## Problem
Followup to https://github.com/neondatabase/neon/pull/6776
While #6776 makes compaction safe on sharded tenants, the logic for
keyspace partitioning remains inefficient: it assumes that the size of
data on a pageserver can be calculated simply as the range between start
and end of a Range -- this is not the case in sharded tenants, where
data within a range belongs to a variety of shards.
Closes: https://github.com/neondatabase/neon/issues/6774
## Summary of changes
I experimented with using a sharding-aware range type in KeySpace to
replace all the Range<Key> uses, but the impact on other code was quite
large (many places use the ranges), and not all of them need this
property of being able to approximate the physical size of data within a
key range.
So I compromised on expressing this as a ShardedRange type, but only
using that type selctively: during keyspace repartition, and in tiered
compaction when accumulating key ranges.
- keyspace partitioning methods take sharding parameters as an input
- new `ShardedRange` type wraps a Range<Key> and a shard identity
- ShardedRange::page_count is the shard-aware replacement for
key_range_size
- Callers that don't need to be shard-aware (e.g. vectored get code that
just wants to count the number of keys in a keyspace) can use
ShardedRange::raw_size to get the faster, shard-naive code (same as old
`key_range_size`)
- Compaction code is updated to carry a shard identity so that it can
use shard aware calculations
- Unit tests for the new fragmentation logic.
- Add a test for compaction on sharded tenants, that validates that we
generate appropriately sized image layers (this fails before fixing
keyspace partitioning)
## Problem
Sometimes we have test data in the form of S3 contents that we would
like to run live in a neon_local environment.
## Summary of changes
- Add a storage controller API that imports an existing tenant.
Currently this is equivalent to doing a create with a high generation
number, but in future this would be something smarter to probe S3 to
find the shards in a tenant and find generation numbers.
- Add a `neon_local` command that invokes the import API, and then
inspects timelines in the newly attached tenant to create matching
branches.
extracted from https://github.com/neondatabase/neon/pull/7468, part of
https://github.com/neondatabase/neon/issues/7462.
In the page server, we use i128 (instead of u128) to do the integer
representation of the key, which indicates that the highest bit of the
key should not be 1. This constraints our keyspace to <= 0x7F.
Also fix the bug of `to_i128` that dropped the highest 4b. Now we keep
3b of them, dropping the sign bit.
And on that, we shrink the metadata keyspace to 0x60-0x7F for now, and
once we add support for u128, we can have a larger metadata keyspace.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
Changing metadata format is not easy. This pull request adds a
tenant-level flag on whether to enable aux file v2. As long as we don't
roll this out to the user and guarantee our staging projects can persist
tenant config correctly, we can test the aux file v2 change with setting
this flag. Previous discussion at
https://github.com/neondatabase/neon/pull/7424.
Signed-off-by: Alex Chi Z <chi@neon.tech>
In the old protocol version, the client sent with each request:
- latest: bool. If true, the client requested the latest page
version, and the 'lsn' was just a hint of when the page was last
modified
- lsn: Lsn, the page version to return
This protocol didn't allow requesting a page at a particular
non-latest LSN and *also* sending a hint on when the page was last
modified. That put a read only compute into an awkward position where
it had to either request each page at the replay-LSN, which could be
very close to the last LSN written in the primary and therefore
require the pageserver to wait for it to arrive, or an older LSN which
could already be garbage collected in the pageserver, resulting in an
error. The new protocol version fixes that by allowing a read only
compute to send both LSNs.
To use the new protocol version, use "pagestream_v2" command instead
of just "pagestream". The old protocol version is still supported, for
compatibility with old computes (and in fact there is no client
support yet, it is added by the next commit).
## Problem
We are currently supporting two read paths. No bueno.
## Summary of changes
High level: use vectored read path to serve get page requests - gated by
`get_impl` config
Low level:
1. Add ps config, `get_impl` to specify which read path to use when
serving get page requests
2. Fix base cached image handling for the vectored read path. This was
subtly broken: previously we
would not mark keys that went past their cached lsn as complete. This is
a self standing change which
could be its own PR, but I've included it here because writing separate
tests for it is tricky.
