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.
## 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
## 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>
Not a user-facing change, but can break any existing `.neon` directories
created by neon_local, as the name of the database used by the storage
controller changes.
This PR changes all the locations apart from the path of
`control_plane/attachment_service` (waiting for an opportune moment to
do that one, because it's the most conflict-ish wrt ongoing PRs like
#6676 )
## Problem
Tenants created via the storage controller have a `PlacementPolicy` that
defines their HA/secondary/detach intent. For backward compat we can
just set it to Single, for onboarding tenants using /location_conf it is
automatically set to Double(1) if there are at least two pageservers,
but for freshly created tenants we didn't have a way to specify it.
This unblocks writing tests that create HA tenants on the storage
controller and do failure injection testing.
## Summary of changes
- Add optional fields to TenantCreateRequest for specifying
PlacementPolicy. This request structure is used both on pageserver API
and storage controller API, but this method is only meaningful for the
storage controller (same as existing `shard_parameters` attribute).
- Use the value from the creation request in tenant creation, if
provided.
## Problem
- The storage controller is the source of truth for a tenant's stripe
size, but doesn't currently have a way to propagate that to compute:
we're just using the default stripe size everywhere.
Closes: https://github.com/neondatabase/neon/issues/6903
## Summary of changes
- Include stripe size in `ComputeHookNotifyRequest`
- Include stripe size in `LocationConfigResponse`
The stripe size is optional: it will only be advertised for
multi-sharded tenants. This enables the controller to defer the choice
of stripe size until we split a tenant for the first time.
Nightly has added a bunch of compiler and linter warnings. There is also
two dependencies that fail compilation on latest nightly due to using
the old `stdsimd` feature name. This PR fixes them.
## Problem
This is a precursor to adding a convenience CLI for the storage
controller.
## Summary of changes
- move controller api structs into pageserver_api::controller_api to
make them visible to other crates
- rename pageserver_api::control_api to pageserver_api::upcall_api to
match the /upcall/v1/ naming in the storage controller.
Why here rather than a totally separate crate? It's convenient to have
all the pageserver-related stuff in one place, and if we ever wanted to
move it to a different crate it's super easy to do that later.
Rebased version of #5234, part of #6768
This consists of three parts:
1. A refactoring and new contract for implementing and testing
compaction.
The logic is now in a separate crate, with no dependency on the
'pageserver' crate. It defines an interface that the real pageserver
must implement, in order to call the compaction algorithm. The interface
models things like delta and image layers, but just the parts that the
compaction algorithm needs to make decisions. That makes it easier unit
test the algorithm and experiment with different implementations.
I did not convert the current code to the new abstraction, however. When
compaction algorithm is set to "Legacy", we just use the old code. It
might be worthwhile to convert the old code to the new abstraction, so
that we can compare the behavior of the new algorithm against the old
one, using the same simulated cases. If we do that, have to be careful
that the converted code really is equivalent to the old.
This inclues only trivial changes to the main pageserver code. All the
new code is behind a tenant config option. So this should be pretty safe
to merge, even if the new implementation is buggy, as long as we don't
enable it.
2. A new compaction algorithm, implemented using the new abstraction.
The new algorithm is tiered compaction. It is inspired by the PoC at PR
#4539, although I did not use that code directly, as I needed the new
implementation to fit the new abstraction. The algorithm here is less
advanced, I did not implement partial image layers, for example. I
wanted to keep it simple on purpose, so that as we add bells and
whistles, we can see the effects using the included simulator.
One difference to #4539 and your typical LSM tree implementations is how
we keep track of the LSM tree levels. This PR doesn't have a permanent
concept of a level, tier or sorted run at all. There are just delta and
image layers. However, when compaction starts, we look at the layers
that exist, and arrange them into levels, depending on their shapes.
That is ephemeral: when the compaction finishes, we forget that
information. This allows the new algorithm to work without any extra
bookkeeping. That makes it easier to transition from the old algorithm
to new, and back again.
