# Refs
- fixes https://github.com/neondatabase/neon/issues/6107
# Problem
`VirtualFile` currently parses the path it is opened with to identify
the `tenant,shard,timeline` labels to be used for the `STORAGE_IO_SIZE`
metric.
Further, for each read or write call to VirtualFile, it uses
`with_label_values` to retrieve the correct metrics object, which under
the hood is a global hashmap guarded by a parking_lot mutex.
We perform tens of thousands of reads and writes per second on every
pageserver instance; thus, doing the mutex lock + hashmap lookup is
wasteful.
# Changes
Apply the technique we use for all other timeline-scoped metrics to
avoid the repeat `with_label_values`: add it to `TimelineMetrics`.
Wrap `TimelineMetrics` into an `Arc`.
Propagate the `Arc<TimelineMetrics>` down do `VirtualFile`, and use
`Timeline::metrics::storage_io_size`.
To avoid contention on the `Arc<TimelineMetrics>`'s refcount atomics
between different connection handlers for the same timeline, we wrap it
into another Arc.
To avoid frequent allocations, we store that Arc<Arc<TimelineMetrics>>
inside the per-connection timeline cache.
Preliminary refactorings to enable this change:
- https://github.com/neondatabase/neon/pull/11001
- https://github.com/neondatabase/neon/pull/11030
# Performance
I ran the benchmarks in
`test_runner/performance/pageserver/pagebench/test_pageserver_max_throughput_getpage_at_latest_lsn.py`
on an `i3en.3xlarge` because that's what we currently run them on.
None of the benchmarks shows a meaningful difference in latency or
throughput or CPU utilization.
I would have expected some improvement in the
many-tenants-one-client-each workload because they all hit that hashmap
constantly, and clone the same `UintCounter` / `Arc` inside of it.
But apparently the overhead is miniscule compared to the remaining work
we do per getpage.
Yet, since the changes are already made, the added complexity is
manageable, and the perf overhead of `with_label_values` demonstrable in
micro-benchmarks, let's have this change anyway.
Also, propagating TimelineMetrics through RequestContext might come in
handy down the line.
The micro-benchmark that demonstrates perf impact of
`with_label_values`, along with other pitfalls and mitigation techniques
around the `metrics`/`prometheus` crate:
- https://github.com/neondatabase/neon/pull/11019
# Alternative Designs
An earlier iteration of this PR stored an `Arc<Arc<Timeline>>` inside
`RequestContext`.
The problem is that this risks reference cycles if the RequestContext
gets stored in an object that is owned directly or indirectly by
`Timeline`.
Ideally, we wouldn't be using this mess of Arc's at all and propagate
Rust references instead.
But tokio requires tasks to be `'static`, and so, we wouldn't be able to
propagate references across task boundaries, which is incompatible with
any sort of fan-out code we already have (e.g. concurrent IO) or future
code (parallel compaction).
So, opt for Arc for now.
## Problem
For pg_regress test, we do both v1 and v2; for all the rest, we default
to v2.
part of https://github.com/neondatabase/neon/issues/9516
## Summary of changes
Use reldir v2 across test cases by default.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
Each page of the slru segment is fetched individually when it's loaded
on demand.
## Summary of Changes
Use `Timeline::get_vectored` to fetch 16 at a time.
## Problem
part of https://github.com/neondatabase/neon/issues/9516
## Summary of changes
Similar to the aux v2 migration, we persist the relv2 migration status
into index_part, so that even the config item is set to false, we will
still read from the v2 storage to avoid loss of data.
Note that only the two variants `None` and
`Some(RelSizeMigration::Migrating)` are used for now. We don't have full
migration implemented so it will never be set to
`RelSizeMigration::Migrated`.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
We intend for cplane to use the heatmap layer download API to warm up
timelines after unarchival. It's tricky for them to recurse in the
ancestors,
and the current implementation doesn't work well when unarchiving a
chain
of branches and warming them up.
## Summary of changes
* Add a `recurse` flag to the API. When the flag is set, the operation
recurses into the parent
timeline after the current one is done.