3. Fork get page to use either the legacy or vectored implementation
4. Validate the use of vectored read path when serving get page requests
against the legacy implementation.
Controlled by `validate_vectored_get` ps config.
5. Use the vectored read path to serve get page requests in tests (with
validation).
## Note
Since the vectored read path does not go through the page cache to read
buffers, this change also amounts to a removal of the buffer page cache. Materialized page cache
is still used.
Currently we move data to the intended storage class via lifecycle
rules, but those are a daily batch job so data first spends up to a day
in standard storage.
Therefore, make it possible to specify the storage class used for
uploads to S3 so that the data doesn't have to be migrated
automatically.
The advantage of this is that it gives cleaner billing reports.
Part of https://github.com/neondatabase/cloud/issues/11348
## Problem
If the previous step of the vectored left no further keyspace to
investigate (i.e. keyspace remains empty after removing keys completed in the previous step),
then we'd still grab the layers lock, potentially add an in-mem layer to the fringe
and at some further point read its index without reading any values from it.
## Summary of changes
If there's nothing left in the current keyspace, then skip the search
and just select the next item from the fringe as usual.
When running `test_pg_regress[release-pg16]` with the vectored read path
for singular gets this improved perf drastically (see PR cover letter).
## Correctness
Since no keys remained from the previous range (i.e. we are on a leaf
node) there's nothing that search can find in deeper nodes.
## Problem
Split off from https://github.com/neondatabase/neon/pull/7399, which is
the first piece of code that does a WithDelimiter object listing using a
prefix that isn't a full directory name.
## Summary of changes
- Revise list function to not append a `/` to the prefix -- prefixes
don't have to end with a slash.
- Fix local_fs implementation of list to not assume that WithDelimiter
case will always use a directory as a prerfix.
- Remove `list_files`, `list_prefixes` wrappers, as they add little
value and obscure the underlying list function -- we need callers to
understand the semantics of what they're really calling (listobjectsv2)
Extracted from https://github.com/neondatabase/neon/pull/7375. We assume
everything >= 0x80 are metadata keys. AUX file keys are part of the
metadata keys, and we use `0x90` as the prefix for AUX file keys.
The AUX file encoding is described in the code comment. We use xxhash128
as the hash algorithm. It seems to be portable according to the
introduction,
> xxHash is an Extremely fast Hash algorithm, processing at RAM speed
limits. Code is highly portable, and produces hashes identical across
all platforms (little / big endian).
...though whether the Rust version follows the same convention is
unknown and might need manual review of the library. Anyways, we can
always change the hash algorithm before rolling it out in
staging/end-user, and I made a quick decision to use xxhash here because
it generates 128b hash + portable. We can save the discussion of which
hash algorithm to use later.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
Vectored get would descend into ancestor timelines for aux files.
This is not the behaviour of the legacy read path and blocks cutting
over to the vectored read path.
Fixes https://github.com/neondatabase/neon/issues/7379
## Summary of Changes
Treat non inherited keys specially in vectored get. At the point when
we want to descend into the ancestor mark all pending non inherited keys
as errored out at the key level. Note that this diverges from the
standard vectored get behaviour for missing keys which is a top level
error. This divergence is required to avoid blocking compaction in case
such an error is encountered when compaction aux files keys. I'm pretty
sure the bug I just described predates the vectored get implementation,
but it's still worth fixing.
## Problem
- #7451
INIT_FORKNUM blocks must be stored on shard 0 to enable including them
in basebackup.
This issue can be missed in simple tests because creating an unlogged
table isn't sufficient -- to repro I had to create an _index_ on an
unlogged table (then restart the endpoint).
Closes: #7451
## Summary of changes
- Add a reproducer for the issue.
- Tweak the condition for `key_is_shard0` to include anything that isn't
a normal relation block _and_ any normal relation block whose forknum is
INIT_FORKNUM.
- To enable existing databases to recover from the issue, add a special
case that omits relations if they were stored on the wrong INITFORK.
This enables postgres to start and the user to drop the table and
recreate it.
