically in
- Rust unit tests
- Python tests
- Nightly pagebench (shouldn't really matter)
- Staging
Before the next release, I'll merge the following aws.git PR that
configures prod to continue using the existing behavior:
* https://github.com/neondatabase/aws/pull/1663
# Interactions With Other Features
This work & rollout should complete before Direct IO is enabled because
Direct IO would double the IOPS & latency for each compaction read
(#8240).
# Future Work
The streaming k-merge's memory usage is proportional to the amount of
memory per participating layer.
But `compact_level0_phase1` still loads all keys into memory for
`all_keys_iter`.
Thus, it continues to have active memory usage proportional to the
number of keys involved in the compaction.
Future work should replace `all_keys_iter` with a streaming keys
iterator.
This PR has a draft in its first commit, which I later reverted because
it's not necessary to achieve the goal of this PR / issue #8184.
Change Azure storage configuration to point to new variables/secrets. They have
the `_NEW` suffix in order not to disrupt any tests while we complete the
switch.
Part of #8128, followup to #8480. closes#8421.
Enable scrubber to optionally post metadata scan health results to
storage controller.
Signed-off-by: Yuchen Liang <yuchen@neon.tech>
Part of #8128, followed by #8502.
## Problem
Currently we lack mechanism to alert unhealthy `scan_metadata` status if
we start running this scrubber command as part of a cronjob. With the
storage controller client introduced to storage scrubber in #8196, it is
viable to set up alert by storing health status in the storage
controller database.
We intentionally do not store the full output to the database as the
json blobs potentially makes the table really huge. Instead, only a
health status and a timestamp recording the last time metadata health
status is posted on a tenant shard.
Signed-off-by: Yuchen Liang <yuchen@neon.tech>
This tests the ability to push into ACR using OIDC. Proved it worked by running slightly modified YAML.
In `promote-images` we push the following images `neon compute-tools {vm-,}compute-node-{v14,v15,v16}` into `neoneastus2`.
https://github.com/neondatabase/cloud/issues/14640
## Problem
We don't allow regular end-users to use `k8s-pod` provisioner,
but we still use it in nightly benchmarks
## Summary of changes
- Remove `provisioner` input from `neon-create-project` action, use
`k8s-neonvm` as a default provioner
- Change `neon-` platform prefix to `neonvm-`
- Remove `neon-captest-freetier` and `neon-captest-new` as we already
have their `neonvm` counterparts
Add two new functions `stream_objects_with_retries` and
`stream_tenants_generic` and use them in the `find-large-objects`
subcommand, migrating it to `remote_storage`.
Also adds the `size` field to the `ListingObject` struct.
Part of #7547
If compression is enabled, we currently try compressing each image
larger than a specific size and if the compressed version is smaller, we
write that one, otherwise we use the uncompressed image. However, this
might sometimes be a wasteful process, if there is a substantial amount
of images that don't compress well.
The compression metrics added in #8420
`pageserver_compression_image_in_bytes_total` and
`pageserver_compression_image_out_bytes_total` are well designed for
answering the question how space efficient the total compression process
is end-to-end, which helps one to decide whether to enable it or not.
To answer the question of how much waste there is in terms of trial
compression, so CPU time, we add two metrics:
* one about the images that have been trial-compressed (considered), and
* one about the images where the compressed image has actually been
written (chosen).
There is different ways of weighting them, like for example one could
look at the count, or the compressed data. But the main contributor to
compression CPU usage is amount of data processed, so we weight the
images by their *uncompressed* size. In other words, the two metrics
are:
* `pageserver_compression_image_in_bytes_considered`
* `pageserver_compression_image_in_bytes_chosen`
Part of #5431
## Problem
Old storage buckets can contain a lot of tenants that aren't known to
the control plane at all, because they belonged to test jobs that get
their control plane state cleaned up shortly after running.
In general, it's somewhat unsafe to purge these, as it's hard to
distinguish "control plane doesn't know about this, so it's garbage"
from "control plane said it didn't know about this, which is a bug in
the scrubber, control plane, or API URL configured".
However, the most common case is that we see only a small husk of a
tenant in S3 from a specific old behavior of the software, for example:
- We had a bug where heatmaps weren't deleted on tenant delete
- When WAL DR was first deployed, we didn't delete initdb.tar.zst on
tenant deletion
## Summary of changes
- Add a KnownBug variant for the garbage reason
- Include such cases in the "safe" deletion mode (`--mode=deleted`)
- Add code that inspects tenants missing in control plane to identify
cases of known bugs (this is kind of slow, but should go away once we've
cleaned all these up)
- Add an additional `-min-age` safety check similar to physical GC,
where even if everything indicates objects aren't needed, we won't
delete something that has been modified too recently.
---------
Co-authored-by: Yuchen Liang <70461588+yliang412@users.noreply.github.com>
Co-authored-by: Arpad Müller <arpad-m@users.noreply.github.com>
## Problem
The secondary download HTTP API is meant to return 200 if the download
is complete, and 202 if it is still in progress. In #8198 the download
implementation was changed to drop out with success early if it
over-runs a time budget, which resulted in 200 responses for incomplete
downloads.
This breaks storcon_cli's "tenant-warmup" command, which uses the OK
status to indicate download complete.
## Summary of changes
- Only return 200 if we get an Ok() _and_ the progress stats indicate
the download is complete.
## Problem
We need to test logical replication with 3rd-party tools regularly.
## Summary of changes
Added a test using ClickHouse as a client
Co-authored-by: Alexander Bayandin <alexander@neon.tech>
Uses the Stream based `list_streaming` function added by #8457 in tenant
deletion, as suggested in https://github.com/neondatabase/neon/pull/7932#issuecomment-2150480180 .
We don't have to worry about retries, as the function is wrapped inside
an outer retry block. If there is a retryable error either during the
listing or during deletion, we just do a fresh start.
Also adds `+ Send` bounds as they are required by the
`delete_tenant_remote` function.
update pg_jsonschema extension to v 0.3.1
update pg_graphql extension to v1.5.7
update pgx_ulid extension to v0.1.5
update pg_tiktoken extension, patch Cargo.toml to use new pgrx
In general, replace:
* 'lfc_approximate_working_set_size' with
* 'lfc_approximate_working_set_size_windows'
For the "main" metrics that are actually scraped and used internally,
the old one is just marked as deprecated.
For the "autoscaling" metrics, we're not currently using the old one, so
we can get away with just replacing it.
Also, for the user-visible metrics we'll only store & expose a few
different time windows, to avoid making the UI overly busy or bloating
our internal metrics storage.
But for the autoscaling-related scraper, we aren't storing the metrics,
and it's useful to be able to programmatically operate on the trendline
of how WSS increases (or doesn't!) with window size. So there, we can
just output datapoints for each minute.
Part of neondatabase/autoscaling#872
See also https://www.notion.so/neondatabase/cca38138fadd45eaa753d81b859490c6
## Storage & Compute release 2024-07-22
This PR has so many commits because the release branch diverged from `main`.
Details https://neondb.slack.com/archives/C033A2WE6BZ/p1721650938949059?thread_ts=1721308848.034069&cid=C033A2WE6BZ
The commit range that is truly new since the last storage release are the the `main` commit which I cherry-picked using this command
```
git cherry-pick 8a8b83df27383a07bb7dbba519325c15d2f46357..4e547e6
```
PR #8299 has switched the storage scrubber to use
`DefaultCredentialsChain`. Now we do this for `remote_storage`, as it
allows us to use `remote_storage` from inside kubernetes. Most of the
diff is due to `GenericRemoteStorage::from_config` becoming `async fn`.
This adds an archival_config endpoint to the pageserver. Currently it
has no effect, and always "works", but later the intent is that it will
make a timeline archived/unarchived.
- [x] add yml spec
- [x] add endpoint handler
Part of https://github.com/neondatabase/neon/issues/8088
## Problem
There are some swagger errors in `pageserver/src/http/openapi_spec.yml`
```
Error 431 15000 Object includes not allowed fields
Error 569 3100401 should always have a 'required'
Error 569 15000 Object includes not allowed fields
Error 1111 10037 properties members must be schemas
```
## Summary of changes
Fixed the above errors.
## Problem
After a shard split, the pageserver leaves the ancestor shard's content
in place. It may be referenced by child shards, but eventually child
shards will de-reference most ancestor layers as they write their own
data and do GC. We would like to eventually clean up those ancestor
layers to reclaim space.
## Summary of changes
- Extend the physical GC command with `--mode=full`, which includes
cleaning up unreferenced ancestor shard layers
- Add test `test_scrubber_physical_gc_ancestors`
- Remove colored log output: in testing this is irritating ANSI code
spam in logs, and in interactive use doesn't add much.
- Refactor storage controller API client code out of storcon_client into
a `storage_controller/client` crate
- During physical GC of ancestors, call into the storage controller to
check that the latest shards seen in S3 reflect the latest state of the
tenant, and there is no shard split in progress.
We're removing the usage of this long-meaningless config field in
https://github.com/neondatabase/aws/pull/1599
Once that PR has been deployed to staging and prod, we can merge this
PR.
## Problem
My prior PR https://github.com/neondatabase/neon/pull/8422
caused leftovers in the GitHub action runner work directory with root
permission.
As an example see here
https://github.com/neondatabase/neon/actions/runs/10001857641/job/27646237324#step:3:37
To work-around we install vanilla postgres as non-root using deb
packages in /home/nonroot user directory
## Summary of changes
- since we cannot use root we install the deb pkgs directly and create
symbolic links for psql, pgbench and libs in expected places
- continue jobs an aws even if azure jobs fail (because this region is
currently unreliable)
Successor of #8288 , just enable zstd in tests. Also adds a test that
creates easily compressable data.
Part of #5431
---------
Co-authored-by: John Spray <john@neon.tech>
Co-authored-by: Joonas Koivunen <joonas@neon.tech>
The error means that manager exited earlier than `ResidenceGuard` and
it's not unexpected with current deletion implementation. This commit
changes log level to reduse noise.
Use the k-merge iterator in the compaction process to reduce memory
footprint.
part of https://github.com/neondatabase/neon/issues/8002
## Summary of changes
* refactor the bottom-most compaction code to use k-merge iterator
* add Send bound on some structs as it is used across the await points
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
Co-authored-by: Arpad Müller <arpad-m@users.noreply.github.com>
We have an issue that some partial uploaded segments can be actually
missing in remote storage. I found this issue when was looking at the
logs in staging, and it can be triggered by failed uploads:
1. Code tries to upload `SEG_TERM_LSN_LSN_sk5.partial`, but receives
error from S3
2. The failed attempt is saved to `segments` vec
3. After some time, the code tries to upload
`SEG_TERM_LSN_LSN_sk5.partial` again
4. This time the upload is successful and code calls `gc()` to delete
previous uploads
5. Since new object and old object share the same name, uploaded data
gets deleted from remote storage
This commit fixes the issue by patching `gc()` not to delete objects
with the same name as currently uploaded.