* Be resilient to warming up a chain of unarchived branches. Let's say
we unarchived `B` and `C` from
the `A -> B -> C` branch hierarchy. `B` got unarchived first. We
generated the unarchival heatmaps
and stash them in `A` and `B`. When `C` unarchived, it dropped it's
unarchival heatmap since `A` and `B`
already had one. If `C` needed layers from `A` and `B`, it was out of
luck. Now, when choosing whether
to keep an unarchival heatmap we look at its end LSN. If it's more
inclusive than what we currently have,
keep it.
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/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
We expose `latest_gc_cutoff` in our API, and callers understandably were
using that to validate LSNs for branch creation. However, this is _not_
the true GC cutoff from a user's point of view: it's just the point at
which we last actually did GC. The actual cutoff used when validating
branch creations and page_service reads is the min() of latest_gc_cutoff
and the planned GC lsn in GcInfo.
Closes: https://github.com/neondatabase/neon/issues/10639
## Summary of changes
- Expose the more useful min() of GC cutoffs as `gc_cutoff_lsn` in the
API, so that the most obviously named field is really the one people
should use.
- Retain the ability to read the LSN at which GC was actually done, in
an `applied_gc_cutoff_lsn` field.
- Internally rename `latest_gc_cutoff_lsn` to `applied_gc_cutoff_lsn`
("latest" was a confusing name, as the value in GcInfo is more up to
date in terms of what a user experiences)
- Temporarily preserve the old `latest_gc_cutoff_lsn` field for compat
with control plane until we update it to use the new field.
---------
Co-authored-by: Arpad Müller <arpad-m@users.noreply.github.com>
Often the output of the timestamp->lsn API is used as input for branch
creation, and branch creation takes the planned lsn into account, i.e.
rejects lsn's as branch lsns that are before the planned lsn.
This patch doesn't fix all race conditions, it's still racy. But at
least it is a step into the right direction.
For #10639
## Problem
We don't have visibility into the ratio of image vs. delta pages
ingested in Pageservers. This might be useful to determine whether we
should compress WAL records before storing them, which in turn might
make compaction more efficient.
## Summary of changes
Add `pageserver_wal_ingest_values_committed` metric with dimensions
`class=metadata|data` and `kind=image|delta`.
## 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
If for some reasons we already garbage-collected the data under an LSN
but the caller uses a past LSN for the find_time_cutoff function, now we
will report a missing key error and GC will never proceed.
Note that missing key error can also happen if the key is really missing
(i.e., during the past offload incidents)
## Summary of changes
Make sure GC proceeds by bumping the LSN. When time_cutoff=None, we will
not increase the time_cutoff (it will be set to latest_gc_cutoff). If we
really need to bump the GC LSN for maintenance purpose, we need a
separate API to do that.
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
Changes in #9786 were functionally complete but missed some edges that
made testing less robust than it should have been:
- `is_key_disposable` didn't consider SLRU dir keys disposable
- Timeline `init_empty` was always creating SLRU dir keys on all shards
The result was that when we had a bug
(https://github.com/neondatabase/neon/pull/10080), it wasn't apparent in
tests, because one would only encounter the issue if running on a
long-lived timeline with enough compaction to drop the initially created
empty SLRU dir keys, _and_ some CLog truncation going on.
Closes: https://github.com/neondatabase/cloud/issues/21516
## Summary of changes
- Update is_key_global and init_empty to handle SLRU dir keys properly
-- the only functional impact is that we avoid writing some spurious
keys in shards >0, but this makes testing much more robust.
- Make `test_clog_truncate` explicitly use a sharded tenant
The net result is that if one reverts #10080, then tests fail (i.e. this
PR is a reproducer for the issue)
This PR
- fixes smgr metrics https://github.com/neondatabase/neon/issues/9925
- adds an additional startup log line logging the current batching
config
- adds a histogram of batch sizes global and per-tenant
- adds a metric exposing the current batching config
The issue described #9925 is that before this PR, request latency was
only observed *after* batching.
This means that smgr latency metrics (most importantly getpage latency)
don't account for
- `wait_lsn` time
- time spent waiting for batch to fill up / the executor stage to pick
up the batch.
The fix is to use a per-request batching timer, like we did before the
initial batching PR.
We funnel those timers through the entire request lifecycle.
