## Problem
part of https://github.com/neondatabase/neon/issues/11813
## Summary of changes
* Integrate feature store with tenant structure.
* gc-compaction picks up the current strategy from the feature store.
* We only log them for now for testing purpose. They will not be used
until we have more patches to support different strategies defined in
PostHog.
* We don't support property-based evaulation for now; it will be
implemented later.
* Evaluating result of the feature flag is not cached -- it's not
efficient and cannot be used on hot path right now.
* We don't report the evaluation result back to PostHog right now.
I plan to enable it in staging once we get the patch merged.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
We want to expose the page service over gRPC, for use with the
communicator.
Requires #11995.
Touches #11728.
## Summary of changes
This patch wires up a gRPC server in the Pageserver, using Tonic. It
does not yet implement the actual page service.
* Adds `listen_grpc_addr` and `grpc_auth_type` config options (disabled
by default).
* Enables gRPC by default with `neon_local`.
* Stub implementation of `page_api.PageService`, returning unimplemented
errors.
* gRPC reflection service for use with e.g. `grpcurl`.
Subsequent PRs will implement the actual page service, including
authentication and observability.
Notably, TLS support is not yet implemented. Certificate reloading
requires us to reimplement the entire Tonic gRPC server.
## Problem
Basebackup cache is on the hot path of compute startup and is generated
on every request (may be slow).
- Issue: https://github.com/neondatabase/cloud/issues/29353
## Summary of changes
- Add `BasebackupCache` which stores basebackups on local disk.
- Basebackup prepare requests are triggered by
`XLOG_CHECKPOINT_SHUTDOWN` records in the log.
- Limit the size of the cache by number of entries.
- Add `basebackup_cache_enabled` feature flag to TenantConfig.
- Write tests for the cache
## Not implemented yet
- Limit the size of the cache by total size in bytes
---------
Co-authored-by: Aleksandr Sarantsev <aleksandr@neon.tech>
## Problem
See
Discussion:
https://neondb.slack.com/archives/C033RQ5SPDH/p1746645666075799
Issue: https://github.com/neondatabase/cloud/issues/28609
Relation size cache is not correctly updated at PS in case of replicas.
## Summary of changes
1. Have two caches for relation size in timeline:
`rel_size_primary_cache` and `rel_size_replica_cache`.
2. `rel_size_primary_cache` is actually what we have now. The only
difference is that it is not updated in `get_rel_size`, only by WAL
ingestion
3. `rel_size_replica_cache` has limited size (LruCache) and it's key is
`(Lsn,RelTag)` . It is updated in `get_rel_size`. Only strict LSN
matches are accepted as cache hit.
---------
Co-authored-by: Konstantin Knizhnik <knizhnik@neon.tech>
## Problem
The gRPC page service API will require decoupling the `PageHandler` from
the libpq protocol implementation. As preparation for this, avoid
passing in the entire server config to `PageHandler`, and instead
explicitly pass in the relevant fields.
Touches https://github.com/neondatabase/neon/issues/11728.
## Summary of changes
* Change `PageHandler` to take a `GetVectoredConcurrentIo` instead of
the entire config.
* Change `IoConcurrency::spawn_from_conf` to take a
`GetVectoredConcurrentIo`.
## 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
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
Import code is one big block. Separating planning and execution will
help with reporting
progress of import to storcon (building block for resuming import).
## Summary of changes
Split up the import into planning and execution.
A concurrency limit driven by PS config is also added.
# Add --dev CLI flag to pageserver and safekeeper binaries
This PR adds the `--dev` CLI flag to both the pageserver and safekeeper
binaries without implementing any functionality yet. This is a precursor
to PR #11517, which will implement the full functionality to require
authentication by default unless the `--dev` flag is specified.
## Changes
- Add `dev_mode` config field to pageserver binary
- Add `--dev` CLI flag to safekeeper binary
This PR is needed for forward compatibility tests to work properly, when
we try to merge #11517
Link to Devin run:
https://app.devin.ai/sessions/ad8231b4e2be430398072b6fc4e85d46
Requested by: John Spray (john@neon.tech)
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: John Spray <john@neon.tech>
## Problem
We saw OOMs due to L0 compaction happening simultaneously for all shards
of the same tenant right after the shard split.
## Summary of changes
Lower the threshold so that we compact fewer files.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
Splits of large tenants (several TB) can cause a huge amount of shard
ancestor compaction work, which can overload Pageservers.
Touches https://github.com/neondatabase/cloud/issues/22532.
## Summary of changes
Add a setting `compaction_shard_ancestor` (default `true`) to disable
shard ancestor compaction on a per-tenant basis.
## Problem
Get page batching stops when we encounter requests at different LSNs.
We are leaving batching factor on the table.
## Summary of changes
The goal is to support keys with different LSNs in a single batch and
still serve them with a single vectored get.
Important restriction: the same key at different LSNs is not supported
in one batch. Returning different key
versions is a much more intrusive change.
Firstly, the read path is changed to support "scattered" queries. This
is a conceptually simple step from
https://github.com/neondatabase/neon/pull/11463. Instead of initializing
the fringe for one keyspace,
we do it for multiple at different LSNs and let the logic already
present into the fringe handle selection.