---------
Co-authored-by: Arpad Müller <arpad-m@users.noreply.github.com>
## Problem
Ahead of enabling eviction in the field, where it will become the
normal/default mode, let's enable it by default throughout our tests in
case any issues become visible there.
## Summary of changes
- Make default `extra_opts` for safekeepers enable offload & deletion
- Set low timeouts in `extra_opts` so that tests running for tens of
seconds have a chance to hit some of these background operations.
## Problem
These tests time out ~1 in 50 runs when in debug mode.
There is no indication of a real issue: they're just wrappers that have
large numbers of individual tests contained within on pytest case.
## Summary of changes
- Bump pg_regress timeout from 600 to 900s
- Bump test_isolation timeout from 300s (default) to 600s
In future it would be nice to break out these tests to run individual
cases (or batches thereof) as separate tests, rather than this monolith.
## Problem
This test would occasionally fail its metric check. This could happen in
the rare case that the nodes had all been restarted before their most
recent eviction.
The metric check was added in
https://github.com/neondatabase/neon/pull/8348
## Summary of changes
- Check metrics before each restart, accumulate into a bool that we
assert on at the end of the test
When `NeonEnv.from_repo_dir` was introduced, storage controller stored
its
state exclusively `attachments.json`.
Since then, it has moved to using Postgres, which stores its state in
`storage_controller_db`.
But `NeonEnv.from_repo_dir` wasn't adjusted to do this.
This PR rectifies the situation.
Context for this is failures in
`test_pageserver_characterize_throughput_with_n_tenants`
CF:
https://neondb.slack.com/archives/C033RQ5SPDH/p1721035799502239?thread_ts=1720901332.293769&cid=C033RQ5SPDH
Notably, `from_repo_dir` is also used by the backwards- and
forwards-compatibility.
Thus, the changes in this PR affect those tests as well.
However, it turns out that the compatibility snapshot already contains
the `storage_controller_db`.
Thus, it should just work and in fact we can remove hacks like
`fixup_storage_controller`.
Follow-ups created as part of this work:
* https://github.com/neondatabase/neon/issues/8399
* https://github.com/neondatabase/neon/issues/8400
## Problem
There are something wrong in the comment of
`control_plane/src/broker.rs` and `control_plane/src/pageserver.rs`
## Summary of changes
Fixed the comment about component name and their data path in
`control_plane/src/broker.rs` and `control_plane/src/pageserver.rs`.
## Problem
We lack insight into:
- How much of a tenant's physical size is image vs. delta layers
- Average sizes of image vs. delta layers
- Total layer counts per timeline, indicating size of index_part object
As well as general observability love, this is motivated by
https://github.com/neondatabase/neon/issues/6738, where we need to
define some sensible thresholds for storage amplification, and using
total physical size may not work well (if someone does a lot of DROPs
then it's legitimate for the physical-synthetic ratio to be huge), but
the ratio between image layer size and delta layer size may be a better
indicator of whether we're generating unreasonable quantities of image
layers.
## Summary of changes
- Add pageserver_layer_bytes and pageserver_layer_count metrics,
labelled by timeline and `kind` (delta or image)
- Add & subtract these with LayerInner's lifetime.
I'm intentionally avoiding using a generic metric RAII guard object, to
avoid bloating LayerInner: it already has all the information it needs
to update metric on new+drop.
This test reproduces the case of a writer creating a deep stack of L0
layers. It uses realistic layer sizes and writes several gigabytes of
data, therefore runs as a performance test although it is validating
memory footprint rather than performance per se.
It acts a regression test for two recent fixes:
- https://github.com/neondatabase/neon/pull/8401
- https://github.com/neondatabase/neon/pull/8391
In future it will demonstrate the larger improvement of using a k-merge
iterator for L0 compaction (#8184)
This test can be extended to enforce limits on the memory consumption of
other housekeeping steps, by restarting the pageserver and then running
other things to do the same "how much did RSS increase" measurement.
Existing tenants and some selection of layers might produce duplicated
keys. Add tests to ensure the k-merge iterator handles it correctly. We
also enforced ordering of the k-merge iterator to put images before
deltas.
part of https://github.com/neondatabase/neon/issues/8002
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
Co-authored-by: Arpad Müller <arpad-m@users.noreply.github.com>
## Problem
We want to run performance tests on all supported cloud providers.
We want to run most tests on the postgres version which is default for
new projects in production, currently (July 24) this is postgres version
16
## Summary of changes
- change default postgres version for some (performance) tests to 16
(which is our default for new projects in prod anyhow)
- add azure region to pgbench_compare jobs
- add azure region to pgvector benchmarking jobs
- re-used project `weathered-snowflake-88107345` was prepared with 1
million embeddings running on 7 minCU 7 maxCU in azure region to compare
with AWS region (pgvector indexing and hnsw queries)
- see job pgbench-pgvector
- Note we now have a 11 environments combinations where we run
pgbench-compare and 5 are for k8s-pod (deprecated) which we can remove
in the future once auto-scaling team approves.
## Logs
A current run with the changes from this pull request is running here
https://github.com/neondatabase/neon/actions/runs/9972096222
Note that we currently expect some failures due to
- https://github.com/neondatabase/neon/issues/8275
- instability of projects on azure region
## Problem
When a tenant creates a new timeline that they will treat as their
'main' history,
it is awkward to permanently retain an 'old main' timeline as its
ancestor. Currently
this is necessary because it is forbidden to delete a timeline which has
descendents.
## Summary of changes
A new pageserver API is proposed to 'adopt' data from a parent timeline
into
one of its children, such that the link between ancestor and child can
be severed,
leaving the parent in a state where it may then be deleted.
---------
Co-authored-by: Joonas Koivunen <joonas@neon.tech>
## Problem
ValueRef is an unnecessarily large structure, because it carries a
cursor. L0 compaction currently instantiates gigabytes of these under
some circumstances.
## Summary of changes
- Carry a ref to the parent layer instead of a cursor, and construct a
cursor on demand.
This reduces RSS high watermark during L0 compaction by about 20%.
## Problem
The `evictions_with_low_residence_duration` is used as an indicator of
cache thrashing. However, there are situations where it is quite
legitimate to only have a short residence during compaction, where a
delta is downloaded, used to generate an image layer, and then
discarded. This can lead to false positive alerts.
## Summary of changes
- Only track low residence duration for layers that have been accessed
at least once (compaction doesn't count as an access). This will give us
a metric that indicates thrashing on layers that the _user_ is using,
rather than those we're downloading for housekeeping purposes.
Once we add "layer visibility" as an explicit property of layers, this
can also be used as a cleaner condition (residence of non-visible layers
should never be alertable)
## Problem
close https://github.com/neondatabase/neon/issues/8389
## Summary of changes
A quick mitigation for tenants with fast writes. We compact at most 60
delta layers at a time, expecting a memory footprint of 15GB. We will
pick the oldest 60 L0 layers.
This should be a relatively safe change so no test is added. Question is
whether to make this parameter configurable via tenant config.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
Co-authored-by: John Spray <john@neon.tech>
- `horizon` is a confusing term, it's not at all obvious that this means
space-based retention limit, rather than the total GC history limit.
Rename to `GcCutoffs::space`.
- `pitr` is less confusing, but still an unecessary level of indirection
from what we really mean: a time-based condition. The fact that we use
that that time-history for Point In Time Recovery doesn't mean we have
to refer to time as "pitr" everywhere. Rename to `GcCutoffs::time`.
As described in #8385, the likely source for flakiness in
test_tenant_creation_fails is the following sequence of events:
1. test instructs the storage controller to create the tenant
2. storage controller adds the tenant and persists it to the database.
issues a creation request
3. the pageserver restarts with the failpoint disabled
4. storage controller's background reconciliation still wants to create
the tenant
5. pageserver gets new request to create the tenant from background
reconciliation
This commit just avoids the storage controller entirely. It has its own
set of issues, as the re-attach request will obviously not include the
tenant, but it's still useful to test for non-existence of the tenant.
The generation is also not optional any more during tenant attachment.
If you omit it, the pageserver yields an error. We change the signature
of `tenant_attach` to reflect that.
Alternative to #8385Fixes#8266
## Problem
This structure was in an Arc<> unnecessarily, making it harder to reason
about its lifetime (i.e. it was superficially possible for LayerManager
to outlive timeline, even though no code used it that way)
## Summary of changes
- Remove the Arc<>
Right now timeline detach ancestor reports an error (409, "no ancestor")
on a new attempt after successful completion. This makes it troublesome
for storage controller retries. Fix it to respond with `200 OK` as if
the operation had just completed quickly.
Additionally, the returned timeline identifiers in the 200 OK response
are now ordered so that responses between different nodes for error
comparison are done by the storage controller added in #8353.
Design-wise, this PR introduces a new strategy for accessing the latest
uploaded IndexPart:
`RemoteTimelineClient::initialized_upload_queue(&self) ->
Result<UploadQueueAccessor<'_>, NotInitialized>`. It should be a more
scalable way to query the latest uploaded `IndexPart` than to add a
query method for each question directly on `RemoteTimelineClient`.
GC blocking will need to be introduced to make the operation fully
idempotent. However, it is idempotent for the cases demonstrated by
tests.
Cc: #6994
## Problem
Pageserver GC uses a size-based condition (GC "horizon" in addition to
time-based "PITR").
Eventually we plan to retire the size-based condition:
https://github.com/neondatabase/neon/issues/6374
Currently, we always apply the more conservative of the two, meaning
that tenants always retain at least 64MB of history (default horizon),
even after a very long time has passed. This is particularly acute in
cases where someone has dropped tables/databases, and then leaves a
database idle: the horizon can prevent GCing very large quantities of
historical data (we already account for this in synthetic size by
ignoring gc horizon).
We're not entirely removing GC horizon right now because we don't want
to 100% rely on standby_horizon for robustness of physical replication,
but we can tweak our logic to avoid retaining that 64MB LSN length
indefinitely.
## Summary of changes
- Rework `Timeline::find_gc_cutoffs`, with new logic:
- If there is no PITR set, then use `DEFAULT_PITR_INTERVAL` (1 week) to
calculate a time threshold. Retain either the horizon or up to that
thresholds, whichever requires less data.
- When there is a PITR set, and we have unambiguously resolved the
timestamp to an LSN, then ignore the GC horizon entirely. For typical
PITRs (1 day, 1 week), this will still easily retain enough data to
avoid stressing read only replicas.