There is just a new tenant config option to choose the compaction
algorithm. The default is "Legacy", meaning the current algorithm in
'main'. If you set it to "Tiered", the new algorithm is used.
3. A simulator, which implements the new abstraction.
The simulator can be used to analyze write and storage amplification,
without running a test with the full pageserver. It can also draw an SVG
animation of the simulation, to visualize how layers are created and
deleted.
To run the simulator:
cargo run --bin compaction-simulator run-suite
---------
Co-authored-by: Heikki Linnakangas <heikki@neon.tech>
It's been dead-code-at-runtime for 9 months, let's remove it.
We can always re-introduce it at a later point.
Came across this while working on #6861, which will touch
`time_for_new_image_layer`. This is an opporunity to make that function
simpler.
The `refill_interval` switched from a milliseconds usize to a Duration
during a review follow-up, hence this slipped through manual testing.
Part of https://github.com/neondatabase/neon/issues/5899
PR adds a simple at most 1Hz refreshed informational API for querying
pageserver utilization. In this first phase, no actual background
calculation is performed. Instead, the worst possible score is always
returned. The returned bytes information is however correct.
Cc: #6835
Cc: #5331
The sharding service didn't have support for S3 disaster recovery.
This PR adds a new endpoint to the attachment service, which is slightly
different from the endpoint on the pageserver, in that it takes the
shard count history of the tenant as json parameters: we need to do
time travel recovery for both the shard count at the target time and the
shard count at the current moment in time, as well as the past shard
counts that either still reference.
Fixes#6604, part of https://github.com/neondatabase/cloud/issues/8233
---------
Co-authored-by: John Spray <john@neon.tech>
This PR introduces a new vectored implementation of the read path.
The search is basically a DFS if you squint at it long enough.
LayerFringe tracks the next layers to visit and acts as our stack.
Vertices are tuples of (layer, keyspace, lsn range). Continuously
pop the top of the stack (most recent layer) and do all the reads
for one layer at once.
The search maintains a fringe (`LayerFringe`) which tracks all the
layers that intersect the current keyspace being searched. Continuously
pop the top of the fringe (layer with highest LSN) and get all the data
required from the layer in one go.
Said search is done on one timeline at a time. If data is still required for
some keys, then search the ancestor timeline.
Apart from the high level layer traversal, vectored variants have been
introduced for grabbing data from each layer type. They still suffer from
read amplification issues and that will be addressed in a different PR.
You might notice that in some places we duplicate the code for the
existing read path. All of that code will be removed when we switch
the non-vectored read path to proxy into the vectored read path.
In the meantime, we'll have to contend with the extra cruft for the sake
of testing and gentle releasing.
## Problem
Timeline creation is meant to be very fast: it should only take
approximately on S3 PUT latency. When we have many shards in a tenant,
we should preserve that responsiveness.
## Summary of changes
- Issue create/delete pageserver API calls concurrently across all >0
shards
- During tenant deletion, delete shard zero last, separately, to avoid
confusing anything using GETs on the timeline.
- Return 201 instead of 200 on creations to make cloud control plane
happy
---------
Co-authored-by: Arpad Müller <arpad-m@users.noreply.github.com>
## Problem
Sharded tenants would sometimes try to write empty image layers during
compaction: this was more noticeable on larger databases.
- https://github.com/neondatabase/neon/issues/6755
**Note to reviewers: the last commit is a refactor that de-intents a
whole block, I recommend reviewing the earlier commits one by one to see
the real changes**
## Summary of changes
- Fix a case where when we drop a key during compaction, we might fail
to write out keys (this was broken when vectored get was added)
- If an image layer is empty, then do not try and write it out, but
leave `start` where it is so that if the subsequent key range meets
criteria for writing an image layer, we will extend its key range to
cover the empty area.
- Add a compaction test that configures small layers and compaction
thresholds, and asserts that we really successfully did image layer
generation. This fails before the fix.