I noticed that even before the initial batching changes, we weren't
accounting for the time spent writing & flushing the response to the
wire.
This PR drive-by fixes that deficiency by dropping the timers at the
very end of processing the batch, i.e., after the `pgb.flush()` call.
I was **unable to maintain the behavior that we deduct
time-spent-in-throttle from various latency metrics.
The reason is that we're using a *single* counter in `RequestContext` to
track micros spent in throttle.
But there are *N* metrics timers in the batch, one per request.
As a consequence, the practice of consuming the counter in the drop
handler of each timer no longer works because all but the first timer
will encounter error `close() called on closed state`.
A failed attempt to maintain the current behavior can be found in
https://github.com/neondatabase/neon/pull/9951.
So, this PR remvoes the deduction behavior from all metrics.
I started a discussion on Slack about it the implications this has for
our internal SLO calculation:
https://neondb.slack.com/archives/C033RQ5SPDH/p1732910861704029
# Refs
- fixes https://github.com/neondatabase/neon/issues/9925
- sub-issue https://github.com/neondatabase/neon/issues/9377
- epic: https://github.com/neondatabase/neon/issues/9376
## Problem
When ingesting implicit `ClearVmBits` operations, we silently drop the
writes if the relation or page is unknown. There are implicit
assumptions around VM pages wrt. explicit/implicit updates, sharding,
and relation sizes, which can possibly drop writes incorrectly. Adding a
few metrics will allow us to investigate further and tighten up the
logic.
Touches #9855.
## Summary of changes
Add a `pageserver_wal_ingest_clear_vm_bits_unknown` metric to record
dropped `ClearVmBits` writes.
Also add comments clarifying the behavior of relation sizes on non-zero
shards.
## Problem
We don't have any observability for the relation size cache. We have
seen cache misses cause significant performance impact with high
relation counts.
Touches #9855.
## Summary of changes
Adds the following metrics:
* `pageserver_relsize_cache_entries`
* `pageserver_relsize_cache_hits`
* `pageserver_relsize_cache_misses`
* `pageserver_relsize_cache_misses_old`
## 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
Co-authored-by: Heikki Linnakangas <heikki@neon.tech>
Co-authored-by: Stas Kelvic <stas@neon.tech>
# Context
This PR contains PoC-level changes for a product feature that allows
onboarding large databases into Neon without going through the regular
data path.
# Changes
This internal RFC provides all the context
* https://github.com/neondatabase/cloud/pull/19799
In the language of the RFC, this PR covers
* the Importer code (`fast_import`)
* all the Pageserver changes (mgmt API changes, flow implementation,
etc)
* a basic test for the Pageserver changes
# Reviewing
As acknowledged in the RFC, the code added in this PR is not ready for
general availability.
Also, the **architecture is not to be discussed in this PR**, but in the
RFC and associated Slack channel instead.
Reviewers of this PR should take that into consideration.
The quality bar to apply during review depends on what area of the code
is being reviewed:
* Importer code (`fast_import`): practically anything goes
* Core flow (`flow.rs`):
* Malicious input data must be expected and the existing threat models
apply.
* The code must not be safe to execute on *dedicated* Pageserver
instances:
* This means in particular that tenants *on other* Pageserver instances
must not be affected negatively wrt data confidentiality, integrity or
availability.
* Other code: the usual quality bar
* Pay special attention to correct use of gate guards, timeline
cancellation in all places during shutdown & migration, etc.
* Consider the broader system impact; if you find potentially
problematic interactions with Storage features that were not covered in
the RFC, bring that up during the review.
I recommend submitting three separate reviews, for the three high-level
areas with different quality bars.
# References
(Internal-only)
* refs https://github.com/neondatabase/cloud/issues/17507
* refs https://github.com/neondatabase/company_projects/issues/293
* refs https://github.com/neondatabase/company_projects/issues/309
* refs https://github.com/neondatabase/cloud/issues/20646
---------
Co-authored-by: Stas Kelvich <stas.kelvich@gmail.com>
Co-authored-by: Heikki Linnakangas <heikki@neon.tech>
Co-authored-by: John Spray <john@neon.tech>
## Problem
We don't take advantage of queue depth generated by the compute
on the pageserver. We can process getpage requests more efficiently
by batching them.