The key property we end up with, whether a PITR is set or not, is that
after enough time has passed, our GC cutoff on an idle timeline will
catch up with the last_record_lsn.
Using `DEFAULT_PITR_INTERVAL` is a bit of an arbitrary hack, but this
feels like it isn't really worth the noise of exposing in TenantConfig.
We could just make it a different named constant though. The end-end
state will be that there is no gc_horizon at all, and that tenants with
pitr_interval=0 would truly retain no history, so this constant would go
away.
Currently storage controller does not support forwarding timeline detach
ancestor requests to pageservers. Add support for forwarding `PUT
.../:tenant_id/timelines/:timeline_id/detach_ancestor`. Implement the
support mostly as is, because the timeline detach ancestor will be made
(mostly) idempotent in future PR.
Cc: #6994
## Problem
Right now if there are too many running xacts to be restored from CLOG
at replica startup,
then replica is not trying to restore them and wait for non-overflown
running-xacs WAL record from primary.
But if primary is not active, then replica will not start at all.
Too many running xacts can be caused by transactions with large number
of subtractions.
But right now it can be also cause by two reasons:
- Lack of shutdown checkpoint which updates `oldestRunningXid` (because
of immediate shutdown)
- nextXid alignment on 1024 boundary (which cause loosing ~1k XIDs on
each restart)
Both problems are somehow addressed now.
But we have existed customers with "sparse" CLOG and lack of
checkpoints.
To be able to start RO replicas for such customers I suggest to add GUC
which allows replica to start even in case of subxacts overflow.
## Summary of changes
Add `neon.running_xacts_overflow_policy` with the following values:
- ignore: restore from CLOG last N XIDs and accept connections
- skip: do not restore any XIDs from CXLOGbut still accept connections
- wait: wait non-overflown running xacts record from primary node
## 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.
## Checklist before merging
- [ ] Do not forget to reformat commit message to not include the above
checklist
---------
Co-authored-by: Konstantin Knizhnik <knizhnik@neon.tech>
## Problem
This test would sometimes violate the min resident size during disk
eviction and fail due to the generate warning log.
Disk usage candidate collection only takes into account active tenants.
However, the statvfs call takes into account the entire tenants
directory, which includes tenants which haven't become active yet.
After re-starting the pageserver, disk usage eviction may kick in
*before* both tenants have become active. Hence, the logic will try to satisfy
thedisk usage requirements by evicting everything belonging to the active
tenant, and hence violating the tenant minimum resident size.
## Summary of changes
Allow the warning
## Problem
new clippy warnings on nightly.
## Summary of changes
broken up each commit by warning type.
1. Remove some unnecessary refs.
2. In edition 2024, inference will default to `!` and not `()`.
3. Clippy complains about doc comment indentation
4. Fix `Trait + ?Sized` where `Trait: Sized`.
5. diesel_derives triggering `non_local_defintions`
## Problem
We already back off on compaction retries, but the impact of a failing
compaction can be so great that backing off up to 300s isn't enough. The
impact is consuming a lot of I/O+CPU in the case of image layer
generation for large tenants, and potentially also leaking disk space.
Compaction failures are extremely rare and almost always indicate a bug,
frequently a bug that will not let compaction to proceed until it is
fixed.
Related: https://github.com/neondatabase/neon/issues/6738
## Summary of changes
- Introduce a CircuitBreaker type
- Add a circuit breaker for compaction, with a policy that after 5
failures, compaction will not be attempted again for 24 hours.
- Add metrics that we can alert on: any >0 value for
`pageserver_circuit_breaker_broken_total` should generate an alert.
- Add a test that checks this works as intended.
Couple notes to reviewers:
- Circuit breakers are intrinsically a defense-in-depth measure: this is
not the solution to any underlying issues, it is just a general
mitigation for "unknown unknowns" that might be encountered in future.
- This PR isn't primarily about writing a perfect CircuitBreaker type:
the one in this PR is meant to be just enough to mitigate issues in
compaction, and make it easy to monitor/alert on these failures. We can
refine this type in future as/when we want to use it elsewhere.
Implement decompression of images for vectored reads.
This doesn't implement support for still treating blobs as uncompressed
with the bits we reserved for compression, as we have removed that
functionality in #8300 anyways.
Part of #5431
We need to pass on the configured compression param during image layer
generation.
This was an oversight of #8106, and the likely cause why #8288 didn't
bring any interesting regressions.
Part of https://github.com/neondatabase/neon/issues/5431
## Problem
I need `neon_superuser` to be allowed to create snapshots for
replication tests
## Summary of changes
Adds a migration that grants these functions to neon_superuser
Rewrite streaming vectored read planner to be a separate struct. The API
is designed to produce batches around `max_read_size` instead of exactly
less than that so that `handle_XX` returns one batch a time.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
In anticipation of later adding a really nice drain+delete API, I
initially only added an intentionally basic `/drop` API that is just
about usable for deleting nodes in a pinch, but requires some ugly
storage controller restarts to persuade it to restart secondaries.
## Summary of changes
I started making a few tiny fixes, and ended up writing the delete
API...
- Quality of life nit: ordering of node + tenant listings in storcon_cli
- Papercut: Fix the attach_hook using the wrong operation type for
reporting slow locks
- Make Service::spawn tolerate `generation_pageserver` columns that
point to nonexistent node IDs. I started out thinking of this as a
general resilience thing, but when implementing the delete API I
realized it was actually a legitimate end state after the delete API is
called (as that API doesn't wait for all reconciles to succeed).
- Add a `DELETE` API for nodes, which does not gracefully drain, but
does reschedule everything. This becomes safe to use when the system is
in any state, but will incur availability gaps for any tenants that
weren't already live-migrated away. If tenants have already been
drained, this becomes a totally clean + safe way to decom a node.
- Add a test and a storcon_cli wrapper for it
This is meant to be a robust initial API that lets us remove nodes
without doing ugly things like restarting the storage controller -- it's
not quite a totally graceful node-draining routine yet. There's more
work in https://github.com/neondatabase/neon/issues/8333 to get to our
end-end state.
## Problem
Follow up to https://github.com/neondatabase/neon/pull/8335, to improve
observability of how many evict/restores we are doing.
## Summary of changes
- Add `safekeeper_eviction_events_started_total` and
`safekeeper_eviction_events_completed_total`, with a "kind" label of
evict or restore. This gives us rates, and also ability to calculate how
many are in progress.
- Generalize SafekeeperMetrics test type to use the same helpers as
pageserver, and enable querying any metric.
- Read the new metrics at the end of the eviction test.
## Problem
SeqWait::would_wait_for returns Ok in the case when we would not wait
for the sequence number and Err otherwise.
ReconcilerWaiter::get_status uses it the wrong way around. This can
cause the storage controller to go into a busy loop
and make it look unavailable to the k8s controller.
## Summary of changes
Use `SeqWait::would_wait_for` correctly.
`trace_read_requests` is a per `Tenant`-object option.
But the `handle_pagerequests` loop doesn't know which
`Tenant` object (i.e., which shard) the request is for.
The remaining use of the `Tenant` object is to check `tenant.cancel`.
That check is incorrect [if the pageserver hosts multiple
shards](https://github.com/neondatabase/neon/issues/7427#issuecomment-2220577518).
I'll fix that in a future PR where I completely eliminate the holding
of `Tenant/Timeline` objects across requests.
See [my code RFC](https://github.com/neondatabase/neon/pull/8286) for
the
high level idea.
Note that we can always bring the tracing functionality if we need it.
But since it's actually about logging the `page_service` wire bytes,
it should be a `page_service`-level config option, not per-Tenant.
And for enabling tracing on a single connection, we can implement
a `set pageserver_trace_connection;` option.
Set core rmilit to ulimited in compute_ctl, so that all child processes
inherit it. We could also set rlimit in relevant startup script, but
that way we would depend on external setup and might inadvertently
disable it again (core dumping worked in pods, but not in VMs with
inittab-based startup).
## Problem
- The condition for eviction is not time-based: it is possible for a
timeline to be restored in response to a client, that client times out,
and then as soon as the timeline is restored it is immediately evicted
again.
- There is no delay on eviction at startup of the safekeeper, so when it
starts up and sees many idle timelines, it does many evictions which
will likely be immediately restored when someone uses the timeline.
## Summary of changes
- Add `eviction_min_resident` parameter, and use it in
`ready_for_eviction` to avoid evictions if the timeline has been
resident for less than this period.
- This also implicitly delays evictions at startup for
`eviction_min_resident`
- Set this to a very low number for the existing eviction test, which
expects immediate eviction.
The default period is 15 minutes. The general reasoning for that is that
in the worst case where we thrash ~10k timelines on one safekeeper,
downloading 16MB for each one, we should set a period that would not
overwhelm the node's bandwidth.
Part of https://github.com/neondatabase/neon/issues/8002. This pull
request adds a k-merge iterator for bottom-most compaction.
## Summary of changes
* Added back lsn_range / key_range in delta layer inner. This was
removed due to https://github.com/neondatabase/neon/pull/8050, but added
back because iterators need that information to process lazy loading.
* Added lazy-loading k-merge iterator.
* Added iterator wrapper as a unified iterator type for image+delta
iterator.
The current status and test should cover the use case for L0 compaction
so that the L0 compaction process can bypass page cache and have a fixed
amount of memory usage. The next step is to integrate this with the new
bottom-most compaction.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
Co-authored-by: Christian Schwarz <christian@neon.tech>
Removes the `ImageCompressionAlgorithm::DisabledNoDecompress` variant.
We now assume any blob with the specific bits set is actually a
compressed blob.
The `ImageCompressionAlgorithm::Disabled` variant still remains and is
the new default.
Reverts large parts of #8238 , as originally intended in that PR.
Part of #5431
## Problem
This test incorrectly assumed that a post-split compaction would only
drop content. This was easily destabilized by any changes to image
generation rules.
## Summary of changes
- Before split, do a full image layer generation pass, to guarantee that
post-split compaction should only drop data, never create it.
- Fix the force_image_layer_creation mode of compaction that we use from
tests like this: previously it would try and generate image layers even
if one already existed with the same layer key, which caused compaction
to fail.
## Problem
#7809 - we do not support sslnegotiation=direct
#7810 - we do not support negotiating down the protocol extensions.
## Summary of changes
1. Same as postgres, check the first startup packet byte for tls header
`0x16`, and check the ALPN.
2. Tell clients using protocol >3.0 to downgrade
I want to fix bugs in `page_service`
([issue](https://github.com/neondatabase/neon/issues/7427)) and the
`import basebackup` / `import wal` stand in the way / make the
refactoring more complicated.
We don't use these methods anyway in practice, but, there have been some
objections to removing the functionality completely.