Secondly, page service code is updated to support batching at different
LSNs. Eeach request parsed from the wire determines its effective
request LSN and keeps it in mem for the batcher toinspect. The batcher
allows keys at
different LSNs in one batch as long one key is not requested at
different LSNs.
I'd suggest doing the first pass commit by commit to get a feel for the
changes.
## Results
I used the batching test from [Christian's
PR](https://github.com/neondatabase/neon/pull/11391) which increases the
change of batch breaks. Looking at the logs I think the new code is at
the max batching factor for the workload (we
only break batches due to them being oversized or because the executor
is idle).
```
Main:
Reasons for stopping batching: {'LSN changed': 22843, 'of batch size': 33417}
test_throughput[release-pg16-50-pipelining_config0-30-100-128-batchable {'max_batch_size': 32, 'execution': 'concurrent-futures', 'mode': 'pipelined'}].perfmetric.batching_factor: 14.6662
My branch:
Reasons for stopping batching: {'of batch size': 37024}
test_throughput[release-pg16-50-pipelining_config0-30-100-128-batchable {'max_batch_size': 32, 'execution': 'concurrent-futures', 'mode': 'pipelined'}].perfmetric.batching_factor: 19.8333
```
Related: https://github.com/neondatabase/neon/issues/10765
## Problem
Part of #9114
There was a debug-mode verification mode that verifies at every
retain_lsn. However, the code was tangled within the actual history
generation itself and it's hard to reason about correctness. This patch
adds a separate post-verification of the gc-compaction result that redos
logs at every retain_lsn and every record above the GC horizon. This
ensures that all key history we produce with gc-compaction is readable,
and if there're read errors after gc-compaction, it can only be
read-path errors instead of gc-compaction bugs.
## Summary of changes
* Add gc_compaction_verification flag, default to true.
* Implement a post-verification process.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
Page service doesn't use TLS for incoming requests.
- Closes: https://github.com/neondatabase/cloud/issues/27236
## Summary of changes
- Add option `enable_tls_page_service_api` to pageserver config
- Propagate `tls_server_config` to `page_service` if the option is
enabled
No integration tests for now because I didn't find out how to call page
service API from python and AFAIK computes don't support TLS yet
# Refs
- refs https://github.com/neondatabase/neon/issues/8915
- discussion thread:
https://neondb.slack.com/archives/C033RQ5SPDH/p1742406381132599
- stacked atop https://github.com/neondatabase/neon/pull/11298
- corresponding internal docs update that illustrates how this PR
removes friction: https://github.com/neondatabase/docs/pull/404
# Problem
Rejecting `pageserver.toml`s with unknown fields adds friction,
especially when using `pageserver.toml` fields as feature flags that
need to be decommissioned.
See the added paragraphs on `pageserver_api::models::ConfigToml` for
details on what kind of friction it causes.
Also read the corresponding internal docs update linked above to see a
more imperative guide for using `pageserver.toml` flags as feature
flags.
# Solution
## Ignoring unknown fields
Ignoring is the serde default behavior.
So, just remove `serde(deny_unknown_fields)` from all structs in
`pageserver_api::config::ConfigToml`
`pageserver_api::config::TenantConfigToml`.
I went through all the child fields and verified they don't use
`deny_unknown_fields` either, including those shared with
`pageserver_api::models`.
## Warning about unknown fields
We still want to warn about unknown fields to
- be informed about typos in the config template
- be reminded about feature-flag style configs that have been cleaned up
in code but not yet in config templates
We tried `serde_ignore` (cf draft #11319) but it doesn't work with
`serde(flatten)`.
The solution we arrived at is to compare the on-disk TOML with the TOML
that we produce if we serialize the `ConfigToml` again.
Any key specified in the on-disk TOML but not present in the serialized
TOML is flagged as an ignored key.
The mechanism to do it is a tiny recursive decent visitor on the
`toml_edit::DocumentMut`.
# Future Work
Invalid config _values_ in known fields will continue to fail pageserver
startup.
See
- https://github.com/neondatabase/cloud/issues/24349
for current worst case impact to deployments & ideas to improve.
## Problem
https://github.com/neondatabase/neon/pull/11140 introduces performance
tracing with OTEL
and a pageserver config which configures the sampling ratio of get page
requests.
Enabling a non-zero sampling ratio on a per region basis is too
aggressive and comes with perf
impact that isn't very well understood yet.
## Summary of changes
Add a `sampling_ratio` tenant level config which overrides the
pageserver level config.
Note that we do not cache the config and load it on every get page
request such that changes propagate
timely.
Note that I've had to remove the `SHARD_SELECTION` span to get this to
work. The tracing library doesn't
expose a neat way to drop a span if one realises it's not needed at
runtime.
Closes https://github.com/neondatabase/neon/issues/11392
Based on https://github.com/neondatabase/neon/pull/11139
## Problem
We want to export performance traces from the pageserver in OTEL format.
End goal is to see them in Grafana.
## Summary of changes
https://github.com/neondatabase/neon/pull/11139 introduces the
infrastructure required to run the otel collector alongside the
pageserver.
### Design
Requirements:
1. We'd like to avoid implementing our own performance tracing stack if
possible and use the `tracing` crate if possible.
2. Ideally, we'd like zero overhead of a sampling rate of zero and be a
be able to change the tracing config for a tenant on the fly.
3. We should leave the current span hierarchy intact. This includes
adding perf traces without modifying existing tracing.