There were two issues with the test at page boundaries:
1. If the first logical message with 10 bytes payload crossed a page
boundary, the calculated 'base_size' was too large because it included
the page header.
2. If it was inserted near the end of a page so that there was not
enough room for another one, we did "remaining_lsn += XLOG_BLCKSZ" but
that didn't take into account the page headers either.
As a result, the test would fail if the WAL insert position at the
beginning of the test was too close to the end of a WAL page. Fix the
calculations by repeating the 10-byte logical message if the starting
position is not suitable.
I bumped into this with PR #7377; it changed the arguments of a few SQL
functions in neon_test_utils extension, which changed the WAL positions
slightly, and caused a test failure.
This is similar to https://github.com/neondatabase/neon/pull/7436, but
for different test.
As noted in the comment, the craft_internal() function fails if the
inserted WAL happens to land at page boundary. I bumped into that with
PR #7377; it changed the arguments of a few SQL functions in
neon_test_utils extension, which changed the WAL positions slightly, and
caused a test failure.
#7030 introduced an annoying papercut, deeming a failure to acquire a
strong reference to `LayerInner` from `DownloadedLayer::drop` as a
canceled eviction. Most of the time, it wasn't that, but just timeline
deletion or tenant detach with the layer not wanting to be deleted or
evicted.
When a Layer is dropped as part of a normal shutdown, the `Layer` is
dropped first, and the `DownloadedLayer` the second. Because of this, we
cannot detect eviction being canceled from the `DownloadedLayer::drop`.
We can detect it from `LayerInner::drop`, which this PR adds.
Test case is added which before had 1 started eviction, 2 canceled. Now
it accurately finds 1 started, 1 canceled.
Before this PR, the `nix::poll::poll` call would stall the executor.
This PR refactors the `walredo::process` module to allow for different
implementations, and adds a new `async` implementation which uses
`tokio::process::ChildStd{in,out}` for IPC.
The `sync` variant remains the default for now; we'll do more testing in
staging and gradual rollout to prod using the config variable.
Performance
-----------
I updated `bench_walredo.rs`, demonstrating that a single `async`-based
walredo manager used by N=1...128 tokio tasks has lower latency and
higher throughput.
I further did manual less-micro-benchmarking in the real pageserver
binary.
Methodology & results are published here:
https://neondatabase.notion.site/2024-04-08-async-walredo-benchmarking-8c0ed3cc8d364a44937c4cb50b6d7019?pvs=4
tl;dr:
- use pagebench against a pageserver patched to answer getpage request &
small-enough working set to fit into PS PageCache / kernel page cache.
- compare knee in the latency/throughput curve
- N tenants, each 1 pagebench clients
- sync better throughput at N < 30, async better at higher N
- async generally noticable but not much worse p99.X tail latencies
- eyeballing CPU efficiency in htop, `async` seems significantly more
CPU efficient at ca N=[0.5*ncpus, 1.5*ncpus], worse than `sync` outside
of that band
Mental Model For Walredo & Scheduler Interactions
-------------------------------------------------
Walredo is CPU-/DRAM-only work.
This means that as soon as the Pageserver writes to the pipe, the
walredo process becomes runnable.
To the Linux kernel scheduler, the `$ncpus` executor threads and the
walredo process thread are just `struct task_struct`, and it will divide
CPU time fairly among them.
In `sync` mode, there are always `$ncpus` runnable `struct task_struct`
because the executor thread blocks while `walredo` runs, and the
executor thread becomes runnable when the `walredo` process is done
handling the request.
In `async` mode, the executor threads remain runnable unless there are
no more runnable tokio tasks, which is unlikely in a production
pageserver.
The above means that in `sync` mode, there is an implicit concurrency
limit on concurrent walredo requests (`$num_runtimes *
$num_executor_threads_per_runtime`).
And executor threads do not compete in the Linux kernel scheduler for
CPU time, due to the blocked-runnable-ping-pong.
In `async` mode, there is no concurrency limit, and the walredo tasks
compete with the executor threads for CPU time in the kernel scheduler.