So, this PR preserves the existing functionality but moves it into the
HTTP management API.
Note that I don't try to fix existing bugs in the code, specifically not
fixing
* it only ever worked correctly for unsharded tenants
* it doesn't clean up on error
All errors are mapped to `ApiError::InternalServerError`.
## Problem
Slack thread:
https://neondb.slack.com/archives/C033RQ5SPDH/p1720511577862519
We're seeing OOMs in staging on a pageserver that has
l0_flush.mode=Direct enabled.
There's a strong correlation between jumps in `maxrss_kb` and
`pageserver_timeline_ephemeral_bytes`, so, it's quite likely that
l0_flush.mode=Direct is the culprit.
Notably, the expected max memory usage on that staging server by the
l0_flush.mode=Direct is ~2GiB but we're seeing as much as 24GiB max RSS
before the OOM kill.
One hypothesis is that we're dropping the semaphore permit before all
the dirtied pages have been flushed to disk. (The flushing to disk
likely happens in the fsync inside the `.finish()` call, because we're
using ext4 in data=ordered mode).
## Summary of changes
Hold the permit until after we're done with `.finish()`.
part of https://github.com/neondatabase/cloud/issues/14024, k8s does not
always have a volume available for logging, and I'm running into weird
permission errors... While I could spend time figuring out how to create
temp directories for logging, I think it would be better to just disable
file logging as k8s containers are ephemeral and we cannot retrieve
anything on the fs after the container gets removed.
## Summary of changes
`PAGESERVER_DISABLE_FILE_LOGGING=1` -> file logging disabled
Signed-off-by: Alex Chi Z <chi@neon.tech>
This tweaks the rows-to-JSON rendering logic in order to avoid
allocating 0-sized temporary vectors and later growing them
to insert elements.
As the exact size is known in advance, both vectors can be built
with an exact capacity upfront. This will avoid further vector
growing/reallocation in the rendering hotpath.
Signed-off-by: Luca BRUNO <lucab@lucabruno.net>
## Problem
In https://github.com/neondatabase/neon/pull/8161, we changed the path
to Neon artefacts by adding commit sha to it, but we missed adding these
changes to `promote-compatibility-data` job that we use for
backward/forward- compatibility testing.
## Summary of changes
- Add commit sha to `promote-compatibility-data`
## Summary of changes
Increase the `assert_size_approx_equal` threshold to avoid flakiness of
`test_lsn_lease_size`. Still needs more investigation to fully resolve
#8293.
- Also set `autovacuum=off` for the endpoint we are running in the test.
Signed-off-by: Yuchen Liang <yuchen@neon.tech>
## Problem
`test_timeline_size_quota_on_startup` assumed that writing data beyond
the size limit would always be blocked. This is not so: the limit is
only enforced if feedback makes it back from the pageserver to the
safekeeper + compute.
Closes: https://github.com/neondatabase/neon/issues/6562
## Summary of changes
- Modify the test to wait for the pageserver to catch up. The size limit
was never actually being enforced robustly, the original version of this
test was just writing much more than 30MB and about 98% of the time
getting lucky such that the feedback happened to arrive before the tests
for loop was done.
- If the test fails, log the logical size as seen by the pageserver.
## Problem
Debug-mode runs of test_pg_regress are rather slow since
https://github.com/neondatabase/neon/pull/8105, and occasionally exceed
their 600s timeout.
## Summary of changes
- Use 8MiB layer files, avoiding large ephemeral layers
On a hetzner AX102, this takes the runtime from 230s to 190s. Which
hopefully will be enough to get the runtime on github runners more
reliably below its 600s timeout.
This has the side benefit of exercising more of the pageserver stack
(including compaction) under a workload that exercises a more diverse
set of postgres functionality than most of our tests.
## Problem
We currently use 'immediate' mode in the most commonly used shutdown
path, when the control plane calls a `compute_ctl` API to terminate
Postgres inside compute without waiting for the actual pod / VM
termination. Yet, 'immediate' shutdown doesn't create a shutdown
checkpoint and ROs have bad times figuring out the list of running xacts
during next start.
## Summary of changes
Use 'fast' mode, which creates a shutdown checkpoint that is important
for ROs to get a list of running xacts faster instead of going through
the CLOG. On the control plane side, we poll this `compute_ctl`
termination API for 10s, it should be enough as we don't really write
any data at checkpoint time. If it times out, we anyway switch to the
slow k8s-based termination.
See https://www.postgresql.org/docs/current/server-shutdown.html for the
list of modes and signals.
The default VM shutdown hook already uses `fast` mode, see [1]
[1]
c9fd8d7693/vm-image-spec.yaml (L30-L31)
Related to #6211
## Problem
LSN Leases introduced in #8084 is a new API that is made shard-aware
from day 1. To support ephemeral endpoint in #7994 without linking
Postgres C API against `compute_ctl`, part of the sharding needs to
reside in `utils`.
## Summary of changes
- Create a new `shard` module in utils crate.
- Move more interface related part of tenant sharding API to utils and
re-export them in pageserver_api.
Signed-off-by: Yuchen Liang <yuchen@neon.tech>
## Problem
Rarely, a dbdir entry can exist with no `relmap_file_key` data. This
causes compaction to fail, because it assumes that if the database
exists, then so does the relmap file.
Basebackup already handled this using a boolean to record whether such a
key exists, but `collect_keyspace` didn't.
## Summary of changes
- Respect the flag for whether a relfilemap exists in collect_keyspace
- The reproducer for this issue will merge separately in
https://github.com/neondatabase/neon/pull/8232
These tests will help verify that replication, both physical and
logical, works as expected in Neon.
Co-authored-by: Sasha Krassovsky <sasha@neon.tech>
Allows a process to run without blocking program execution, which can be
useful for certain test scenarios.
Co-authored-by: Sasha Krassovsky <sasha@neon.tech>
## Problem
- Resident memory on long running pageserver processes tends to climb:
memory fragmentation is suspected.
- Total resident memory may be a limiting factor for running on smaller
nodes.
## Summary of changes
- As a low-energy experiment, switch the pageserver to use jemalloc (not
a net-new dependency, proxy already use it)
- Decide at end of week whether to revert before next release.
## Problem
Sparse keyspaces were constructed with ranges out of order: this didn't break things obviously, but meant that users of KeySpace functions that assume ordering would assert out.
Closes https://github.com/neondatabase/neon/issues/8277
## Summary of changes
make sure the sparse keyspace has ordered keyspace parts
The find-large-objects scrubber subcommand is quite fast if you run it
in an environment with low latency to the S3 bucket (say an EC2 instance
in the same region). However, the higher the latency gets, the slower
the command becomes. Therefore, add a concurrency param and make it
parallelized. This doesn't change that general relationship, but at
least lets us do multiple requests in parallel and therefore hopefully
faster.
Running with concurrency of 64 (default):
```
2024-07-05T17:30:22.882959Z INFO lazy_load_identity [...]
[...]
2024-07-05T17:30:28.289853Z INFO Scanned 500 shards. [...]
```
With concurrency of 1, simulating state before this PR:
```
2024-07-05T17:31:43.375153Z INFO lazy_load_identity [...]
[...]
2024-07-05T17:33:51.987092Z INFO Scanned 500 shards. [...]
```
In other words, to list 500 shards, speed is increased from 2:08 minutes
to 6 seconds.
Follow-up of #8257, part of #5431
Improve parsing of the `ImageCompressionAlgorithm` enum to allow level
customization like `zstd(1)`, as strum only takes `Default::default()`,
i.e. `None` as the level.
Part of #5431
## Problem
test_subscriber_restart has quit large failure rate'
https://neonprod.grafana.net/d/fddp4rvg7k2dcf/regression-test-failures?orgId=1&var-test_name=test_subscriber_restart&var-max_count=100&var-restrict=false
I can be caused by too small timeout (5 seconds) to wait until changes
are propagated.
Related to #8097
## Summary of changes
Increase timeout to 30 seconds.
## 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.
## Checklist before merging
- [ ] Do not forget to reformat commit message to not include the above
checklist
Co-authored-by: Konstantin Knizhnik <knizhnik@neon.tech>
## Problem
We want to be able to test how our infrastructure reacts on segfaults in
Postgres (for example, we collect cores, and get some required
logs/metrics, etc)
## Summary of changes
- Add `trigger_segfauls` function to `neon_test_utils` to trigger a
segfault in Postgres
- Add `trigger_panic` function to `neon_test_utils` to trigger SIGABRT
(by using `elog(PANIC, ...))
- Fix cleanup logic in regression tests in endpoint crashed
## Problem
Assume a timeline with the following workload: very slow ingest of
updates to a small number of keys that fit within the same partition (as decided by
`KeySpace::partition`). These tenants will create small L0 layers since due to time
based rolling, and, consequently, the L1 layers will also be small.
Currently, by default, we need to ingest 512 MiB of WAL before checking
if an image layer is required. This scheme works fine under the assumption that L1s are roughly of
checkpoint distance size, but as the first paragraph explained, that's not the case for all workloads.
## Summary of changes
Check if new image layers are required at least once every checkpoint timeout interval.
## Problem
Safekeepers left running for a long time use a lot of memory (up to the
point of OOMing, on small nodes) for deleted timelines, because the
`Timeline` struct is kept alive as a guard against recreating deleted
timelines.
Closes: https://github.com/neondatabase/neon/issues/6810
## Summary of changes
- Create separate tombstones that just record a ttid and when the
timeline was deleted.
- Add a periodic housekeeping task that cleans up tombstones older than
a hardcoded TTL (24h)
I think this also makes https://github.com/neondatabase/neon/pull/6766
un-needed, as the tombstone is also checked during deletion.
I considered making the overall timeline map use an enum type containing
active or deleted, but having a separate map of tombstones avoids
bloating that map, so that calls like `get()` can still go straight to a
timeline without having to walk a hashmap that also contains tombstones.
## Problem
This test directly manages locations on pageservers and configuration of
an endpoint. However, it did not switch off the parts of the storage
controller that attempt to do the same: occasionally, the test would
fail in a strange way such as a compute failing to accept a
reconfiguration request.
## Summary of changes
- Wire up the storage controller's compute notification hook to a no-op
handler
- Configure the tenant's scheduling policy to Stop.
## Problem
See #7466
## Summary of changes
Implement algorithm descried in
https://hal.science/hal-00465313/document
Now new GUC is added:
`neon.wss_max_duration` which specifies size of sliding window (in
seconds). Default value is 1 hour.
It is possible to request estimation of working set sizes (within this
window using new function
`approximate_working_set_size_seconds`. Old function
`approximate_working_set_size` is preserved for backward compatibility.
But its scope is also limited by `neon.wss_max_duration`.