To satisfy (3) (and (2) in part) a separate span hierarchy is used.
`RequestContext` gains an optional `perf_span` member
that's only set when the request was chosen by sampling. All perf span
related methods added to `RequestContext` are no-ops for requests that
are not sampled.
This on its own is not enough for (3), so performance spans use a
separate tracing subscriber. The `tracing` crate doesn't have great
support for this, so there's a fair amount of boilerplate to override
the subscriber at all points of the perf span lifecycle.
### Perf Impact
[Periodic
pagebench](https://neonprod.grafana.net/d/ddqtbfykfqfi8d/e904990?orgId=1&from=2025-02-08T14:15:59.362Z&to=2025-03-10T14:15:59.362Z&timezone=utc)
shows no statistically significant regression with a sample ratio of 0.
There's an annotation on the dashboard on 2025-03-06.
### Overview of changes:
1. Clean up the `RequestContext` API a bit. Namely, get rid of the
`RequestContext::extend` API and use the builder instead.
2. Add pageserver level configs for tracing: sampling ratio, otel
endpoint, etc.
3. Introduce some perf span tracking utilities and expose them via
`RequestContext`. We add a `tracing::Span` wrapper to be used for perf
spans and a `tracing::Instrumented` equivalent for it. See doc comments
for reason.
4. Set up OTEL tracing infra according to configuration. A separate
runtime is used for the collector.
5. Add perf traces to the read path.
## Refs
- epic https://github.com/neondatabase/neon/issues/9873
---------
Co-authored-by: Christian Schwarz <christian@neon.tech>
## Problem
Previously, L0 flushes would wait for uploads, as a simple form of
backpressure. However, this prevented flush pipelining and upload
parallelism. It has since been disabled by default and replaced by L0
compaction backpressure.
Touches https://github.com/neondatabase/cloud/issues/24664.
## Summary of changes
This patch removes L0 flush upload waits, along with the
`l0_flush_wait_upload`. This can't be merged until the setting has been
removed across the fleet.
## Problem
SSL certs are loaded only during start up. It doesn't allow the rotation
of short-lived certificates without server restart.
- Closes: https://github.com/neondatabase/cloud/issues/25525
## Summary of changes
- Implement `ReloadingCertificateResolver` which reloads certificates
from disk periodically.
## Problem
Pageservers use unencrypted HTTP requests for storage controller API.
- Closes: https://github.com/neondatabase/cloud/issues/25524
## Summary of changes
- Replace hyper0::server::Server with http_utils::server::Server in
storage controller.
- Add HTTPS handler for storage controller API.
- Support `ssl_ca_file` in pageserver.
The only difference between
- `pageserver_api::models::TenantConfig` and
- `pageserver::tenant::config::TenantConfOpt`
at this point is that `TenantConfOpt` serializes with
`skip_serializing_if = Option::is_none`.
That is an efficiency improvement for all the places that currently
serde `models::TenantConfig` because new serializations will no longer
write `$fieldname: null` for each field that is `None` at runtime.
This should be particularly beneficial for Storcon, which stores
JSON-serialized `models::TenantConfig` in its DB.
# Behavior Changes
This PR changes the serialization behavior: we omit `None` fields
instead of serializing `$fieldname: null`).
So it's a data format change (see section on compatibility below).
And it changes API responses from Storcon and Pageserver.
## API Response Compatibility
Storcon returns the location description.
Afaik it is passed through into
- storcon_cli output
- storcon UI in console admin UI
These outputs will no longer contain `$fieldname: null` values,
which de-bloats the output (good).
But in storcon UI, it also serves as an editor "default", which
will be eliminated after a storcon with this PR is released.
## Data Format Compatibility
Backwards compat: new software reading old serialized data will
deserialize to the same runtime value because all the field types
are exactly the same and `skip_serializing_if` does not affect
deserialization.
Forward compat: old software reading data serialized by new software
will map absence fields in the serialized form to runtime value
`Option::None`. This is serde default behavior, see this playground
to convince yourself:
https://play.rust-lang.org/?version=stable&mode=debug&edition=2024&gist=f7f4e1a169959a3085b6158c022a05eb
The `serde(with="humantime_serde")` however behaves strangely:
if used on an `Option<Duration>`, it still requires the field to be
present,
unlike the serde default behavior shown in the previous paragraph.
The workaround is to set `serde(default)`.
Previously it was set on each individual field, but, we do have the
container attribute, so, set it there.
This requires deriving a `Default` impl, which, because all fields are
`Option`,
is non-magic.
See my notes here:
https://gist.github.com/problame/eddbc225a5d12617e9f2c6413e0cf799
# Future Work
We should have separate types (& crates) for
- runtime types configuration (e.g. PageServerConf::tenant_config,
AttachedLocationConf)
- `config-v1` file pageserver local disk file format
- `mgmt API`
- `pageserver.toml`
Right now they all use the same, which is convenient but makes it hard
to reason about compatibility breakage.
# Refs
- corresponding docs.neon.build PR
https://github.com/neondatabase/docs/pull/470
## Problem
This is already disabled in production, as it is replaced by L0 flush
delays. It will be removed in a later PR, once the config option is no
longer specified in production.
## Summary of changes
Disable `l0_flush_wait_upload` by default.