## Summary of changes
Batch up incoming getpage requests that arrive within a configurable
time window (`server_side_batch_timeout`).
Then process the entire batch via one `get_vectored` timeline operation.
By default, no merging takes place.
## Testing
* **Functional**: https://github.com/neondatabase/neon/pull/9792
* **Performance**: will be done in staging/pre-prod
# Refs
* https://github.com/neondatabase/neon/issues/9377
* https://github.com/neondatabase/neon/issues/9376
Co-authored-by: Christian Schwarz <christian@neon.tech>
ref https://github.com/neondatabase/neon/issues/9441
The metrics from LR publisher testing project: ~300KB aux key deltas per
256MB files. Therefore, I think we can do compaction more aggressively
as these deltas are small and compaction can reduce layer download
latency. We also have a read path perf fix
https://github.com/neondatabase/neon/pull/9631 but I'd still combine the
read path fix with the reduce of the compaction threshold.
## Summary of changes
* reduce metadata compaction threshold
* use num of L1 delta layers as an indicator for metadata compaction
* dump more logs
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
https://github.com/neondatabase/neon/pull/9524 split the decoding and
interpretation step from ingestion.
The output of the first phase is a `wal_decoder::models::InterpretedWalRecord`.
Before this patch set that struct contained a list of `Value` instances.
We wish to lift the decoding and interpretation step to the safekeeper,
but it would be nice if the safekeeper gave us a batch containing the raw data instead of actual values.
## Summary of changes
Main goal here is to make `InterpretedWalRecord` hold a raw buffer which
contains pre-serialized Values.
For this we do:
1. Add a `SerializedValueBatch` type. This is `inmemory_layer::SerializedBatch` with some
extra functionality for extension, observing values for shard 0 and tests.
2. Replace `inmemory_layer::SerializedBatch` with `SerializedValueBatch`
3. Make `DatadirModification` maintain a `SerializedValueBatch`.
### `DatadirModification` changes
`DatadirModification` now maintains a `SerializedValueBatch` and extends
it as new WAL records come in (to avoid flushing to disk on every
record).
In turn, this cascaded into a number of modifications to
`DatadirModification`:
1. Replace `pending_data_pages` and `pending_zero_data_pages` with `pending_data_batch`.
2. Removal of `pending_zero_data_pages` and its cousin `on_wal_record_end`
3. Rename `pending_bytes` to `pending_metadata_bytes` since this is what it tracks now.
4. Adapting of various utility methods like `len`, `approx_pending_bytes` and `has_dirty_data_pages`.
Removal of `pending_zero_data_pages` and the optimisation associated
with it ((1) and (2)) deserves more detail.
Previously all zero data pages went through `pending_zero_data_pages`.
We wrote zero data pages when filling gaps caused by relation extension
(case A) and when handling special wal records (case B). If it happened
that the same WAL record contained a non zero write for an entry in
`pending_zero_data_pages` we skipped the zero write.
Case A: We handle this differently now. When ingesting the
`SerialiezdValueBatch` associated with one PG WAL record, we identify the gaps and fill the
them in one go. Essentially, we move from a per key process (gaps were filled after each
new key), and replace it with a per record process. Hence, the optimisation is not
required anymore.
Case B: When the handling of a special record needs to zero out a key,
it just adds that to the current batch. I inspected the code, and I
don't think the optimisation kicked in here.
## Problem
We wish to have high level WAL decoding logic in `wal_decoder::decoder`
module.
## Summary of Changes
For this we need the `Value` and `NeonWalRecord` types accessible there, so:
1. Move `Value` and `NeonWalRecord` to `pageserver::value` and
`pageserver::record` respectively.
2. Get rid of `pageserver::repository` (follow up from (1))
3. Move PG specific WAL record types to `postgres_ffi::walrecord`. In
theory they could live in `wal_decoder`, but it would create a circular
dependency between `wal_decoder` and `postgres_ffi`. Long term it makes
sense for those types to be PG version specific, so that will work out nicely.