Version of Neon extension is changed to 1.4
## 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.
## Checklist before merging
- [ ] Do not forget to reformat commit message to not include the above
checklist
---------
Co-authored-by: Konstantin Knizhnik <knizhnik@neon.tech>
Co-authored-by: Matthias van de Meent <matthias@neon.tech>
Part of #7497, closes#8071. (accidentally closed#8208, reopened here)
## Problem
After the changes in #8084, we need synthetic size to also account for
leased LSNs so that users do not get free retention by running a small
ephemeral endpoint for a long time.
## Summary of changes
This PR integrates LSN leases into the synthetic size calculation. We
model leases as read-only branches started at the leased LSN (except it
does not have a timeline id).
Other changes:
- Add new unit tests testing whether a lease behaves like a read-only
branch.
- Change `/size_debug` response to include lease point in the SVG
visualization.
- Fix `/lsn_lease` HTTP API to do proper parsing for POST.
Signed-off-by: Yuchen Liang <yuchen@neon.tech>
Co-authored-by: Joonas Koivunen <joonas@neon.tech>
Co-authored-by: Christian Schwarz <christian@neon.tech>
Adds a find-large-objects subcommand to the scrubber to allow listing
layer objects larger than a specific size.
To be used like:
```
AWS_PROFILE=dev REGION=us-east-2 BUCKET=neon-dev-storage-us-east-2 cargo run -p storage_scrubber -- find-large-objects --min-size 250000000 --ignore-deltas
```
Part of #5431
## Problem
When generations were new, these messages were an important way of
noticing if something unexpected was going on. We found some real issues
when investigating tests that unexpectedly tripped them.
At time has gone on, this code is now pretty battle-tested, and as we do
more live migrations etc, it's fairly normal to see the occasional
message from a node with a stale generation.
At this point the cognitive load on developers to selectively allow-list
these logs outweighs the benefit of having them at warn severity.
Closes: https://github.com/neondatabase/neon/issues/8080
## Summary of changes
- Downgrade "Dropped remote consistent LSN updates" and "Dropping stale
deletions" messages to INFO
- Remove all the allow-list entries for these logs.
## Problem
`pg-clients` workflow looks different from the main `build-and-test`
workflow for historical reasons (it was my very first task at Neon, and
back then I wasn't really familiar with the rest of the CI pipelines).
This PR unifies `pg-clients` workflow with `build-and-test`
## Summary of changes
- Rename `pg_clients.yml` to `pg-clients.yml`
- Run the workflow on changes in relevant files
- Create Allure report for tests
- Send slack notifications to `#on-call-qa-staging-stream` channel
(instead of `#on-call-staging-stream`)
- Update Client libraries once we're here
## Problem
I'd like to keep this in the tree since it might be useful in prod as
well. It's a bit too noisy as is and missing the lsn.
## Summary of changes
Add an lsn field and and increase the rate limit duration.
## Problem
Currently, if you need to rename a job and the job is listed in [branch
protection
rules](https://github.com/neondatabase/neon/settings/branch_protection_rules),
the PR won't be allowed to merge.
## Summary of changes
- Add `conclusion` job that fails if any of its dependencies don't
finish successfully
## Problem
If there's a quota error, it makes sense to cache it for a short window
of time. Many clients do not handle database connection errors
gracefully, so just spam retry 🤡
## Summary of changes
Updates the node_info cache to support storing console errors. Store
console errors if they cannot be retried (using our own heuristic.
should only trigger for quota exceeded errors).
## Problem
The metrics we have today aren't convenient for planning around the
impact of timeline archival on costs.
Closes: https://github.com/neondatabase/neon/issues/8108
## Summary of changes
- Add metric `pageserver_archive_size`, which indicates the logical
bytes of data which we would expect to write into an archived branch.
- Add metric `pageserver_pitr_history_size`, which indicates the
distance between last_record_lsn and the PITR cutoff.
These metrics are somewhat temporary: when we implement #8088 and
associated consumption metric changes, these will reach a final form.
For now, an "archived" branch is just any branch outside of its parent's
PITR window: later, archival will become an explicit state (which will
_usually_ correspond to falling outside the parent's PITR window).
The overall volume of timeline metrics is something to watch, but we are
removing many more in https://github.com/neondatabase/neon/pull/8245
than this PR is adding.
I'd like to add some constraints to the layer map we generate in tests.
(1) is the layer map that the current compaction algorithm will produce.
There is a property that for all delta layer, all delta layer overlaps
with it on the LSN axis will have the same LSN range.
(2) is the layer map that cannot be produced with the legacy compaction
algorithm.
(3) is the layer map that will be produced by the future
tiered-compaction algorithm. The current validator does not allow that
but we can modify the algorithm to allow it in the future.
## Summary of changes
Add a validator to check if the layer map is valid and refactor the test
cases to include delta layer start/end LSN.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
Co-authored-by: Christian Schwarz <christian@neon.tech>
## Problem
We record detailed histograms for all page_service op types, which
mostly aren't very interesting, but make our prometheus scrapes huge.
Closes: #8223
## Summary of changes
- Only track GetPageAtLsn histograms on a per-timeline granularity. For
all other operation types, rely on existing node-wide histograms.
we want to run some specific pagebench test cases on dedicated hardware
to get reproducible results
run1: 1 client per tenant => characterize throughput with n tenants.
- 500 tenants
- scale 13 (200 MB database)
- 1 hour duration
- ca 380 GB layer snapshot files
run2.singleclient: 1 client per tenant => characterize latencies
run2.manyclient: N clients per tenant => characterize throughput
scalability within one tenant.
- 1 tenant with 1 client for latencies
- 1 tenant with 64 clients because typically for a high number of
connections we recommend the connection pooler
which by default uses 64 connections (for scalability)
- scale 136 (2048 MB database)
- 20 minutes each
PR #8106 was created with the assumption that no blob is larger than
`256 MiB`. Due to #7852 we have checking for *writes* of blobs larger
than that limit, but we didn't have checking for *reads* of such large
blobs: in theory, we could be reading these blobs every day but we just
don't happen to write the blobs for some reason.
Therefore, we now add a warning for *reads* of such large blobs as well.
To make deploying compression less dangerous, we therefore only assume a
blob is compressed if the compression setting is present in the config.
This also means that we can't back out of compression once we enabled
it.
Part of https://github.com/neondatabase/neon/issues/5431
## Problem
test_location_conf_churn fails on log errors when it tries to shutdown a
pageserver immediately after starting a tenant attach, like this:
https://neon-github-public-dev.s3.amazonaws.com/reports/pr-8224/9761000525/index.html#/testresult/15fb6beca5c7327c
```
shutdown:shutdown{tenant_id=35f5c55eb34e7e5e12288c5d8ab8b909 shard_id=0000}:timeline_shutdown{timeline_id=30936747043353a98661735ad09cbbfe shutdown_mode=FreezeAndFlush}: failed to freeze and flush: cannot flush frozen layers when flush_loop is not running, state is Exited\n')
```
This is happening because Tenant::shutdown fires its cancellation token
early if the tenant is not fully attached by the time shutdown is
called, so the flush loop is shutdown by the time we try and flush.
## Summary of changes
- In the early-cancellation case, also set the shutdown mode to Hard to
skip trying to do a flush that will fail.
## Problem
GitHub Actions complain that we use actions that depend on deprecated
Node 16:
```
Node.js 16 actions are deprecated. Please update the following actions to use Node.js 20: docker/setup-buildx-action@v2
```
But also, the latest `docker/setup-buildx-action` fails with the following
error:
```
/nvme/actions-runner/_work/_actions/docker/setup-buildx-action/v3/webpack:/docker-setup-buildx/node_modules/@actions/cache/lib/cache.js:175
throw new Error(`Path Validation Error: Path(s) specified in the action for caching do(es) not exist, hence no cache is being saved.`);
^
Error: Path Validation Error: Path(s) specified in the action for caching do(es) not exist, hence no cache is being saved.
at Object.rejected (/nvme/actions-runner/_work/_actions/docker/setup-buildx-action/v3/webpack:/docker-setup-buildx/node_modules/@actions/cache/lib/cache.js:175:1)
at Generator.next (<anonymous>)
at fulfilled (/nvme/actions-runner/_work/_actions/docker/setup-buildx-action/v3/webpack:/docker-setup-buildx/node_modules/@actions/cache/lib/cache.js:29:1)
```
We can work this around by setting `cache-binary: false` for `uses:
docker/setup-buildx-action@v3`
## Summary of changes
- Update `docker/setup-buildx-action` from `v2` to `v3`, set
`cache-binary: false`
- Update `docker/login-action` from `v2` to `v3`
- Update `docker/build-push-action` from `v4`/`v5` to `v6`
All the code to ensure the WAL record lands at a page boundary was
unnecessary for reproducing the original problem. In fact, it's a pretty
basic test that checks that outbound replication (= neon as publisher)
still works after restarting the endpoint. It just used to be very
broken before commit 5ceccdc7de, which also added this test.
To verify that:
1. Check out commit f3af5f4660 (because the next commit, 7dd58e1449,
fixed the same bug in a different way, making it infeasible to revert
the bug fix in an easy way)
2. Revert the bug fix from commit 5ceccdc7de with this:
```
diff --git a/pgxn/neon/walproposer_pg.c b/pgxn/neon/walproposer_pg.c
index 7debb6325..9f03bbd99 100644
--- a/pgxn/neon/walproposer_pg.c
+++ b/pgxn/neon/walproposer_pg.c
@@ -1437,8 +1437,10 @@ XLogWalPropWrite(WalProposer *wp, char *buf, Size nbytes, XLogRecPtr recptr)
*
* https://github.com/neondatabase/neon/issues/5749
*/
+#if 0
if (!wp->config->syncSafekeepers)
XLogUpdateWalBuffers(buf, recptr, nbytes);
+#endif
while (nbytes > 0)
{
```
3. Run the test_wal_page_boundary_start regression test. It fails, as
expected
4. Apply this commit to the test, and run it again. It still fails, with
the same error mentioned in issue #5749:
```
PG:2024-06-30 20:49:08.805 GMT [1248196] STATEMENT: START_REPLICATION SLOT "sub1" LOGICAL 0/0 (proto_version '4', origin 'any', publication_names '"pub1"')
PG:2024-06-30 21:37:52.567 GMT [1467972] LOG: starting logical decoding for slot "sub1"
PG:2024-06-30 21:37:52.567 GMT [1467972] DETAIL: Streaming transactions committing after 0/1532330, reading WAL from 0/1531C78.
PG:2024-06-30 21:37:52.567 GMT [1467972] STATEMENT: START_REPLICATION SLOT "sub1" LOGICAL 0/0 (proto_version '4', origin 'any', publication_names '"pub1"')
PG:2024-06-30 21:37:52.567 GMT [1467972] LOG: logical decoding found consistent point at 0/1531C78
PG:2024-06-30 21:37:52.567 GMT [1467972] DETAIL: There are no running transactions.