## Problem
`l0_flush_delay_threshold` has already been set to 30 in production for
a couple of weeks. Let's harmonize the default.
## Summary of changes
Update `DEFAULT_L0_FLUSH_DELAY_FACTOR` to 3 such that the default
`l0_flush_delay_threshold` is `3 * compaction_threshold`.
This differs from the production setting, which is hardcoded to 30 (with
`compaction_threshold` at 10), and is more appropriate for any tenants
that have custom `compaction_threshold` overrides.
## Problem
`compaction_l0_first` has already been enabled in production for a
couple of weeks.
## Summary of changes
Enable `compaction_l0_first` by default.
Also set `CompactFlags::NoYield` in `timeline_checkpoint_handler`, to
ensure explicitly requested compaction runs to completion. This endpoint
is mainly used in tests, and caused some flakiness where tests expected
compaction to complete.
## 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.
Updates storage components to edition 2024. We like to stay on the
latest edition if possible. There is no functional changes, however some
code changes had to be done to accommodate the edition's breaking
changes.
The PR has two commits:
* the first commit updates storage crates to edition 2024 and appeases
`cargo clippy` by changing code. i have accidentially ran the formatter
on some files that had other edits.
* the second commit performs a `cargo fmt`
I would recommend a closer review of the first commit and a less close
review of the second one (as it just runs `cargo fmt`).
part of https://github.com/neondatabase/neon/issues/10918
## Problem
part of https://github.com/neondatabase/neon/issues/9114
## Summary of changes
Add the auto trigger for gc-compaction. It computes two values: L1 size
and L2 size. When L1 size >= initial trigger threshold, we will trigger
an initial gc-compaction. When l1_size / l2_size >=
gc_compaction_ratio_percent, we will trigger the "tiered" gc-compaction.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
The interpreted SK <-> PS protocol does not guard against gaps (neither
does the Vanilla one, but that's beside the point).
## Summary of changes
Extend the protocol to include the start LSN of the PG WAL section from
which the records were interpreted.
Validation is enabled via a config flag on the pageserver and works as
follows:
**Case 1**: `raw_wal_start_lsn` is smaller than the requested LSN
There can't be gaps here, but we check that the shard received records
which it hasn't seen before.
**Case 2**: `raw_wal_start_lsn` is equal to the requested LSN
This is the happy case. No gap and nothing to check
**Case 3**: `raw_wal_start_lsn` is greater than the requested LSN
This is a gap.
To make Case 3 work I had to bend the protocol a bit.
We read record chunks of WAL which aren't record aligned and feed them
to the decoder.
The picture below shows a shard which subscribes at a position somewhere
within Record 2.
We already have a wal reader which is below that position so we wait to
catch up.
We read some wal in Read 1 (all of Record 1 and some of Record 2). The
new shard doesn't
need Record 1 (it has already processed it according to the starting
position), but we read
past it's starting position. When we do Read 2, we decode Record 2 and
ship it off to the shard,
but the starting position of Read 2 is greater than the starting
position the shard requested.
This looks like a gap.
To make it work, we extend the protocol to send an empty
`InterpretedWalRecords` to shards
if the WAL the records originated from ends the requested start
position. On the pageserver,
that just updates the tracking LSNs in memory (no-op really). This gives
us a workaround for
the fake gap.
As a drive by, make `InterpretedWalRecords::next_record_lsn` mandatory
in the application level definition.
It's always included.
Related: https://github.com/neondatabase/cloud/issues/23935
## Problem
We've seen the previous default of 50 cause OOMs. Compacting many L0
layers at once now has limited benefit, since the cost is mostly linear
anyway. This is already being reduced to 20 in production settings.
## Summary of changes
Reduce `DEFAULT_COMPACTION_UPPER_LIMIT` to 20.
Once released, let's remove the config overrides.
## Problem
Part of https://github.com/neondatabase/neon/issues/9516
## Summary of changes
This patch adds the support for storing reldir in the sparse keyspace.
All logic are guarded with the `rel_size_v2_enabled` flag, so if it's
set to false, the code path is exactly the same as what's currently in
prod.
Note that we did not persist the `rel_size_v2_enabled` flag and the
logic around it will be implemented in the next patch. (i.e., what if we
enabled it, restart the pageserver, and then it gets set to false? we
should still read from v2 using the rel_size_v2_migration_status in the
index_part). The persistence logic I'll implement in the next patch will
disallow switching from v2->v1 via config item.
I also refactored the metrics so that it can work with the new reldir
store. However, this metric is not correctly computed for reldirs (see
the comments) before. With the refactor, the value will be computed only
when we have an initial value for the reldir size. The refactor keeps
the incorrectness of the computation when there are more than 1
database.
For the tests, we currently run all the tests with v2, and I'll set it
to false and add some v2-specific tests before merging, probably also
v1->v2 migration tests.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
L0 compaction frequently gets starved out by other background tasks and
image/GC compaction. L0 compaction must be responsive to keep read
amplification under control.
Touches #10694.
Resolves#10689.
## Summary of changes
Use a separate semaphore for the L0-only compaction pass.
* Add a `CONCURRENT_L0_COMPACTION_TASKS` semaphore and
`BackgroundLoopKind::L0Compaction`.
* Add a setting `compaction_l0_semaphore` (default off via
`compaction_l0_first`).
* Use the L0 semaphore when doing an `OnlyL0Compaction` pass.