If we're not CPU-bound, `async` has a pipelining and hence throughput
advantage over `sync` because one executor thread can continue
processing requests while a walredo request is in flight.
If we're CPU-bound, under a fair CPU scheduler, the *fixed* number of
executor threads has to share CPU time with the aggregate of walredo
processes.
It's trivial to reason about this in `sync` mode due to the
blocked-runnable-ping-pong.
In `async` mode, at 100% CPU, the system arrives at some (potentially
sub-optiomal) equilibrium where the executor threads get just enough CPU
time to fill up the remaining CPU time with runnable walredo process.
Why `async` mode Doesn't Limit Walredo Concurrency
--------------------------------------------------
To control that equilibrium in `async` mode, one may add a tokio
semaphore to limit the number of in-flight walredo requests.
However, the placement of such a semaphore is non-trivial because it
means that tasks queuing up behind it hold on to their request-scoped
allocations.
In the case of walredo, that might be the entire reconstruct data.
We don't limit the number of total inflight Timeline::get (we only
throttle admission).
So, that queue might lead to an OOM.
The alternative is to acquire the semaphore permit *before* collecting
reconstruct data.
However, what if we need to on-demand download?
A combination of semaphores might help: one for reconstruct data, one
for walredo.
The reconstruct data semaphore permit is dropped after acquiring the
walredo semaphore permit.
This scheme effectively enables both a limit on in-flight reconstruct
data and walredo concurrency.
However, sizing the amount of permits for the semaphores is tricky:
- Reconstruct data retrieval is a mix of disk IO and CPU work.
- If we need to do on-demand downloads, it's network IO + disk IO + CPU
work.
- At this time, we have no good data on how the wall clock time is
distributed.
It turns out that, in my benchmarking, the system worked fine without a
semaphore. So, we're shipping async walredo without one for now.
Future Work
-----------
We will do more testing of `async` mode and gradual rollout to prod
using the config flag.
Once that is done, we'll remove `sync` mode to avoid the temporary code
duplication introduced by this PR.
The flag will be removed.
The `wait()` for the child process to exit is still synchronous; the
comment [here](
655d3b6468/pageserver/src/walredo.rs (L294-L306))
is still a valid argument in favor of that.
The `sync` mode had another implicit advantage: from tokio's
perspective, the calling task was using up coop budget.
But with `async` mode, that's no longer the case -- to tokio, the writes
to the child process pipe look like IO.
We could/should inform tokio about the CPU time budget consumed by the
task to achieve fairness similar to `sync`.
However, the [runtime function for this is
`tokio_unstable`](`https://docs.rs/tokio/latest/tokio/task/fn.consume_budget.html).
Refs
----
refs #6628
refs https://github.com/neondatabase/neon/issues/2975
No functional changes, this is a comments/naming PR.
While merging sharding changes, some cleanup of the shard.rs types was
deferred.
In this PR:
- Rename `is_zero` to `is_shard_zero` to make clear that this method
doesn't literally mean that the entire object is zeros, just that it
refers to the 0th shard in a tenant.
- Pull definitions of types to the top of shard.rs and add a big comment
giving an overview of which type is for what.
Closes: https://github.com/neondatabase/neon/issues/6072
## Problem
My benchmarks show that prometheus is not very good.
https://github.com/conradludgate/measured
We're already using it in storage_controller and it seems to be working
well.
## Summary of changes
Replace prometheus with my new measured crate in proxy only.
Apologies for the large diff. I tried to keep it as minimal as I could.
The label types add a bit of boiler plate (but reduce the chance we
mistype the labels), and some of our custom metrics like CounterPair and
HLL needed to be rewritten.
## Problem
Some awkwardness in the measured API.
Missing process metrics.
## Summary of changes
Update measured to use the new convenience setup features.
Added measured-process lib.
Added measured support for libmetrics
## Problem
We have two places that use a helper (`ser_rfc3339_millis`) to get serde
to stringify SystemTimes into the desired format.
## Summary of changes
Created a new module `utils::serde_system_time` and inside it a wrapper
type `SystemTime` for `std::time::SystemTime` that
serializes/deserializes to the RFC3339 format.