4. Move higher level WAL record types (to be ingested by pageserver)
into `wal_decoder::models`
Related: https://github.com/neondatabase/neon/issues/9335
Epic: https://github.com/neondatabase/neon/issues/9329
## Problem
We have some known N^2 behaviors when it comes to large relation counts,
due to the monolithic encoding and full rewrites of of RelDirectory each
time a relation is added. Ordinarily our backpressure mechanisms give
"slow but steady" performance when creating/dropping/truncating
relations. However, in the case of a transaction abort, it is possible
for a single WAL record to drop an unbounded number of relations. The
results in an unavailable compute, as when it sends one of these
records, it can stall the pageserver's ingest for many minutes, even
though the compute only sent a small amount of WAL.
Closes https://github.com/neondatabase/neon/issues/9505
## Summary of changes
- Rewrite relation-dropping code to do one read/modify/write cycle of
RelDirectory, instead of doing it separately for each relation in a
loop.
- Add a test for the bug scenario encountered:
`test_tx_abort_with_many_relations`
The test has ~40s runtime on my workstation. About 1 second of that is
the part where we wait for ingest to catch up after a rollback, the rest
is the slowness of creating and truncating a large number of relations.
---------
Co-authored-by: Heikki Linnakangas <heikki@neon.tech>
Part of the aux v1 retirement
https://github.com/neondatabase/neon/issues/8623
## Summary of changes
Remove write/read path for aux v1, but keeping the config item and the
index part field for now.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
There is double update of resize cache in `put_rel_truncation`
Also `page_server_request` contains check that fork is MAIN_FORKNUM
which
1. is incorrect (because Vm/FSM pages are shreded in the same way as
MAIN fork pages and
2. is redundant because `page_server_request` is never called for `get
page` request so first part to OR condition is always true.
## Summary of changes
Remove redundant code
## 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>
Part of https://github.com/neondatabase/neon/issues/8002
Close https://github.com/neondatabase/neon/issues/8920
Legacy compaction (as well as gc-compaction) rely on the GC process to
remove unused layer files, but this relies on many factors (i.e., key
partition) to ensure data in a dropped table can be eventually removed.
In gc-compaction, we consider the keyspace information when doing the
compaction process. If a key is not in the keyspace, we will skip that
key and not include it in the final output.
However, this is not easy to implement because gc-compaction considers
branch points (i.e., retain_lsns) and the retained keyspaces could
change across different LSNs. Therefore, for now, we only remove aux v1
keys in the compaction process.
## Summary of changes
* Add `FilterIterator` to filter out keys.
* Integrate `FilterIterator` with gc-compaction.
* Add `collect_gc_compaction_keyspace` for a spec of keyspaces that can
be retained during the gc-compaction process.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
This adds preliminary PG17 support to Neon, based on RC1 / 2024-09-04
07b828e9d4
NOTICE: The data produced by the included version of the PostgreSQL fork
may not be compatible with the future full release of PostgreSQL 17 due to
expected or unexpected future changes in magic numbers and internals.
DO NOT EXPECT DATA IN V17-TENANTS TO BE COMPATIBLE WITH THE 17.0
RELEASE!
Co-authored-by: Anastasia Lubennikova <anastasia@neon.tech>
Co-authored-by: Alexander Bayandin <alexander@neon.tech>
Co-authored-by: Konstantin Knizhnik <knizhnik@neon.tech>
Co-authored-by: Heikki Linnakangas <heikki@neon.tech>
## Problem
In https://github.com/neondatabase/neon/pull/8621, validation of keys
during ingest was removed because the places where we actually store
keys are now past the point where we have already converted them to
CompactKey (i128) representation.
## Summary of changes
Reinstate validation at an earlier stage in ingest. This doesn't cover
literally every place we write a key, but it covers most cases where
we're trusting postgres to give us a valid key (i.e. one that doesn't
try and use a custom spacenode).
Addresses the 1.82 beta clippy lint `too_long_first_doc_paragraph` by
adding newlines to the first sentence if it is short enough, and making
a short first sentence if there is the need.
Part of https://github.com/neondatabase/neon/issues/8623
## Summary of changes
It seems that we have tenants with aux policy set to v1 but don't have
any aux files in the storage. It is still safe to force migrate them
without notifying the customers. This patch adds more details to the
warning to identify the cases where we have to reach out to the users
before retiring aux v1.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
Currently, DatadirModification keeps a key-indexed map of all pending
writes, even though we (almost) never need to read back dirty pages for
anything other than metadata pages (e.g. relation sizes).