* Use the background semaphore when doing a regular compaction pass
(which includes an initial L0 pass).
* While waiting for the background semaphore, yield for L0 compaction if
triggered.
* Add `CompactFlags::NoYield` to disable L0 yielding, and set it for the
HTTP API route.
* Remove the old `use_compaction_semaphore` setting and
compaction-scoped semaphore.
* Remove the warning when waiting for a semaphore; it's noisy and we
have metrics.
## Problem
Image compaction can starve out L0 compaction if a tenant has several
timelines with L0 debt.
Touches #10694.
Requires #10740.
## Summary of changes
* Add an initial L0 compaction pass, in order of L0 count.
* Add a tenant option `compaction_l0_first` to control the L0 pass
(disabled by default).
* Add `CompactFlags::OnlyL0Compaction` to run an L0-only compaction
pass.
* Clean up the compaction iteration logic.
A later PR will use separate semaphores for the L0 and image compaction
passes to avoid cross-tenant L0 starvation. That PR will also make image
compaction yield if _any_ of the tenant's timelines have pending L0
compaction to further avoid starvation.
This changes the default value of the `timeline_offloading` pageserver
and tenant configs to true, now that offloading has been rolled out
without problems.
There is also a small fix in the tenant config merge function, where we
applied the `lazy_slru_download` value instead of `timeline_offloading`.
Related issue: https://github.com/neondatabase/cloud/issues/21353
## Problem
helps investigate https://github.com/neondatabase/neon/issues/10482
## Summary of changes
In debug mode and testing mode, we will record all files visited by a
read operation, and print it out when it errors.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
L0 compaction can get starved by other background tasks. It needs to be
responsive to avoid read amp blowing up during heavy write workloads.
Touches #10694.
## Summary of changes
Add a separate semaphore for compaction, configurable via
`use_compaction_semaphore` (disabled by default). This is primarily for
testing in staging; it needs further work (in particular to split
image/L0 compaction jobs) before it can be enabled.
## Problem
Image layer generation could block L0 compactions for a long time.
## Summary of changes
* Refactored the return value of `create_image_layers_for_*` functions
to make it self-explainable.
* Preempt image layer generation in `Try` mode if L0 piles up.
Note that we might potentially run into a state that only the beginning
part of the keyspace gets image coverage. In that case, we either need
to implement something to prioritize some keyspaces with image coverage,
or tune the image_creation_threshold to ensure that the frequency of
image creation could keep up with L0 compaction.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
Co-authored-by: Erik Grinaker <erik@neon.tech>
## Problem
Follow-up of the incident, we should not use the same bound on
lower/upper limit of compaction files. This patch adds an upper bound
limit, which is set to 50 for now.
## Summary of changes
Add `compaction_upper_limit`.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
Co-authored-by: Christian Schwarz <christian@neon.tech>
## Problem
We need a setting to disable the flush upload wait, to test L0 flush
backpressure in staging.
## Summary of changes
Add `l0_flush_wait_upload` setting.
## Problem
There is no direct backpressure for compaction and L0 read
amplification. This allows a large buildup of compaction debt and read
amplification.
Resolves#5415.
Requires #10402.
## Summary of changes
Delay layer flushes based on the number of level 0 delta layers:
* `l0_flush_delay_threshold`: delay flushes such that they take 2x as
long (default `2 * compaction_threshold`).
* `l0_flush_stall_threshold`: stall flushes until level 0 delta layers
drop below threshold (default `4 * compaction_threshold`).
If either threshold is reached, ephemeral layer rolls also synchronously
wait for layer flushes to propagate this backpressure up into WAL
ingestion. This will bound the number of frozen layers to 1 once
backpressure kicks in, since all other frozen layers must flush before
the rolled layer.
## Analysis
This will significantly change the compute backpressure characteristics.
Recall the three compute backpressure knobs:
* `max_replication_write_lag`: 500 MB (based on Pageserver
`last_received_lsn`).
* `max_replication_flush_lag`: 10 GB (based on Pageserver
`disk_consistent_lsn`).
* `max_replication_apply_lag`: disabled (based on Pageserver
`remote_consistent_lsn`).
Previously, the Pageserver would keep ingesting WAL and build up
ephemeral layers and L0 layers until the compute hit
`max_replication_flush_lag` at 10 GB and began backpressuring. Now, once
we delay/stall WAL ingestion, the compute will begin backpressuring
after `max_replication_write_lag`, i.e. 500 MB. This is probably a good
thing (we're not building up a ton of compaction debt), but we should
consider tuning these settings.
`max_replication_flush_lag` probably doesn't serve a purpose anymore,
and we should consider removing it.
Furthermore, the removal of the upload barrier in #10402 will mean that
we no longer backpressure flushes based on S3 uploads, since
`max_replication_apply_lag` is disabled. We should consider enabling
this as well.
### When and what do we compact?
Default compaction settings:
* `compaction_threshold`: 10 L0 delta layers.
* `compaction_period`: 20 seconds (between each compaction loop check).
* `checkpoint_distance`: 256 MB (size of L0 delta layers).
* `l0_flush_delay_threshold`: 20 L0 delta layers.
* `l0_flush_stall_threshold`: 40 L0 delta layers.
Compaction characteristics:
* Minimum compaction volume: 10 layers * 256 MB = 2.5 GB.