PG:2024-06-30 21:37:52.567 GMT [1467972] STATEMENT: START_REPLICATION SLOT "sub1" LOGICAL 0/0 (proto_version '4', origin 'any', publication_names '"pub1"')
PG:2024-06-30 21:37:52.568 GMT [1467972] ERROR: could not find record while sending logically-decoded data: invalid contrecord length 312 (expected 6) at 0/1533FD8
```
## Problem
See https://github.com/neondatabase/cloud/issues/14289
and PR #8210
## Summary of changes
Add test for problems fixed in #8210
## 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.
## Checklist before merging
- [ ] Do not forget to reformat commit message to not include the above
checklist
---------
Co-authored-by: Konstantin Knizhnik <knizhnik@neon.tech>
## Problem
Some of the Nightly benchmarks fail with the error
```
+ /tmp/neon/pg_install/v14/bin/pgbench --version
/tmp/neon/pg_install/v14/bin/pgbench: error while loading shared libraries: libpq.so.5: cannot open shared object file: No such file or directory
```
Originally, we added the `pgbench --version` call to check that
`pgbench` is installed and to fail earlier if it's not.
The failure happens because we don't have `LD_LIBRARY_PATH` set for
every job, and it also affects `psql` command.
We can move it to `actions/run-python-test-set` so as not to duplicate
code (as it already have `LD_LIBRARY_PATH` set).
## Summary of changes
- Remove `pgbench --version` call
- Move `psql` commands to common `actions/run-python-test-set`
part of https://github.com/neondatabase/neon/issues/7418
# Motivation
(reproducing #7418)
When we do an `InMemoryLayer::write_to_disk`, there is a tremendous
amount of random read I/O, as deltas from the ephemeral file (written in
LSN order) are written out to the delta layer in key order.
In benchmarks (https://github.com/neondatabase/neon/pull/7409) we can
see that this delta layer writing phase is substantially more expensive
than the initial ingest of data, and that within the delta layer write a
significant amount of the CPU time is spent traversing the page cache.
# High-Level Changes
Add a new mode for L0 flush that works as follows:
* Read the full ephemeral file into memory -- layers are much smaller
than total memory, so this is afforable
* Do all the random reads directly from this in memory buffer instead of
using blob IO/page cache/disk reads.
* Add a semaphore to limit how many timelines may concurrently do this
(limit peak memory).
* Make the semaphore configurable via PS config.
# Implementation Details
The new `BlobReaderRef::Slice` is a temporary hack until we can ditch
`blob_io` for `InMemoryLayer` => Plan for this is laid out in
https://github.com/neondatabase/neon/issues/8183
# Correctness
The correctness of this change is quite obvious to me: we do what we did
before (`blob_io`) but read from memory instead of going to disk.
The highest bug potential is in doing owned-buffers IO. I refactored the
API a bit in preliminary PR
https://github.com/neondatabase/neon/pull/8186 to make it less
error-prone, but still, careful review is requested.
# Performance
I manually measured single-client ingest performance from `pgbench -i
...`.
Full report:
https://neondatabase.notion.site/2024-06-28-benchmarking-l0-flush-performance-e98cff3807f94cb38f2054d8c818fe84?pvs=4
tl;dr:
* no speed improvements during ingest, but
* significantly lower pressure on PS PageCache (eviction rate drops to
1/3)
* (that's why I'm working on this)
* noticable but modestly lower CPU time
This is good enough for merging this PR because the changes require
opt-in.
We'll do more testing in staging & pre-prod.
# Stability / Monitoring
**memory consumption**: there's no _hard_ limit on max `InMemoryLayer`
size (aka "checkpoint distance") , hence there's no hard limit on the
memory allocation we do for flushing. In practice, we a) [log a
warning](23827c6b0d/pageserver/src/tenant/timeline.rs (L5741-L5743))
when we flush oversized layers, so we'd know which tenant is to blame
and b) if we were to put a hard limit in place, we would have to decide
what to do if there is an InMemoryLayer that exceeds the limit.
It seems like a better option to guarantee a max size for frozen layer,
dependent on `checkpoint_distance`. Then limit concurrency based on
that.
**metrics**: we do have the
[flush_time_histo](23827c6b0d/pageserver/src/tenant/timeline.rs (L3725-L3726)),
but that includes the wait time for the semaphore. We could add a
separate metric for the time spent after acquiring the semaphore, so one
can infer the wait time. Seems unnecessary at this point, though.
Add support for reading and writing zstd-compressed blobs for use in
image layer generation, but maybe one day useful also for delta layers.
The reading of them is unconditional while the writing is controlled by
the `image_compression` config variable allowing for experiments.
For the on-disk format, we re-use some of the bitpatterns we currently
keep reserved for blobs larger than 256 MiB. This assumes that we have
never ever written any such large blobs to image layers.
After the preparation in #7852, we now are unable to read blobs with a
size larger than 256 MiB (or write them).
A non-goal of this PR is to come up with good heuristics of when to
compress a bitpattern. This is left for future work.
Parts of the PR were inspired by #7091.
cc #7879
Part of #5431
## Problem
At high percentiles we see more than 800 layers being visited by the
read path. We need the tenant/timeline to investigate.
## Summary of changes
Add a rate limited log line when the average number of layers visited
per key is in the last specified histogram bucket.
I plan to use this to identify tenants in us-east-2 staging that exhibit
this behaviour. Will revert before next week's release.
Before this PR, during timeline shutdown, we'd occasionally see
log lines like this one:
```
2024-06-26T18:28:11.063402Z INFO initial_size_calculation{tenant_id=$TENANT,shard_id=0000 timeline_id=$TIMELINE}:logical_size_calculation_task:get_or_maybe_download{layer=000000000000000000000000000000000000-000000067F0001A3950001C1630100000000__0000000D88265898}: layer file download failed, and caller has been cancelled: Cancelled, shutting down
Stack backtrace:
0: <core::result::Result<T,F> as core::ops::try_trait::FromResidual<core::result::Result<core::convert::Infallible,E>>>::from_residual
at /rustc/129f3b9964af4d4a709d1383930ade12dfe7c081/library/core/src/result.rs:1964:27
pageserver::tenant::remote_timeline_client::RemoteTimelineClient::download_layer_file::{{closure}}
at /home/nonroot/pageserver/src/tenant/remote_timeline_client.rs:531:13
pageserver::tenant::storage_layer::layer::LayerInner::download_and_init::{{closure}}
at /home/nonroot/pageserver/src/tenant/storage_layer/layer.rs:1136:14
pageserver::tenant::storage_layer::layer::LayerInner::download_init_and_wait::{{closure}}::{{closure}}
at /home/nonroot/pageserver/src/tenant/storage_layer/layer.rs:1082:74
```
We can eliminate the anyhow backtrace with no loss of information
because the conversion to anyhow::Error happens in exactly one place.
refs #7427
## Problem
Tenant attachment has error paths for failures to write local
configuration, but these types of local storage I/O errors should be
considered fatal for the process. Related thread on an earlier PR that
touched this code:
https://github.com/neondatabase/neon/pull/7947#discussion_r1655134114
## Summary of changes
- Make errors writing tenant config fatal (abort process)
- When reading tenant config, make all I/O errors except ENOENT fatal
- Replace use of bare anyhow errors with `LoadConfigError`
Before this PR, `RemoteStorageConfig::from_toml` would support
deserializing an
empty `{}` TOML inline table to a `None`, otherwise try `Some()`.
We can instead let
* in proxy: let clap derive handle the Option
* in PS & SK: assume that if the field is specified, it must be a valid
RemtoeStorageConfig
(This PR started with a much simpler goal of factoring out the
`deserialize_item` function because I need that in another PR).
## Problem
See https://github.com/neondatabase/cloud/issues/14289
## Summary of changes
Check connection status after calling PQconnectStartParams
## 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.
## Checklist before merging
- [ ] Do not forget to reformat commit message to not include the above
checklist
---------
Co-authored-by: Konstantin Knizhnik <knizhnik@neon.tech>
This makes it much more convenient to use in the common case that you
want to flush all the WAL. (Passing pg_current_wal_insert_lsn() as the
argument doesn't work for the same reasons as explained in the comments:
we need to be back off to the beginning of a page if the previous record
ended at page boundary.)
I plan to use this to fix the issue that Arseny Sher called out at
https://github.com/neondatabase/neon/pull/7288#discussion_r1660063852
## Problem
We use `build-tools` image as a base image to build other images, and it
has a pretty old `libpq-dev` installed (v13; it wasn't that old until I
removed system Postgres 14 from `build-tools` image in
https://github.com/neondatabase/neon/pull/6540)
## Summary of changes
- Remove `libpq-dev` from `build-tools` image
- Set `LD_LIBRARY_PATH` for tests (for different Postgres binaries that
we use, like psql and pgbench)
- Set `PQ_LIB_DIR` to build Storage Controller
- Set `LD_LIBRARY_PATH`/`DYLD_LIBRARY_PATH` in the Storage Controller
where it calls Postgres binaries
## Problem
We lack visibility of how much local disk space is used by secondary
tenant locations
Close: https://github.com/neondatabase/neon/issues/8181
## Summary of changes
- Add `pageserver_secondary_resident_physical_size`, tagged by tenant
- Register & de-register label sets from SecondaryTenant
- Add+use wrappers in SecondaryDetail that update metrics when
adding+removing layers/timelines
We have one pretty serious MVCC visibility bug with hot standby
replicas. We incorrectly treat any transactions that are in progress
in the primary, when the standby is started, as aborted. That can
break MVCC for queries running concurrently in the standby. It can
also lead to hint bits being set incorrectly, and that damage can last
until the replica is restarted.
The fundamental bug was that we treated any replica start as starting
from a shut down server. The fix for that is straightforward: we need
to set 'wasShutdown = false' in InitWalRecovery() (see changes in the
postgres repo).
However, that introduces a new problem: with wasShutdown = false, the
standby will not open up for queries until it receives a running-xacts
WAL record from the primary. That's correct, and that's how Postgres
hot standby always works. But it's a problem for Neon, because:
* It changes the historical behavior for existing users. Currently,
the standby immediately opens up for queries, so if they now need to
wait, we can breka existing use cases that were working fine
(assuming you don't hit the MVCC issues).
* The problem is much worse for Neon than it is for standalone
PostgreSQL, because in Neon, we can start a replica from an
arbitrary LSN. In standalone PostgreSQL, the replica always starts
WAL replay from a checkpoint record, and the primary arranges things
so that there is always a running-xacts record soon after each
checkpoint record. You can still hit this issue with PostgreSQL if
you have a transaction with lots of subtransactions running in the
primary, but it's pretty rare in practice.