This new type is then used in the two places that were previously using
the helper for serialization, thereby eliminating the need to decorate
structs.
Closes#7151.
This PR is an off-by-default revision v2 of the (since-reverted) PR
#6555 / commit `3220f830b7fbb785d6db8a93775f46314f10a99b`.
See that PR for details on why running with a single runtime is
desirable and why we should be ready.
We reverted #6555 because it showed regressions in prodlike cloudbench,
see the revert commit message `ad072de4209193fd21314cf7f03f14df4fa55eb1`
for more context.
This PR makes it an opt-in choice via an env var.
The default is to use the 4 separate runtimes that we have today, there
shouldn't be any performance change.
I tested manually that the env var & added metric works.
```
# undefined env var => no change to before this PR, uses 4 runtimes
./target/debug/neon_local start
# defining the env var enables one-runtime mode, value defines that one runtime's configuration
NEON_PAGESERVER_USE_ONE_RUNTIME=current_thread ./target/debug/neon_local start
NEON_PAGESERVER_USE_ONE_RUNTIME=multi_thread:1 ./target/debug/neon_local start
NEON_PAGESERVER_USE_ONE_RUNTIME=multi_thread:2 ./target/debug/neon_local start
NEON_PAGESERVER_USE_ONE_RUNTIME=multi_thread:default ./target/debug/neon_local start
```
I want to use this change to do more manualy testing and potentially
testing in staging.
Future Work
-----------
Testing / deployment ergonomics would be better if this were a variable
in `pageserver.toml`.
It can be done, but, I don't need it right now, so let's stick with the
env var.
The binary etc were renamed some time ago, but the path in the source
tree remained "attachment_service" to avoid disruption to ongoing PRs.
There aren't any big PRs out right now, so it's a good time to cut over.
- Rename `attachment_service` to `storage_controller`
- Move it to the top level for symmetry with `storage_broker` & to avoid
mixing the non-prod neon_local stuff (`control_plane/`) with the storage
controller which is a production component.
Updates the `test-context` dev-dependency of the `remote_storage` crate
to 0.3. This removes a lot of `async_trait` instances.
Related earlier work: #6305, #6464
Add support for backing up partial segments to remote storage. Disabled
by default, can be enabled with `--partial-backup-enabled`.
Safekeeper timeline has a background task which is subscribed to
`commit_lsn` and `flush_lsn` updates. After the partial segment was
updated (`flush_lsn` was changed), the segment will be uploaded to S3 in
about 15 minutes.
The filename format for partial segments is
`Segment_Term_Flush_Commit_skNN.partial`, where:
- `Segment` – the segment name, like `000000010000000000000001`
- `Term` – current term
- `Flush` – flush_lsn in hex format `{:016X}`, e.g. `00000000346BC568`
- `Commit` – commit_lsn in the same hex format
- `NN` – safekeeper_id, like `1`
The full object name example:
`000000010000000000000002_2_0000000002534868_0000000002534410_sk1.partial`
Each safekeeper will keep info about remote partial segments in its
control file. Code updates state in the control file before doing any S3
operations. This way control file stores information about all
potentially existing remote partial segments and can clean them up after
uploading a newer version.
Closes#6336
We want to move the code base away from task_mgr.
This PR refactors the walreceiver code such that it doesn't use
`task_mgr` anymore.
# Background
As a reminder, there are three tasks in a Timeline that's ingesting WAL.
`WalReceiverManager`, `WalReceiverConnectionHandler`, and
`WalReceiverConnectionPoller`.
See the documentation in `task_mgr.rs` for how they interact.
Before this PR, cancellation was requested through
task_mgr::shutdown_token() and `TaskHandle::shutdown`.
Wait-for-task-finish was implemented using a mixture of
`task_mgr::shutdown_tasks` and `TaskHandle::shutdown`.
This drawing might help:
<img width="300" alt="image"
src="https://github.com/neondatabase/neon/assets/956573/b6be7ad6-ecb3-41d0-b410-ec85cb8d6d20">
# Changes
For cancellation, the entire WalReceiver task tree now has a
`child_token()` of `Timeline::cancel`. The `TaskHandle` no longer is a
cancellation root.