* Additional compaction volume (assuming 128 MB/s WAL): 128 MB/s * 20
seconds = 2.5 GB (10 L0 layers).
* Required compaction bandwidth: 5.0 GB / 20 seconds = 256 MB/s.
### When do we hit `max_replication_write_lag`?
Depending on how fast compaction and flushes happens, the compute will
backpressure somewhere between `l0_flush_delay_threshold` or
`l0_flush_stall_threshold` + `max_replication_write_lag`.
* Minimum compute backpressure lag: 20 layers * 256 MB + 500 MB = 5.6 GB
* Maximum compute backpressure lag: 40 layers * 256 MB + 500 MB = 10.0
GB
This seems like a reasonable range to me.
## Refs
- Epic: https://github.com/neondatabase/neon/issues/9378
Co-authored-by: Vlad Lazar <vlad@neon.tech>
Co-authored-by: Christian Schwarz <christian@neon.tech>
## Problem
The read path does its IOs sequentially.
This means that if N values need to be read to reconstruct a page,
we will do N IOs and getpage latency is `O(N*IoLatency)`.
## Solution
With this PR we gain the ability to issue IO concurrently within one
layer visit **and** to move on to the next layer without waiting for IOs
from the previous visit to complete.
This is an evolved version of the work done at the Lisbon hackathon,
cf https://github.com/neondatabase/neon/pull/9002.
## Design
### `will_init` now sourced from disk btree index keys
On the algorithmic level, the only change is that the
`get_values_reconstruct_data`
now sources `will_init` from the disk btree index key (which is
PS-page_cache'd), instead
of from the `Value`, which is only available after the IO completes.
### Concurrent IOs, Submission & Completion
To separate IO submission from waiting for its completion, while
simultaneously
feature-gating the change, we introduce the notion of an `IoConcurrency`
struct
through which IO futures are "spawned".
An IO is an opaque future, and waiting for completions is handled
through
`tokio::sync::oneshot` channels.
The oneshot Receiver's take the place of the `img` and `records` fields
inside `VectoredValueReconstructState`.
When we're done visiting all the layers and submitting all the IOs along
the way
we concurrently `collect_pending_ios` for each value, which means
for each value there is a future that awaits all the oneshot receivers
and then calls into walredo to reconstruct the page image.
Walredo is now invoked concurrently for each value instead of
sequentially.
Walredo itself remains unchanged.
The spawned IO futures are driven to completion by a sidecar tokio task
that
is separate from the task that performs all the layer visiting and
spawning of IOs.
That tasks receives the IO futures via an unbounded mpsc channel and
drives them to completion inside a `FuturedUnordered`.
(The behavior from before this PR is available through
`IoConcurrency::Sequential`,
which awaits the IO futures in place, without "spawning" or "submitting"
them
anywhere.)
#### Alternatives Explored
A few words on the rationale behind having a sidecar *task* and what
alternatives were considered.
One option is to queue up all IO futures in a FuturesUnordered that is
polled
the first time when we `collect_pending_ios`.
Firstly, the IO futures are opaque, compiler-generated futures that need
to be polled at least once to submit their IO. "At least once" because
tokio-epoll-uring may not be able to submit the IO to the kernel on
first
poll right away.
Second, there are deadlocks if we don't drive the IO futures to
completion
independently of the spawning task.
The reason is that both the IO futures and the spawning task may hold
some
_and_ try to acquire _more_ shared limited resources.
For example, both spawning task and IO future may try to acquire
* a VirtualFile file descriptor cache slot async mutex (observed during
impl)
* a tokio-epoll-uring submission slot (observed during impl)
* a PageCache slot (currently this is not the case but we may move more
code into the IO futures in the future)
Another option is to spawn a short-lived `tokio::task` for each IO
future.
We implemented and benchmarked it during development, but found little
throughput improvement and moderate mean & tail latency degradation.
Concerns about pressure on the tokio scheduler made us discard this
variant.
The sidecar task could be obsoleted if the IOs were not arbitrary code
but a well-defined struct.
However,
1. the opaque futures approach taken in this PR allows leaving the
existing
code unchanged, which
2. allows us to implement the `IoConcurrency::Sequential` mode for
feature-gating
the change.
Once the new mode sidecar task implementation is rolled out everywhere,
and `::Sequential` removed, we can think about a descriptive submission
& completion interface.
The problems around deadlocks pointed out earlier will need to be solved
then.
For example, we could eliminate VirtualFile file descriptor cache and
tokio-epoll-uring slots.
The latter has been drafted in
https://github.com/neondatabase/tokio-epoll-uring/pull/63.
See the lengthy doc comment on `spawn_io()` for more details.
### Error handling
There are two error classes during reconstruct data retrieval:
* traversal errors: index lookup, move to next layer, and the like
* value read IO errors
A traversal error fails the entire get_vectored request, as before this
PR.
A value read error only fails that value.
In any case, we preserve the existing behavior that once
`get_vectored` returns, all IOs are done. Panics and failing
to poll `get_vectored` to completion will leave the IOs dangling,
which is safe but shouldn't happen, and so, a rate-limited
log statement will be emitted at warning level.
There is a doc comment on `collect_pending_ios` giving more code-level
details and rationale.
### Feature Gating
The new behavior is opt-in via pageserver config.
The `Sequential` mode is the default.