Related: https://github.com/neondatabase/neon/issues/6345
## Summary of changes
- commit() modifications before ingesting database creation wal records,
so that they are guaranteed to be able to get() everything they need
directly from the underlying Timeline.
- Split dirty pages in DatadirModification into pending_metadata_pages
and pending_data_pages. The data ones don't need to be in a
key-addressable format, so they just go in a Vec instead.
- Special case handling of zero-page writes in DatadirModification,
putting them in a map which is flushed on the end of a WAL record. This
handles the case where during ingest, we might first write a zero page,
and then ingest a postgres write to that page. We used to do this via
the key-indexed map of writes, but in this PR we change the data page
write path to not bother indexing these by key.
My least favorite thing about this PR is that I needed to change the
DatadirModification interface to add the on_record_end call. This is not
very invasive because there's really only one place we use it, but it
changes the object's behaviour from being clearly an aggregation of many
records to having some per-record state. I could avoid this by
implicitly doing the work when someone calls set_lsn or commit -- I'm
open to opinions on whether that's cleaner or dirtier.
## Performance
There may be some efficiency improvement here, but the primary
motivation is to enable an earlier stage of ingest to operate without
access to a Timeline. The `pending_data_pages` part is the "fast path"
bulk write data that can in principle be generated without a Timeline,
in parallel with other ingest batches, and ultimately on the safekeeper.
`test_bulk_insert` on AX102 shows approximately the same results as in
the previous PR #8591:
```
------------------------------ Benchmark results -------------------------------
test_bulk_insert[neon-release-pg16].insert: 23.577 s
test_bulk_insert[neon-release-pg16].pageserver_writes: 5,428 MB
test_bulk_insert[neon-release-pg16].peak_mem: 637 MB
test_bulk_insert[neon-release-pg16].size: 0 MB
test_bulk_insert[neon-release-pg16].data_uploaded: 1,922 MB
test_bulk_insert[neon-release-pg16].num_files_uploaded: 8
test_bulk_insert[neon-release-pg16].wal_written: 1,382 MB
test_bulk_insert[neon-release-pg16].wal_recovery: 18.264 s
test_bulk_insert[neon-release-pg16].compaction: 0.052 s
```
It's better to reject invalid keys on the write path than storing it and
panic-ing the pageserver.
https://github.com/neondatabase/neon/issues/8636
## Summary of changes
If a key cannot be represented using i128, we don't allow writing that
key into the pageserver.
There are two versions of the check valid function: the normal one that
simply rejects i128 keys, and the stronger one that rejects all keys
that we don't support.
The current behavior when a key gets rejected is that safekeeper will
keep retrying streaming that key to the pageserver. And once such key
gets written, no new computes can be started. Therefore, there could be
a large amount of pageserver warnings if a key cannot be ingested. To
validate this behavior by yourself, the reviewer can (1) use the
stronger version of the valid check (2) run the following SQL.
```
set neon.regress_test_mode = true;
CREATE TABLESPACE regress_tblspace LOCATION '/Users/skyzh/Work/neon-test/tablespace';
CREATE SCHEMA testschema;
CREATE TABLE testschema.foo (i int) TABLESPACE regress_tblspace;
insert into testschema.foo values (1), (2), (3);
```
For now, I'd like to merge the patch with only rejecting non-i128 keys.
It's still unknown whether the stronger version covers all the cases
that basebackup doesn't support. Furthermore, the behavior of rejecting
a key will produce large amounts of warnings due to safekeeper retry.
Therefore, I'd like to reject the minimum set of keys that we don't
support (i128 ones) for now. (well, erroring out is better than panic on
`to_compact_key`)
The next step is to fix the safekeeper behavior (i.e., on such key
rejections, stop streaming WAL), so that we can properly stop writing.
An alternative solution is to simply drop these keys on the write path.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
part of https://github.com/neondatabase/neon/issues/8623
We want to discover potential aux v1 customers that we might have missed
from the migrations.