This means that `Timeline::cancel.cancel()` is propagated.
For wait-for-task-finish, all three tasks in the task tree hold the
`Timeline::gate` open until they exit.
The downside of using the `Timeline::gate` is that we can no longer wait
for just the walreceiver to shut down, which is particularly relevant
for `Timeline::flush_and_shutdown`.
Effectively, it means that we might ingest more WAL while the
`freeze_and_flush()` call is ongoing.
Also, drive-by-fix the assertiosn around task kinds in `wait_lsn`. The
check for `WalReceiverConnectionHandler` was ineffective because that
never was a task_mgr task, but a TaskHandle task. Refine the assertion
to check whether we would wait, and only fail in that case.
# Alternatives
I contemplated (ab-)using the `Gate` by having a separate `Gate` for
`struct WalReceiver`.
All the child tasks would use _that_ gate instead of `Timeline::gate`.
And `struct WalReceiver` itself would hold an `Option<GateGuard>` of the
`Timeline::gate`.
Then we could have a `WalReceiver::stop` function that closes the
WalReceiver's gate, then drops the `WalReceiver::Option<GateGuard>`.
However, such design would mean sharing the WalReceiver's `Gate` in an
`Arc`, which seems awkward.
A proper abstraction would be to make gates hierarchical, analogous to
CancellationToken.
In the end, @jcsp and I talked it over and we determined that it's not
worth the effort at this time.
# Refs
part of #7062
## Problem
During incidents, we may need to quickly access the storage controller's
API without trying API client code or crafting `curl` CLIs on the fly. A
basic CLI client is needed for this.
## Summary of changes
- Update storage controller node listing API to only use public types in
controller_api.rs
- Add a storage controller API for listing tenants
- Add a basic test that the CLI can list and modify nodes and tenants.
## Problem
Part of the legacy (but current) compaction algorithm is to find a stack
of overlapping delta layers which will be turned
into an image layer. This operation is exponential in terms of the
number of matching layers and we do it roughly every 20 seconds.
## Summary of changes
Only check if a new image layer is required if we've ingested a certain
amount of WAL since the last check.
The amount of wal is expressed in terms of multiples of checkpoint
distance, with the intuition being that
that there's little point doing the check if we only have two new L1
layers (not enough to create a new image).
## Problem
In the event of bugs with scheduling or reconciliation, we need to be
able to switch this off at a per-tenant granularity.
This is intended to mitigate risk of issues with
https://github.com/neondatabase/neon/pull/7181, which makes scheduling
more involved.
Closes: #7103
## Summary of changes
- Introduce a scheduling policy per tenant, with API to set it
- Refactor persistent.rs helpers for updating tenants to be more general
- Add tests
## Problem
https://github.com/neondatabase/cloud/issues/9642
## Summary of changes
1. Make `EndpointRateLimiter` generic, renamed as `BucketRateLimiter`
2. Add support for claiming multiple tokens at once
3. Add `AuthRateLimiter` alias.
4. Check `(Endpoint, IP)` pair during authentication, weighted by how
many hashes proxy would be doing.
TODO: handle ipv6 subnets. will do this in a separate PR.
Postgres can always write some more WAL, so previous checks that WAL doesn't
change after something had been crafted were wrong; remove them. Add comments
here and there.
should fix https://github.com/neondatabase/neon/issues/4691
Release notes: https://blog.rust-lang.org/2024/03/21/Rust-1.77.0.html
Thanks to #6886 the diff is reasonable, only for one new lint
`clippy::suspicious_open_options`. I added `truncate()` calls to the
places where it is obviously the right choice to me, and added allows
everywhere else, leaving it for followups.
I had to specify cargo install --locked because the build would fail otherwise.
This was also recommended by upstream.
This change improves the resilience of the system to unclean restarts.
Previously, re-attach responses only included attached tenants
- If the pageserver had local state for a secondary location, it would
remain, but with no guarantee that it was still _meant_ to be there.
After this change, the pageserver will only retain secondary locations
if the /re-attach response indicates that they should still be there.