## Problem
The ShardCount type has a magic '0' value that represents a legacy
single-sharded tenant, whose TenantShardId is formatted without a
`-0001` suffix (i.e. formatted as a traditional TenantId).
This was error-prone in code locations that wanted the actual number of
shards: they had to handle the 0 case specially.
## Summary of changes
- Make the internal value of ShardCount private, and expose `count()`
and `literal()` getters so that callers have to explicitly say whether
they want the literal value (e.g. for storing in a TenantShardId), or
the actual number of shards in the tenant.
---------
Co-authored-by: Arpad Müller <arpad-m@users.noreply.github.com>
There is O(n^2) issues due to how we store these directories (#6626), so
it's good to keep an eye on them and ensure the numbers stay low.
The new per-timeline metric `pageserver_directory_entries_count`
isn't perfect, namely we don't calculate it every time we attach
the timeline, but only if there is an actual change.
Also, it is a collective metric over multiple scalars. Lastly,
we only emit the metric if it is above a certain threshold.
However, the metric still give a feel for the general size of the timeline.
We care less for small values as the metric is mainly there to
detect and track tenants with large directory counts.
We also expose the directory counts in `TimelineInfo` so that one can
get the detailed size distribution directly via the pageserver's API.
Related: #6642 , https://github.com/neondatabase/cloud/issues/10273
## Problem
One doesn't know at tenant creation time how large the tenant will grow.
We need to be able to dynamically adjust the shard count at runtime.
This is implemented as "splitting" of shards into smaller child shards,
which cover a subset of the keyspace that the parent covered.
Refer to RFC: https://github.com/neondatabase/neon/pull/6358
Part of epic: #6278
## Summary of changes
This PR implements the happy path (does not cleanly recover from a crash
mid-split, although won't lose any data), without any optimizations
(e.g. child shards re-download their own copies of layers that the
parent shard already had on local disk)
- Add `/v1/tenant/:tenant_shard_id/shard_split` API to pageserver: this
copies the shard's index to the child shards' paths, instantiates child
`Tenant` object, and tears down parent `Tenant` object.
- Add `splitting` column to `tenant_shards` table. This is written into
an existing migration because we haven't deployed yet, so don't need to
cleanly upgrade.
- Add `/control/v1/tenant/:tenant_id/shard_split` API to
attachment_service,
- Add `test_sharding_split_smoke` test. This covers the happy path:
future PRs will add tests that exercise failure cases.
This PR adds an API to live-reconfigure the VirtualFile io engine.
It also adds a flag to `pagebench get-page-latest-lsn`, which is where I
found this functionality to be useful: it helps compare the io engines
in a benchmark without re-compiling a release build, which took ~50s on
the i3en.3xlarge where I was doing the benchmark.
Switching the IO engine is completely safe at runtime.
- log when we start walredo process
- include tenant shard id in walredo argv
- dump some basic walredo state in tenant details api
- more suitable walredo process launch histogram buckets
- avoid duplicate tracing labels in walredo launch spans
This commit adds a function to `KeySpace` which updates a key key space
by removing all overlaps with a second key space. This can involve
splitting or removing of existing ranges.
The implementation is not particularly efficient: O(M * N * log(N))
where N is the number of ranges in the current key space and M is the
number of ranges in the key space we are checking against. In practice,
this shouldn't matter much since, in the short term, the only caller of
this function will be the vectored read path and the number of key
spaces invovled will be small. This follows from the upper bound placed
on the number of keys accepted by the vectored read path.
A couple other small utility functions are added. They'll be used by the
vectored search path as well.
## Problem
See https://github.com/neondatabase/cloud/issues/8673
## Summary of changes
Download missed SLRU segments from page server
## Checklist before requesting a review
- [ ] I have performed a self-review of my code.
- [ ] If it is a core feature, I have added thorough tests.
- [ ] Do we need to implement analytics? if so did you add the relevant
metrics to the dashboard?