## Summary of changes
Log warnings on basebackup, load timeline, and the first put_file.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem/Solution
TimelineWriter::put_batch is simply a loop over individual puts. Each
put acquires and releases locks, and checks for potentially starting a
new layer. Batching these is more efficient, but more importantly
unlocks future changes where we can pre-build serialized buffers much
earlier in the ingest process, potentially even on the safekeeper
(imagine a future model where some variant of DatadirModification lives
on the safekeeper).
Ensuring that the values in put_batch are written to one layer also
enables a simplification upstream, where we no longer need to write
values in LSN-order. This saves us a sort, but also simplifies follow-on
refactors to DatadirModification: we can store metadata keys and data
keys separately at that level without needing to zip them together in
LSN order later.
## Why?
In this PR, these changes are simplify optimizations, but they are
motivated by evolving the ingest path in the direction of disentangling
extracting DatadirModification from Timeline. It may not obvious how
right now, but the general idea is that we'll end up with three phases
of ingest:
- A) Decode walrecords and build a datadirmodification with all the
simple data contents already in a big serialized buffer ready to write
to an ephemeral layer **<-- this part can be pipelined and parallelized,
and done on a safekeeper!**
- B) Let that datadirmodification see a Timeline, so that it can also
generate all the metadata updates that require a read-modify-write of
existing pages
- C) Dump the results of B into an ephemeral layer.
Related: https://github.com/neondatabase/neon/issues/8452
## Caveats
Doing a big monolithic buffer of values to write to disk is ordinarily
an anti-pattern: we prefer nice streaming I/O. However:
- In future, when we do this first decode stage on the safekeeper, it
would be inefficient to serialize a Vec of Value, and then later
deserialize it just to add blob size headers while writing into the
ephemeral layer format. The idea is that for bulk write data, we will
serialize exactly once.
- The monolithic buffer is a stepping stone to pipelining more of this:
by seriailizing earlier (rather than at the final put_value), we will be
able to parallelize the wal decoding and bulk serialization of data page
writes.
- The ephemeral layer's buffered writer already stalls writes while it
waits to flush: so while yes we'll stall for a couple milliseconds to
write a couple megabytes, we already have stalls like this, just
distributed across smaller writes.
## Benchmarks
This PR is primarily a stepping stone to safekeeper ingest filtering,
but also provides a modest efficiency improvement to the `wal_recovery`
part of `test_bulk_ingest`.
test_bulk_ingest:
```
test_bulk_insert[neon-release-pg16].insert: 23.659 s
test_bulk_insert[neon-release-pg16].pageserver_writes: 5,428 MB
test_bulk_insert[neon-release-pg16].peak_mem: 626 MB
test_bulk_insert[neon-release-pg16].size: 0 MB
test_bulk_insert[neon-release-pg16].data_uploaded: 1,922 MB
test_bulk_insert[neon-release-pg16].num_files_uploaded: 8
test_bulk_insert[neon-release-pg16].wal_written: 1,382 MB
test_bulk_insert[neon-release-pg16].wal_recovery: 18.981 s
test_bulk_insert[neon-release-pg16].compaction: 0.055 s
vs. tip of main:
test_bulk_insert[neon-release-pg16].insert: 24.001 s
test_bulk_insert[neon-release-pg16].pageserver_writes: 5,428 MB
test_bulk_insert[neon-release-pg16].peak_mem: 604 MB
test_bulk_insert[neon-release-pg16].size: 0 MB
test_bulk_insert[neon-release-pg16].data_uploaded: 1,922 MB
test_bulk_insert[neon-release-pg16].num_files_uploaded: 8
test_bulk_insert[neon-release-pg16].wal_written: 1,382 MB
test_bulk_insert[neon-release-pg16].wal_recovery: 23.586 s
test_bulk_insert[neon-release-pg16].compaction: 0.054 s
```
We can get CompactionError::Other(Cancelled) via the error handling with
a few ways.
[evidence](https://neon-github-public-dev.s3.amazonaws.com/reports/pr-8655/10301613380/index.html#suites/cae012a1e6acdd9fdd8b81541972b6ce/653a33de17802bb1/).