The only significant change in `Sequential` mode compared to before
this PR is the buffering of results in the `oneshot`s.
## Code-Level Changes
Prep work:
* Make `GateGuard` clonable.
Core Feature:
* Traversal code: track `will_init` in `BlobMeta` and source it from
the Delta/Image/InMemory layer index, instead of determining `will_init`
after we've read the value. This avoids having to read the value to
determine whether traversal can stop.
* Introduce `IoConcurrency` & its sidecar task.
* `IoConcurrency` is the clonable handle.
* It connects to the sidecar task via an `mpsc`.
* Plumb through `IoConcurrency` from high level code to the
individual layer implementations' `get_values_reconstruct_data`.
We piggy-back on the `ValuesReconstructState` for this.
* The sidecar task should be long-lived, so, `IoConcurrency` needs
to be rooted up "high" in the call stack.
* Roots as of this PR:
* `page_service`: outside of pagestream loop
* `create_image_layers`: when it is called
* `basebackup`(only auxfiles + replorigin + SLRU segments)
* Code with no roots that uses `IoConcurrency::sequential`
* any `Timeline::get` call
* `collect_keyspace` is a good example
* follow-up: https://github.com/neondatabase/neon/issues/10460
* `TimelineAdaptor` code used by the compaction simulator, unused in
practive
* `ingest_xlog_dbase_create`
* Transform Delta/Image/InMemoryLayer to
* do their values IO in a distinct `async {}` block
* extend the residence of the Delta/Image layer until the IO is done
* buffer their results in a `oneshot` channel instead of straight
in `ValuesReconstructState`
* the `oneshot` channel is wrapped in `OnDiskValueIo` /
`OnDiskValueIoWaiter`
types that aid in expressiveness and are used to keep track of
in-flight IOs so we can print warnings if we leave them dangling.
* Change `ValuesReconstructState` to hold the receiving end of the
`oneshot` channel aka `OnDiskValueIoWaiter`.
* Change `get_vectored_impl` to `collect_pending_ios` and issue walredo
concurrently, in a `FuturesUnordered`.
Testing / Benchmarking:
* Support queue-depth in pagebench for manual benchmarkinng.
* Add test suite support for setting concurrency mode ps config
field via a) an env var and b) via NeonEnvBuilder.
* Hacky helper to have sidecar-based IoConcurrency in tests.
This will be cleaned up later.
More benchmarking will happen post-merge in nightly benchmarks, plus in
staging/pre-prod.
Some intermediate helpers for manual benchmarking have been preserved in
https://github.com/neondatabase/neon/pull/10466 and will be landed in
later PRs.
(L0 layer stack generator!)
Drive-By:
* test suite actually didn't enable batching by default because
`config.compatibility_neon_binpath` is always Truthy in our CI
environment
=> https://neondb.slack.com/archives/C059ZC138NR/p1737490501941309
* initial logical size calculation wasn't always polled to completion,
which was
surfaced through the added WARN logs emitted when dropping a
`ValuesReconstructState` that still has inflight IOs.
* remove the timing histograms
`pageserver_getpage_get_reconstruct_data_seconds`
and `pageserver_getpage_reconstruct_seconds` because with planning,
value read
IO, and walredo happening concurrently, one can no longer attribute
latency
to any one of them; we'll revisit this when Vlad's work on
tracing/sampling
through RequestContext lands.
* remove code related to `get_cached_lsn()`.
The logic around this has been dead at runtime for a long time,
ever since the removal of the materialized page cache in #8105.
## Testing
Unit tests use the sidecar task by default and run both modes in CI.
Python regression tests and benchmarks also use the sidecar task by
default.
We'll test more in staging and possibly preprod.
# Future Work
Please refer to the parent epic for the full plan.
The next step will be to fold the plumbing of IoConcurrency
into RequestContext so that the function signatures get cleaned up.
Once `Sequential` isn't used anymore, we can take the next
big leap which is replacing the opaque IOs with structs
that have well-defined semantics.
---------
Co-authored-by: Christian Schwarz <christian@neon.tech>
## Problem
part of https://github.com/neondatabase/neon/issues/9114
The automatic trigger is already implemented at
https://github.com/neondatabase/neon/pull/10221 but I need to write some
tests and finish my experiments in staging before I can merge it with
confidence. Given that I have some other patches that will modify the
config items, I'd like to get the config items merged first to reduce
conflicts.
## Summary of changes
* add `l2_lsn` to index_part.json -- below that LSN, data have been
processed by gc-compaction
* add a set of gc-compaction auto trigger control items into the config
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
# Problem
The timeout-based batching adds latency to unbatchable workloads.
We can choose a short batching timeout (e.g. 10us) but that requires
high-resolution timers, which tokio doesn't have.
I thoroughly explored options to use OS timers (see
[this](https://github.com/neondatabase/neon/pull/9822) abandoned PR).
In short, it's not an attractive option because any timer implementation
adds non-trivial overheads.
# Solution
The insight is that, in the steady state of a batchable workload, the
time we spend in `get_vectored` will be hundreds of microseconds anyway.
If we prepare the next batch concurrently to `get_vectored`, we will
have a sizeable batch ready once `get_vectored` of the current batch is
done and do not need an explicit timeout.
This can be reasonably described as **pipelining of the protocol
handler**.