- If the pageserver had local state for an attached location that was
omitted from a re-attach response, it would be entirely detached. This
is wasteful in a typical HA setup, where an offline node's tenants might
have been re-attached elsewhere before it restarts, but the offline
node's location should revert to a secondary location rather than being
wiped. Including secondary tenants in the re-attach response enables the
pageserver to avoid throwing away local state unnecessarily.
In this PR:
- The re-attach items are extended with a 'mode' field.
- Storage controller populates 'mode'
- Pageserver interprets it (default is attached if missing) to construct
either a SecondaryTenant or a Tenant.
- A new test exercises both cases.
## Problem
Storage controller had basically no metrics.
## Summary of changes
1. Migrate the existing metrics to use Conrad's
[`measured`](https://docs.rs/measured/0.0.14/measured/) crate.
2. Add metrics for incoming http requests
3. Add metrics for outgoing http requests to the pageserver
4. Add metrics for outgoing pass through requests to the pageserver
5. Add metrics for database queries
Note that the metrics response for the attachment service does not use
chunked encoding like the rest of the metrics endpoints. Conrad has
kindly extended the crate such that it can now be done. Let's leave it
for a follow-up since the payload shouldn't be that big at this point.
Fixes https://github.com/neondatabase/neon/issues/6875
This is a mixed bag of changes split out for separate review while
working on other things, and batched together to reduce load on CI
runners. Each commits stands alone for review purposes:
- do_tenant_shard_split was a long function and had a synchronous
validation phase at the start that could readily be pulled out into a
separate function. This also avoids the special casing of
ApiError::BadRequest when deciding whether an abort is needed on errors
- Add a 'describe' API (GET on tenant ID) that will enable storcon-cli
to see what's going on with a tenant
- the 'locate' API wasn't really meant for use in the field. It's for
tests: demote it to the /debug/ prefix
- The `Single` placement policy was a redundant duplicate of Double(0),
and Double was a bad name. Rename it Attached.
(https://github.com/neondatabase/neon/issues/7107)
- Some neon_local commands were added for debug/demos, which are now
replaced by commands in storcon-cli (#7114 ). Even though that's not
merged yet, we don't need the neon_local ones any more.
Closes https://github.com/neondatabase/neon/issues/7107
## Backward compat of Single/Double -> `Attached(n)` change
A database migration is used to convert any existing values.
Add shard_number to PageserverFeedback and parse it on the compute side.
When compute receives a new ps_feedback, it calculates min LSNs among
feedbacks from all shards, and uses those LSNs for backpressure.
Add `test_sharding_backpressure` to verify that backpressure slows down
compute to wait for the slowest shard.
## Problem
The existing secondary download API relied on the caller to wait as long
as it took to complete -- for large shards that could be a long time, so
typical clients that might have a baked-in ~30s timeout would have a
problem.
## Summary of changes
- Take a `wait_ms` query parameter to instruct the pageserver how long
to wait: if the download isn't complete in this duration, then 201 is
returned instead of 200.
- For both 200 and 201 responses, include response body describing
download progress, in terms of layers and bytes. This is sufficient for
the caller to track how much data is being transferred and log/present
that status.
- In storage controller live migrations, use this API to apply a much
longer outer timeout, with smaller individual per-request timeouts, and
log the progress of the downloads.
- Add a test that injects layer download delays to exercise the new
behavior
# Problem
On-demand downloads are still using `tokio::fs`, which we know is
inefficient.
# Changes
- Add `pagebench ondemand-download-churn` to quantify on-demand download
throughput
- Requires dumping layer map, which required making `history_buffer`
impl `Deserialize`
- Implement an equivalent of `tokio::io::copy_buf` for owned buffers =>
`owned_buffers_io` module and children.
- Make layer file download sensitive to `io_engine::get()`, using
VirtualFile + above copy loop
- For this, I had to move some code into the `retry_download`, e.g.,
`sync_all()` call.
Drive-by:
- fix missing escaping in `scripts/ps_ec2_setup_instance_store`
- if we failed in retry_download to create a file, we'd try to remove
it, encounter `NotFound`, and `abort()` the process using
`on_fatal_io_error`. This PR adds treats `NotFound` as a success.