- [ ] If this PR requires public announcement, mark it with
/release-notes label and add several sentences in this section.
## Checklist before merging
- [ ] Do not forget to reformat commit message to not include the above
checklist
---------
Co-authored-by: Konstantin Knizhnik <knizhnik@neon.tech>
Co-authored-by: Heikki Linnakangas <heikki@neon.tech>
Depends on: https://github.com/neondatabase/neon/pull/6468
## Problem
The sharding service will be used as a "virtual pageserver" by the
control plane -- so it needs the set of pageserver APIs that the control
plane uses, and to present them under identical URLs, including prefix
(/v1).
## Summary of changes
- Add missing APIs:
- Tenant deletion
- Timeline deletion
- Node list (used in test now, later in tools)
- `/location_config` API (for migrating tenants into the sharding
service)
- Rework attachment service URLs:
- `/v1` prefix is used for pageserver-compatible APIs
- `/upcall/v1` prefix is used for APIs that are called by the pageserver
(re-attach and validate)
- `/debug/v1` prefix is used for endpoints that are for testing
- `/control/v1` prefix is used for new sharding service APIs that do not
mimic a pageserver API, such as registering and configuring nodes.
- Add test_sharding_service. The sharding service already had some
collateral coverage from its use in general tests, but this is the first
dedicated testing for it.
1. Introduce a naive `Timeline::get_vectored` implementation
The return type is intended to be flexible enough for various types of
callers. We return the pages in a map keyed by `Key` such that the
caller doesn't have to map back to the key if it needs to know it. Some
callers can ignore errors
for specific pages, so we return a separate `Result<Bytes,
PageReconstructError>` for each page and an overarching
`GetVectoredError` for API misuse. The overhead of the mapping will be
small and bounded since we enforce a maximum key count for the
operation.
2. Use the `get_vectored` API for SLRU segment reconstruction and image
layer creation.
The idea is to achieve separation between keyspace layout definition
and operating on said keyspace. I've inlined all these function since
they're small and we don't use LTO in the storage release builds
at the moment.
Closes https://github.com/neondatabase/neon/issues/6347
## Problem
To test sharding, we need something to control it. We could write python
code for doing this from the test runner, but this wouldn't be usable
with neon_local run directly, and when we want to write tests with large
number of shards/tenants, Rust is a better fit efficiently handling all
the required state.
This service enables automated tests to easily get a system with
sharding/HA without the test itself having to set this all up by hand:
existing tests can be run against sharded tenants just by setting a
shard count when creating the tenant.
## Summary of changes
Attachment service was previously a map of TenantId->TenantState, where
the principal state stored for each tenant was the generation and the
last attached pageserver. This enabled it to serve the re-attach and
validate requests that the pageserver requires.
In this PR, the scope of the service is extended substantially to do
overall management of tenants in the pageserver, including
tenant/timeline creation, live migration, evacuation of offline
pageservers etc. This is done using synchronous code to make declarative
changes to the tenant's intended state (`TenantState.policy` and
`TenantState.intent`), which are then translated into calls into the
pageserver by the `Reconciler`.
Top level summary of modules within
`control_plane/attachment_service/src`:
- `tenant_state`: structure that represents one tenant shard.
- `service`: implements the main high level such as tenant/timeline
creation, marking a node offline, etc.
- `scheduler`: for operations that need to pick a pageserver for a
tenant, construct a scheduler and call into it.
- `compute_hook`: receive notifications when a tenant shard is attached
somewhere new. Once we have locations for all the shards in a tenant,
emit an update to postgres configuration via the neon_local `LocalEnv`.
- `http`: HTTP stubs. These mostly map to methods on `Service`, but are
separated for readability and so that it'll be easier to adapt if/when
we switch to another RPC layer.
- `node`: structure that describes a pageserver node. The most important
attribute of a node is its availability: marking a node offline causes
tenant shards to reschedule away from it.