To mitigate that, we introduce another way to collect the
running-xacts information at startup, without waiting for the
running-xacts WAL record: We can the CLOG for XIDs that haven't been
marked as committed or aborted. It has limitations with
subtransactions too, but should mitigate the problem for most users.
See https://github.com/neondatabase/neon/issues/7236.
Co-authored-by: Konstantin Knizhnik <knizhnik@neon.tech>
This makes it much more convenient to use in the common case that you
want to flush all the WAL. (Passing pg_current_wal_insert_lsn() as the
argument doesn't work for the same reasons as explained in the
comments: we need to be back off to the beginning of a page if the
previous record ended at page boundary.)
I plan to use this to fix the issue that Arseny Sher called out at
https://github.com/neondatabase/neon/pull/7288#discussion_r1660063852
The 'running' boolean was replaced with a semaphore in commit
f0e2bb79b2, but this initialization was missed. Remove it so that if a
test tries to access it, you get an error rather than always claiming
that the endpoint is not running.
Spotted by Arseny at
https://github.com/neondatabase/neon/pull/7288#discussion_r1660068657
Reverts neondatabase/neon#7956
Rationale: compute incompatibilties
Slack thread:
https://neondb.slack.com/archives/C033RQ5SPDH/p1718011276665839?thread_ts=1718008160.431869&cid=C033RQ5SPDH
Relevant quotes from @hlinnaka
> If we go through with the current release candidate, but the compute
is pinned, people who create new projects will get that warning, which
is silly. To them, it looks like the ICU version was downgraded, because
initdb was run with newer version.
> We should upgrade the ICU version eventually. And when we do that,
users with old projects that use ICU will start to see that warning. I
think that's acceptable, as long as we do homework, notify users, and
communicate that properly.
> When do that, we should to try to upgrade the storage and compute
versions at roughly the same time.
## Problem
See https://github.com/neondatabase/cloud/issues/10845
## Summary of changes
Do not report error if GIN page is not restored
## 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.
## Checklist before merging
- [ ] Do not forget to reformat commit message to not include the above
checklist
---------
Co-authored-by: Konstantin Knizhnik <knizhnik@neon.tech>
## Problem
After [0e4f182680] which introduce async
connect
Neon is not able to connect to page server.
## Summary of changes
Perform sync commit at MacOS/X
## 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.
## Checklist before merging
- [ ] Do not forget to reformat commit message to not include the above
checklist
---------
Co-authored-by: Konstantin Knizhnik <knizhnik@neon.tech>
## Problem
## Summary of changes
## 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.
## Checklist before merging
- [ ] Do not forget to reformat commit message to not include the above
checklist
## Problem
"John pointed out that the switch to protocol version 2 made
test_gc_aggressive test flaky:
https://github.com/neondatabase/neon/issues/7692.
I tracked it down, and that is indeed an issue. Conditions for hitting
the issue:
The problem occurs in the primary
GC horizon is set to a very low value, e.g. 0.
If the primary is actively writing WAL, and GC runs in the pageserver at
the same time that the primary sends a GetPage request, it's possible
that the GC advances the GC horizon past the GetPage request's LSN. I'm
working on a fix here: https://github.com/neondatabase/neon/pull/7708."
- Heikki
## Summary of changes
Use protocol version 1 as default.
## Problem
- #7451
INIT_FORKNUM blocks must be stored on shard 0 to enable including them
in basebackup.
This issue can be missed in simple tests because creating an unlogged
table isn't sufficient -- to repro I had to create an _index_ on an
unlogged table (then restart the endpoint).
Closes: #7451
## Summary of changes
- Add a reproducer for the issue.
- Tweak the condition for `key_is_shard0` to include anything that isn't
a normal relation block _and_ any normal relation block whose forknum is
INIT_FORKNUM.
- To enable existing databases to recover from the issue, add a special
case that omits relations if they were stored on the wrong INITFORK.
This enables postgres to start and the user to drop the table and
recreate it.
Part of neondatabase/cloud#12047.
The basic idea is that for our VMs, we want to enable swap and disable
Linux memory overcommit. Alongside these, we should set postgres'
dynamic_shared_memory_type to mmap, but we want to avoid setting it to
mmap if swap is not enabled.
Implementing this in the control plane would be fiddly, but it's
relatively straightforward to add to compute_ctl.
Manual testing of the changes in #7160 revealed that, if the
thread-local destructor ever runs (it apparently doesn't in our test
suite runs, otherwise #7160 would not have auto-merged), we can
encounter an `abort()` due to a double-panic in the tracing code.
This github comment here contains the stack trace:
https://github.com/neondatabase/neon/pull/7160#issuecomment-2003778176
This PR reverts #7160 and uses a atomic counter to identify the
thread-local in log messages, instead of the memory address of the
thread local, which may be re-used.
The PR #7141 added log message
```
ThreadLocalState is being dropped and id might be re-used in the future
```
which was supposed to be emitted when the thread-local is destroyed.
Instead, it was emitted on _each_ call to `thread_local_system()`,
ie.., on each tokio-epoll-uring operation.
## Problem
Previously we always wrote out both legacy and modern tenant config
files. The legacy write enabled rollbacks, but we are long past the
point where that is needed.
We still need the legacy format for situations where someone is running
tenants without generations (that will be yanked as well eventually),
but we can avoid writing it out at all if we do have a generation number
set. We implicitly also avoid writing the legacy config if our mode is
Secondary (secondary mode is newer than generations).
## Summary of changes
- Make writing legacy tenant config conditional on there being no
generation number set.
The goal of this doc is to propose a way to reliably collect garbages below the GC horizon. This process is called bottom-most garbage-collect-compaction, and is part of the broader legacy-enhanced compaction that we plan to implement in the future.
## Motivation
The current GC algorithm will wait until the covering via image layers before collecting the garbages of a key region. Relying on image layer generation to generate covering images is not reliable. There are prior arts to generate feedbacks from the GC algorithm to the image generation process to accelerate garbage collection, but it slows down the system and creates write amplification.
The idea of bottom-most compaction is simple: we rewrite all layers that are below or intersect with the GC horizon to produce a flat level of image layers at the GC horizon and deltas above the GC horizon. In this process,
- All images and deltas ≤ GC horizon LSN will be dropped. This process collects garbages.
- We produce images for all keys involved in the compaction process at the GC horizon.
Therefore, it can precisely collect all garbages below the horizon, and reduce the space amplification, i.e., in the staircase pattern (test_gc_feedback).
The staircase pattern in test_gc_feedback in the original compaction algorithm. The goal is to collect garbage below the red horizontal line.
# Branches
With branches, the bottom-most compaction should retain a snapshot of the keyspace at the `retain_lsn` so that the child branch can access data at the branch point. This requires some modifications to the basic bottom-most compaction algorithm that we sketched above.
## Single Timeline w/ Snapshots: handle `retain_lsn`
First let’s look into the case where we create branches over the main branch but don’t write any data to them (aka “snapshots”).
The bottom-most compaction algorithm collects all deltas and images of a key and can make decisions on what data to retain. Given that we have a single key’s history as below:
```
LSN 0x10 -> A
LSN 0x20 -> append B
retain_lsn: 0x20
LSN 0x30 -> append C
LSN 0x40 -> append D
retain_lsn: 0x40
LSN 0x50 -> append E
GC horizon: 0x50
LSN 0x60 -> append F
```
The algorithm will produce:
```
LSN 0x20 -> AB
(drop all history below the earliest retain_lsn)
LSN 0x40 -> ABCD
(assume the cost of replaying 2 deltas is higher than storing the full image, we generate an image here)
What happens is that we balance the space taken by each retain_lsn and the cost of replaying deltas during the bottom-most compaction process. This is controlled by a threshold. If `count(deltas) < $threshold`, the deltas will be retained. Otherwise, an image will be generated and the deltas will be dropped.
In the example above, the `$threshold` is 2.
## Child Branches with data: pull + partial images
In the previous section we have shown how bottom-most compaction respects `retain_lsn` so that all data that was readable at branch creation remains readable. But branches can have data on their own, and that data can fall out of the branch’s PITR window. So, this section explains how we deal with that.
We will run the same bottom-most compaction for these branches, to ensure the space amplification on the child branch is reasonable.
```
branch_lsn: 0x20
LSN 0x30 -> append P
LSN 0x40 -> append Q
LSN 0x50 -> append R
GC horizon: 0x50
LSN 0x60 -> append S
```
Note that bottom-most compaction happens on a per-timeline basis. When it processes this key, it only reads the history from LSN 0x30 without a base image. Therefore, on child branches, the bottom-most compaction process will make image creation decisions based on the same `count(deltas) < $threshold` criteria, and if it decides to create an image, the base image will be retrieved from the ancestor branch.
```
branch_lsn: 0x20
LSN 0x50 -> ABPQR
(we pull the image at LSN 0x20 from the ancestor branch to get AB, and then apply append PQ to the page; we replace the record at 0x40 with an image and drop the delta)
Note that for child branches, we do not create image layers for the images when bottom-most compaction runs. Instead, we drop the 0x30/0x40/0x50 delta records and directly place the image ABPQR@0x50 into the delta layer, which serves as a sparse image layer. For child branches, if we create image layers, we will need to put all keys in the range into the image layer. This causes space bloat and slow compactions. In this proposal, the compaction process will only compact and process keys modified inside the child branch.
# Result
Bottom-most compaction ensures all garbage under the GC horizon gets collected right away (compared with “eventually” in the current algorithm). Meanwhile, it generates images at each of the retain_lsn to ensure branch reads are fast. As we make per-key decisions on whether to generate an image or not, the theoretical lower bound of the storage space we need to retain for a branch is lower than before.
Before: min(sum(logs for each key), sum(image for each key)), for each partition — we always generate image layers on a key range
After: sum(min(logs for each key, image for each key))
# Compaction Trigger
The bottom-most compaction can be automatically triggered. The goal of the trigger is that it should ensure a constant factor for write amplification. Say that the user write 1GB of WAL into the system, we should write 1GB x C data to S3. The legacy compaction algorithm does not have such a constant factor C. The data we write to S3 is quadratic to the logical size of the database (see [A Theoretical View of Neon Storage](https://www.notion.so/A-Theoretical-View-of-Neon-Storage-8d7ad7555b0c41b2a3597fa780911194?pvs=21)).
We propose the following compaction trigger that generates a constant write amplification factor. Write amplification >= total writes to S3 / total user writes. We only analyze the write amplification caused by the bottom-most GC-compaction process, ignoring the legacy create image layers amplification.