# Testing
Functional
- The copy loop is generic & unit tested.
Performance
- Used the `ondemand-download-churn` benchmark to manually test against
real S3.
- Results (public Notion page):
https://neondatabase.notion.site/Benchmarking-tokio-epoll-uring-on-demand-downloads-2024-04-15-newer-code-03c0fdc475c54492b44d9627b6e4e710?pvs=4
- Performance is equivalent at low concurrency. Jumpier situation at
high concurrency, but, still less CPU / throughput with
tokio-epoll-uring.
- It’s a win.
# Future Work
Turn the manual performance testing described in the above results
document into a performance regression test:
https://github.com/neondatabase/neon/issues/7146
Aiming for the design where `heavier_once_cell::OnceCell` is initialized
by a future factory lead to awkwardness with how
`LayerInner::get_or_maybe_download` looks right now with the `loop`. The
loop helps with two situations:
- an eviction has been scheduled but has not yet happened, and a read
access should cancel the eviction
- a previous `LayerInner::get_or_maybe_download` that canceled a pending
eviction was canceled leaving the `heavier_once_cell::OnceCell`
uninitialized but needing repair by the next
`LayerInner::get_or_maybe_download`
By instead supporting detached initialization in
`heavier_once_cell::OnceCell` via an `OnceCell::get_or_detached_init`,
we can fix what the monolithic #7030 does:
- spawned off download task initializes the
`heavier_once_cell::OnceCell` regardless of the download starter being
canceled
- a canceled `LayerInner::get_or_maybe_download` no longer stops
eviction but can win it if not canceled
Split off from #7030.
Cc: #5331
## Problem
These fields were only optional for the convenience of the `local_fs`
test helper -- real remote storage backends provide them. It complicated
any code that actually wanted to use them for anything.
## Summary of changes
- Make these fields non-optional
- For azure/S3 it is an error if the server doesn't provide them
- For local_fs, use random strings as etags and the file's mtime for
last_modified.
## Problem
If a pageserver was offline when the storage controller started, there
was no mechanism to update the
storage controller state when the pageserver becomes active.
## Summary of changes
* Add a heartbeater module. The heartbeater must be driven by an
external loop.
* Integrate the heartbeater into the service.
- Extend the types used by the service and scheduler to keep track of a
nodes' utilisation score.
- Add a background loop to drive the heartbeater and update the state
based on the deltas it generated
- Do an initial round of heartbeats at start-up
The `tenant_id` in `TenantLocationConfigRequest` in the
`location_config` endpoint was only used in the storage
controller/attachment service, and there it was only used for assertions
and the creation part.
## Summary
- Currently we can set stripe size at tenant creation, but it doesn't
mean anything until we have multiple shards
- When onboarding an existing tenant, it will always get a default shard
stripe size, so we would like to be able to pick the actual stripe size
at the point we split.
## Why do this inline with a split?
The alternative to this change would be to have a separate endpoint on
the storage controller for setting the stripe size on a tenant, and only
permit writes to that endpoint when the tenant has only a single shard.
That would work, but be a little bit more work for a client, and not
appreciably simpler (instead of having a special argument to the split
functions, we'd have a special separate endpoint, and a requirement that
the controller must sync its config down to the pageserver before
calling the split API). Either approach would work, but this one feels a
bit more robust end-to-end: the split API is the _very last moment_ that
the stripe size is mutable, so if we aim to set it before splitting, it
makes sense to do it as part of the same operation.
## Problem
Currently we manually register nodes with the storage controller, and
use a script during deploy to register with the cloud control plane.
Rather than extend that script further, nodes should just register on
startup.
## Summary of changes
- Extend the re-attach request to include an optional
NodeRegisterRequest
- If the `register` field is set, handle it like a normal node
registration before executing the normal re-attach work.
- Update tests/neon_local that used to rely on doing an explicit
register step that could be enabled/disabled.
---------
Co-authored-by: Christian Schwarz <christian@neon.tech>