This PR is a precursor to implementing the full sharding service for
prod (#6342). What's the difference between this and a production-ready
controller for pageservers?
- JSON file persistence to be replaced with a database
- Limited observability.
- No concurrency limits. Marking a pageserver offline will try and
migrate every tenant to a new pageserver concurrently, even if there are
thousands.
- Very simple scheduler that only knows to pick the pageserver with
fewest tenants, and place secondary locations on a different pageserver
than attached locations: it does not try to place shards for the same
tenant on different pageservers. This matters little in tests, because
picking the least-used pageserver usually results in round-robin
placement.
- Scheduler state is rebuilt exhaustively for each operation that
requires a scheduler.
- Relies on neon_local mechanisms for updating postgres: in production
this would be something that flows through the real control plane.
---------
Co-authored-by: Arpad Müller <arpad-m@users.noreply.github.com>
## Problem
The `/v1/tenant` listing API only applies to attached tenants.
For an external service to implement a global reconciliation of its list
of shards vs. what's on the pageserver, we need a full view of what's in
TenantManager, including secondary tenant locations, and InProgress
locations.
Dependency of https://github.com/neondatabase/neon/pull/6251
## Summary of changes
- Add methods to Tenant and SecondaryTenant to reconstruct the
LocationConf used to create them.
- Add `GET /v1/location_config` API
## Problem
In #5980 the page service connection handler gets a simple piece of
logic for finding the right Timeline: at connection time, it picks an
arbitrary Timeline, and then when handling individual page requests it
checks if the original timeline is the correct shard, and if not looks
one up.
This is pretty slow in the case where we have to go look up the other
timeline, because we take the big tenants manager lock.
## Summary of changes
- Add a `shard_timelines` map of ShardIndex to Timeline on the page
service connection handler
- When looking up a Timeline for a particular ShardIndex, consult
`shard_timelines` to avoid hitting the TenantsManager unless we really
need to.
- Re-work the CancellationToken handling, because the handler now holds
gateguards on multiple timelines, and so must respect cancellation of
_any_ timeline it has in its cache, not just the timeline related to the
request it is currently servicing.
---------
Co-authored-by: Vlad Lazar <vlad@neon.tech>
The theme of the changes in this PR is that they're enablers for #6251
which are superficial struct/api changes.
This is a spinoff from #6251:
- Various APIs + clients thereof take TenantShardId rather than TenantId
- The creation API gets a ShardParameters member, which may be used to
configure shard count and stripe size. This enables the attachment
service to present a "virtual pageserver" creation endpoint that creates
multiple shards.
- The attachment service will use tenant size information to drive shard
splitting. Make a version of `TenantHistorySize` that is usable for
decoding these API responses.
- ComputeSpec includes a shard stripe size.
Generally useful when debugging / troubleshooting.
I found this useful when manually duplicating a tenant from a script[^1]
where I can't use `neon_fixtures.Pageserver.tenant_attach`'s automatic
integration with the neon_local's attachment_service.
[^1]: https://github.com/neondatabase/neon/pull/6349
PR #6266 broke the getpage_latest_lsn benchmark.
Before this patch, we'd fail with
```
not implemented: split up range
```
because `r.start = rel size key` and `r.end = rel size key + 1`.
The filtering of the key ranges in that loop is a bit ugly, but,
I measured:
* setup with 180k layer files (20k tenants * 9 layers).
* total physical size is 463GiB
* 5k tenants, the range filtering takes `0.6 seconds` on an
i3en.3xlarge.
That's a tiny fraction of the overall time it takes for pagebench to get
ready to send requests. So, this is good enough for now / there are
other bottlenecks that are bigger.
Before this PR, `is_rel_block_key` returns true for the blknum
`0xffffffff`,
which is a blknum that's actually never written by Postgres, but used by
Neon Pageserver to store the relsize.
Quoting @MMeent:
> PostgreSQL can't extend the relation beyond size of 0xFFFFFFFF blocks,
> so block number 0xFFFFFFFE is the last valid block number.