Given that we have ***X*** bytes of the delta layers above the GC horizon, ***A*** bytes of the delta layers intersecting with the GC horizon, ***B*** bytes of the delta layers below the GC horizon, and ***C*** bytes of the image layers below the GC horizon.
The legacy GC + compaction loop will always keep ***A*** unchanged, reduce ***B and C*** when there are image layers covering the key range. This yields 0 write amplification (only file deletions) and extra ***B*** bytes of space.
The bottom-most compaction proposed here will split ***A*** into deltas above the GC horizon and below the GC horizon. Everything below the GC horizon will be image layers after the compaction (not considering branches). Therefore, this yields ***A+C*** extra write traffic each iteration, plus 0 extra space.
Also considering read amplification (below the GC horizon). When a read request reaches the GC horizon, the read amplification will be (A+B+C)/C=1+(A+B)/C. Reducing ***A*** and ***B*** can help reduce the read amplification below the GC horizon.
The metrics-based trigger will wait until a point that space amplification is not that large and write amplification is not that large before the compaction gets triggered. The trigger is defined as **(A+B)/C ≥ 1 (or some other ratio)**.
To reason about this trigger, consider the two cases:
**Data Ingestion**
User keeps ingesting data into the database, which indicates that WAL size roughly equals to the database logical size. The compaction gets triggered only when the newly-written WAL roughly equals to the current bottom-most image size (=X). Therefore, it’s triggered when the database size gets doubled. This is a reasonable amount of work. Write amplification is 2X/X=1 for the X amount of data written.
In this case, WAL size will be larger than the database logical size ***D***. The compaction gets triggered for every ***D*** bytes of WAL written. Therefore, for every ***D*** bytes of WAL, we rewrite the bottom-most layer, which produces an extra ***D*** bytes of write amplification. This incurs exactly 2x write amplification (by the write of D), 1.5x write amplification (if we count from the start of the process) and no space amplification.
Note that here I try to reason that write amplification is a constant (i.e., the data we write to S3 is proportional to the data the user write). The main problem with the current legacy compaction algorithm is that write amplification is proportional to the database size.
The next step is to optimize the write amplification above the GC horizon (i.e., change the image creation criteria, top-most compaction, or introduce tiered compaction), to ensure the write amplification of the whole system is a constant factor.
20GB layers → +20GB layers → delete 20GB, need 40GB temporary space
# Sub-Compactions
The gc-compaction algorithm may take a long time and we need to split the job into multiple sub-compaction jobs.
As in the figure, the auto-trigger schedules a compaction job covering the full keyspace below a specific LSN. In such case that we cannot finish compacting it in one run in a reasonable amount of time, the algorithm will vertically split it into multiple jobs (in this case, 5).
Each gc-compaction job will create one level of delta layers and one flat level of image layers for each LSN. Those layers will be automatically split based on size, which means that if the sub-compaction job produces 1GB of deltas, it will produce 4 * 256MB delta layers. For those layers that is not fully contained within the sub-compaction job rectangles, it will be rewritten to only contain the keys outside of the key range.
# Implementation
The main implementation of gc-compaction is in `compaction.rs`.
*`compact_with_gc`: The main loop of gc-compaction. It takes a rectangle range of the layer map and compact that specific range. It selects layers intersecting with the rectangle, downloads the layers, creates the k-merge iterator to read those layers in the key-lsn order, and decide which keys to keep or insert a reconstructed page. The process is the basic unit of a gc-compaction and is not interruptable. If the process gets preempted by L0 compaction, it has to be restarted from scratch. For layers overlaps with the rectangle but not fully inside, the main loop will also rewrite them so that the new layer (or two layers if both left and right ends are outside of the rectangle) has the same LSN range as the original one but only contain the keys outside of the compaction range.
*`gc_compaction_split_jobs`: Splits a big gc-compaction job into sub-compactions based on heuristics in the layer map. The function looks at the layer map and splits the compaction job based on the size of the layers so that each compaction job only pulls ~4GB of layer files.
*`generate_key_retention` and `KeyHistoryRetention`: Implements the algorithm described in the "basic idea" and "branch" chapter of this RFC. It takes a vector of history of a key (key-lsn-value) and decides which LSNs of the key to retain. If there are too many deltas between two retain_lsns, it will reconstruct the page and insert an image into the compaction result. Also, we implement `KeyHistoryRetention::verify` to ensure the generated result is not corrupted -- all retain_lsns and all LSNs above the gc-horizon should be accessible.
*`GcCompactionQueue`: the automatic trigger implementation for gc-compaction. `GcCompactionQueue::iteration` is called at the end of the tenant compaction loop. It will then call `trigger_auto_compaction` to decide whether to trigger a gc-compaction job for this tenant. If yes, the compaction-job will be added to the compaction queue, and the queue will be slowly drained once there are no other compaction jobs running. gc-compaction has the lowest priority. If a sub-compaction job is not successful or gets preempted by L0 compaction (see limitations for reasons why a compaction job would fail), it will _not_ be retried.
* Changes to `index_part.json`: we added a `last_completed_lsn` field to the index part for the auto-trigger to decide when to trigger a compaction.
* Changes to the read path: when gc-compaction updates the layer map, all reads need to wait. See `gc_compaction_layer_update_lock` and comments in the code path for more information.
Gc-compaction can also be scheduled over the HTTP API. Example:
The `dry_run` mode can be specified in the query string so that the compaction will go through all layers to estimate how much space can be saved without writing the compaction result into the layer map.
The auto-trigger is controlled by tenant-level flag `gc_compaction_enabled`. If this is set to false, no gc-compaction will be automatically scheduled on this tenant (but manual trigger still works).
# Next Steps
There are still some limitations of gc-compaction itself that needs to be resolved and tested,
- gc-compaction is currently only automatically triggered on root branches. We have not tested gc-compaction on child branches in staging.
- gc-compaction will skip aux key regions because of the possible conflict with the assumption of aux file tombstones.
- gc-compaction does not consider keyspaces at retain_lsns and only look at keys in the layers. This also causes us giving up some sub-compaction jobs because a key might have part of its history available due to traditional GC removing part of the history.
- We limit gc-compaction to run over shards <= 150GB to avoid gc-compaction taking too much time blocking other compaction jobs. The sub-compaction split algorithm needs to be improved to be able to split vertically and horizontally. Also, we need to move the download layer process out of the compaction loop so that we don't block other compaction jobs for too long.
- The compaction trigger always schedules gc-compaction from the lowest LSN to the gc-horizon. Currently we do not schedule compaction jobs that only selects layers in the middle. Allowing this could potentially reduce the number of layers read/write throughout the process.
- gc-compaction will give up if there are too many layers to rewrite or if there are not enough disk space for the compaction.
- gc-compaction sometimes fails with "no key produced during compaction", which means that all existing keys within the compaction range can be collected; but we don't have a way to write this information back to the layer map -- we cannot generate an empty image layer.
- We limit the maximum size of deltas for a single key to 512MB. If above this size, gc-compaction will give up. This can be resolved by changing `generate_key_retention` to be a stream instead of requiring to collect all the key history.
In the future,
- Top-most compaction: ensure we always have an image coverage for the latest data (or near the latest data), so that reads will be fast at the latest LSN.
- Tiered compaction on deltas: ensure read from any LSN is fast.
<pathd="M 517.125 423.5 L 553.375 423.5 L 553.375 482 L 571.5 482 L 535.25 512 L 499 482 L 517.125 482 Z"fill="white"/>
<pathd="M 517.125 423.5 L 553.375 423.5 L 553.375 482 L 571.5 482 L 535.25 512 L 499 482 L 517.125 482 Z"stroke="black"stroke-linecap="round"stroke-linejoin="round"stroke-width="1"/>
<pathd="M 211.32422 585 L 265.17578 585 L 265.17578 611.332 L 287.84375 611.332 L 238.25 633.117 L 188.65625 611.332 L 211.32422 611.332 Z"fill="white"/>
<pathd="M 211.32422 585 L 265.17578 585 L 265.17578 611.332 L 287.84375 611.332 L 238.25 633.117 L 188.65625 611.332 L 211.32422 611.332 Z"stroke="black"stroke-linecap="round"stroke-linejoin="round"stroke-width="1"/>
<pathd="M 89.32422 639.081 L 143.17578 639.081 L 143.17578 665.413 L 165.84375 665.413 L 116.25 687.198 L 66.65625 665.413 L 89.32422 665.413 Z"fill="white"/>
<pathd="M 89.32422 639.081 L 143.17578 639.081 L 143.17578 665.413 L 165.84375 665.413 L 116.25 687.198 L 66.65625 665.413 L 89.32422 665.413 Z"stroke="black"stroke-linecap="round"stroke-linejoin="round"stroke-width="1"/>
<pathd="M -120.675 651.5 L -84.425 651.5 L -84.425 710 L -66.3 710 L -102.55 740 L -138.8 710 L -120.675 710 Z"fill="white"/>
<pathd="M -120.675 651.5 L -84.425 651.5 L -84.425 710 L -66.3 710 L -102.55 740 L -138.8 710 L -120.675 710 Z"stroke="black"stroke-linecap="round"stroke-linejoin="round"stroke-width="1"/>
<pathd="M -120.675 651.5 L -84.425 651.5 L -84.425 710 L -66.3 710 L -102.55 740 L -138.8 710 L -120.675 710 Z"fill="white"/>
<pathd="M -120.675 651.5 L -84.425 651.5 L -84.425 710 L -66.3 710 L -102.55 740 L -138.8 710 L -120.675 710 Z"stroke="black"stroke-linecap="round"stroke-linejoin="round"stroke-width="1"/>
<pathd="M 420.125 1062 L 456.375 1062 L 456.375 1120.5 L 474.5 1120.5 L 438.25 1150.5 L 402 1120.5 L 420.125 1120.5 Z"fill="white"/>
<pathd="M 420.125 1062 L 456.375 1062 L 456.375 1120.5 L 474.5 1120.5 L 438.25 1150.5 L 402 1120.5 L 420.125 1120.5 Z"stroke="black"stroke-linecap="round"stroke-linejoin="round"stroke-width="1"/>
<pathd="M 420.125 1062 L 456.375 1062 L 456.375 1120.5 L 474.5 1120.5 L 438.25 1150.5 L 402 1120.5 L 420.125 1120.5 Z"fill="white"/>
<pathd="M 420.125 1062 L 456.375 1062 L 456.375 1120.5 L 474.5 1120.5 L 438.25 1150.5 L 402 1120.5 L 420.125 1120.5 Z"stroke="black"stroke-linecap="round"stroke-linejoin="round"stroke-width="1"/>
Blocking a user prevents them from interacting with repositories, such as opening or commenting on pull requests or issues. Learn more about blocking a user.