# Implementation
We model the sub-protocol handler for pagestream requests
(`handle_pagrequests`) as two futures that form a pipeline:
2. Batching: read requests from the connection and fill the current
batch
3. Execution: `take` the current batch, execute it using `get_vectored`,
and send the response.
The Reading and Batching stage are connected through a new type of
channel called `spsc_fold`.
See the long comment in the `handle_pagerequests_pipelined` for details.
# Changes
- Refactor `handle_pagerequests`
- separate functions for
- reading one protocol message; produces a `BatchedFeMessage` with just
one page request in it
- batching; tried to merge an incoming `BatchedFeMessage` into an
existing `BatchedFeMessage`; returns `None` on success and returns back
the incoming message in case merging isn't possible
- execution of a batched message
- unify the timeline handle acquisition & request span construction; it
now happen in the function that reads the protocol message
- Implement serial and pipelined model
- serial: what we had before any of the batching changes
- read one protocol message
- execute protocol messages
- pipelined: the design described above
- optionality for execution of the pipeline: either via concurrent
futures vs tokio tasks
- Pageserver config
- remove batching timeout field
- add ability to configure pipelining mode
- add ability to limit max batch size for pipelined configurations
(required for the rollout, cf
https://github.com/neondatabase/cloud/issues/20620 )
- ability to configure execution mode
- Tests
- remove `batch_timeout` parametrization
- rename `test_getpage_merge_smoke` to `test_throughput`
- add parametrization to test different max batch sizes and execution
moes
- rename `test_timer_precision` to `test_latency`
- rename the test case file to `test_page_service_batching.py`
- better descriptions of what the tests actually do
## On the holding The `TimelineHandle` in the pending batch
While batching, we hold the `TimelineHandle` in the pending batch.
Therefore, the timeline will not finish shutting down while we're
batching.
This is not a problem in practice because the concurrently ongoing
`get_vectored` call will fail quickly with an error indicating that the
timeline is shutting down.
This results in the Execution stage returning a `QueryError::Shutdown`,
which causes the pipeline / entire page service connection to shut down.
This drops all references to the
`Arc<Mutex<Option<Box<BatchedFeMessage>>>>` object, thereby dropping the
contained `TimelineHandle`s.
- => fixes https://github.com/neondatabase/neon/issues/9850
# Performance
Local run of the benchmarks, results in [this empty
commit](1cf5b1463f)
in the PR branch.
Key take-aways:
* `concurrent-futures` and `tasks` deliver identical `batching_factor`
* tail latency impact unknown, cf
https://github.com/neondatabase/neon/issues/9837
* `concurrent-futures` has higher throughput than `tasks` in all
workloads (=lower `time` metric)
* In unbatchable workloads, `concurrent-futures` has 5% higher
`CPU-per-throughput` than that of `tasks`, and 15% higher than that of
`serial`.
* In batchable-32 workload, `concurrent-futures` has 8% lower
`CPU-per-throughput` than that of `tasks` (comparison to tput of
`serial` is irrelevant)
* in unbatchable workloads, mean and tail latencies of
`concurrent-futures` is practically identical to `serial`, whereas
`tasks` adds 20-30us of overhead
Overall, `concurrent-futures` seems like a slightly more attractive
choice.
# Rollout
This change is disabled-by-default.
Rollout plan:
- https://github.com/neondatabase/cloud/issues/20620
# Refs
- epic: https://github.com/neondatabase/neon/issues/9376
- this sub-task: https://github.com/neondatabase/neon/issues/9377
- the abandoned attempt to improve batching timeout resolution:
https://github.com/neondatabase/neon/pull/9820
- closes https://github.com/neondatabase/neon/issues/9850
- fixes https://github.com/neondatabase/neon/issues/9835
## Problem
For any given tenant shard, pageservers receive all of the tenant's WAL
from the safekeeper.
This soft-blocks us from using larger shard counts due to bandwidth
concerns and CPU overhead of filtering
out the records.
## Summary of changes
This PR lifts the decoding and interpretation of WAL from the pageserver
into the safekeeper.
A customised PG replication protocol is used where instead of sending
raw WAL, the safekeeper sends
filtered, interpreted records. The receiver drives the protocol
selection, so, on the pageserver side, usage
of the new protocol is gated by a new pageserver config:
`wal_receiver_protocol`.
More granularly the changes are:
1. Optionally inject the protocol and shard identity into the arguments
used for starting replication
2. On the safekeeper side, implement a new wal sending primitive which
decodes and interprets records
before sending them over
3. On the pageserver side, implement the ingestion of this new
replication message type. It's very similar
to what we already have for raw wal (minus decoding and interpreting).
## Notes
* This PR currently uses my [branch of
rust-postgres](https://github.com/neondatabase/rust-postgres/tree/vlad/interpreted-wal-record-replication-support)
which includes the deserialization logic for the new replication message
type. PR for that is open
[here](https://github.com/neondatabase/rust-postgres/pull/32).
* This PR contains changes for both pageservers and safekeepers. It's
safe to merge because the new protocol is disabled by default on the
pageserver side. We can gradually start enabling it in subsequent
releases.
* CI tests are running on https://github.com/neondatabase/neon/pull/9747
## Links
Related: https://github.com/neondatabase/neon/issues/9336
Epic: https://github.com/neondatabase/neon/issues/9329