Hopefully fix it by:
1. replace the `map_err` which hid the
`GetReadyAncestorError::Cancelled` with `From<GetReadyAncestorError> for
GetVectoredError` conversion
2. simplifying the code in pgdatadir_mapping to eliminate the token
anyhow wrapping for deserialization errors
3. stop wrapping GetVectoredError as anyhow errors
4. stop wrapping PageReconstructError as anyhow errors
Additionally, produce warnings if we treat any other error (as was legal
before this PR) as missing key.
Cc: #8708.
## Problem
Postgres is using `access()` function in `GetNewRelFileNumber` to check
if assigned relfilenumber is not used for any other relation. This check
will not work in Neon, because we do not have all files in local
storage.
## Summary of changes
Use smgrexists() instead which will check at page server if such
relfilenode is used.
## 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>
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`.
## 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
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
## 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
Some test cases add random keys into the timeline, but it is not part of
the `collect_keyspace`, this will cause compaction remove the keys.
The pull request adds a field to supply extra keyspaces during unit
tests.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
Closes#7406.
## Problem
When a `get_lsn_by_timestamp` request is cancelled, an anyhow error is
exposed to handle that case, which verbosely logs the error. However, we
don't benefit from having the full backtrace provided by anyhow in this
case.
## Summary of changes
This PR introduces a new `ApiError` type to handle errors caused by
cancelled request more robustly.
- A new enum variant `ApiError::Cancelled`
- Currently the cancelled request is mapped to status code 500.
- Need to handle this error in proxy's `http_util` as well.
- Added a failpoint test to simulate cancelled `get_lsn_by_timestamp`
request.
Signed-off-by: Yuchen Liang <yuchen@neon.tech>
Store logical replication origin in KV storage
## Problem
See #6977
## Summary of changes
* Extract origin_lsn from commit WAl record
* Add ReplOrigin key to KV storage and store origin_lsn
* In basebackup replace snapshot origin_lsn with last committed
origin_lsn at basebackup LSN
## 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
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
Co-authored-by: Konstantin Knizhnik <knizhnik@neon.tech>
Co-authored-by: Alex Chi Z <chi@neon.tech>
The keyspace utils like `is_rel_size_key` or `is_rel_fsm_block_key` and
many others are free functions and have to be either imported separately
or specified with the full path starting in `pageserver_api:🔑:`.
This is less convenient than if these functions were just inherent
impls.
Follow-up of #7890Fixes#6438
## Problem
In all cases, AncestorStopping is equivalent to Cancelled.
This became more obvious in
https://github.com/neondatabase/neon/pull/7912#discussion_r1620582309
when updating these error types.
## Summary of changes
- Remove AncestorStopping, always use Cancelled instead
## Problem
Looking at several noisy shutdown logs:
- In https://github.com/neondatabase/neon/issues/7861 we're hitting a
log error with `InternalServerError(timeline shutting down\n'` on the
checkpoint API handler.
- In the field, we see initial_logical_size_calculation errors on
shutdown, via DownloadError
- In the field, we see errors logged from layer download code
(independent of the error propagated) during shutdown
Closes: https://github.com/neondatabase/neon/issues/7861
## Summary of changes
The theme of these changes is to avoid propagating anyhow::Errors for
cases that aren't really unexpected error cases that we might want a
stacktrace for, and avoid "Other" error variants unless we really do
have unexpected error cases to propagate.
- On the flush_frozen_layers path, use the `FlushLayerError` type
throughout, rather than munging it into an anyhow::Error. Give
FlushLayerError an explicit from_anyhow helper that checks for timeline
cancellation, and uses it to give a Cancelled error instead of an Other
error when the timeline is shutting down.
- In logical size calculation, remove BackgroundCalculationError (this
type was just a Cancelled variant and an Other variant), and instead use
CalculateLogicalSizeError throughout. This can express a
PageReconstructError, and has a From impl that translates cancel-like
page reconstruct errors to Cancelled.
- Replace CalculateLogicalSizeError's Other(anyhow::Error) variant case
with a Decode(DeserializeError) variant, as this was the only kind of
error we actually used in the Other case.
- During layer download, drop out early if the timeline is shutting
down, so that we don't do an `error!()` log of the shutdown error in
this case.