This PR changes the definition of the function to exclude blknum
0xffffffff.
My motivation for doing this change is to fix the `pagebench` getpage
benchmark, which uses `is_rel_block_key` to filter the keyspace for
valid pages to request from page_service.
fixes https://github.com/neondatabase/neon/issues/6210
I checked other users of the function.
The first one is `key_is_shard0`, which already had added an exemption
for 0xffffffff. So, there's no functional change with this PR.
The second one is `DatadirModification::flush`[^1]. With this PR,
`.flush()` will skip the relsize key, whereas it didn't
before. This means we will pile up all the relsize key-value pairs
`(Key,u32)`
in `DatadirModification::pending_updates` until `.commit()` is called.
The only place I can think of where that would be a problem is if we
import from a full basebackup, and don't `.commit()` regularly,
like we currently don't do in `import_basebackup_from_tar`.
It exposes us to input-controlled allocations.
However, that was already the case for the other keys that are skipped,
so, one can argue that this change is not making the situation much
worse.
[^1]: That type's `flush()` and `commit()` methods are terribly named,
but,
that's for another time
This PR adds a component-level benchmarking utility for pageserver.
Its name is `pagebench`.
The problem solved by `pagebench` is that we want to put Pageserver
under high load.
This isn't easily achieved with `pgbench` because it needs to go through
a compute, which has signficant performance overhead compared to
accessing Pageserver directly.
Further, compute has its own performance optimizations (most
importantly: caches). Instead of designing a compute-facing workload
that defeats those internal optimizations, `pagebench` simply bypasses
them by accessing pageserver directly.
Supported benchmarks:
* getpage@latest_lsn
* basebackup
* triggering logical size calculation
This code has no automated users yet.
A performance regression test for getpage@latest_lsn will be added in a
later PR.
part of https://github.com/neondatabase/neon/issues/5771
This is a precursor to:
- https://github.com/neondatabase/neon/pull/6185
While that PR contains big changes to neon_local and attachment_service,
this PR contains a few unrelated standalone changes generated while
working on that branch:
- Fix restarting a pageserver when it contains multiple shards for the
same tenant
- When using location_config api to attach a tenant, create its
timelines dir
- Update test paths where generations were previously optional to make
them always-on: this avoids tests having to spuriously assert that
attachment_service is not None in order to make the linter happy.
- Add a TenantShardId python implementation for subsequent use in test
helpers that will be made shard-aware
- Teach scrubber to read across shards when checking for layer
existence: this is a refactor to track the list of existent layers at
tenant-level rather than locally to each timeline. This is a precursor
to testing shard splitting.
Part of getpage@lsn benchmark epic:
https://github.com/neondatabase/neon/issues/5771
This allows getting the list of tenants and timelines without triggering
initial logical size calculation by requesting the timeline details API
response, which would skew our results.
Dependency (commits inline):
https://github.com/neondatabase/neon/pull/5842
## Problem
Secondary mode tenants need a manifest of what to download. Ultimately
this will be some kind of heat-scored set of layers, but as a robust
first step we will simply use the set of resident layers: secondary
tenant locations will aim to match the on-disk content of the attached
location.
## Summary of changes
- Add heatmap types representing the remote structure
- Add hooks to Tenant/Timeline for generating these heatmaps
- Create a new `HeatmapUploader` type that is external to `Tenant`, and
responsible for walking the list of attached tenants and scheduling
heatmap uploads.
Notes to reviewers:
- Putting the logic for uploads (and later, secondary mode downloads)
outside of `Tenant` is an opinionated choice, motivated by:
- Enable future smarter scheduling of operations, e.g. uploading the
stalest tenant first, rather than having all tenants compete for a fair
semaphore on a first-come-first-served basis. Similarly for downloads,
we may wish to schedule the tenants with the hottest un-downloaded
layers first.
- Enable accessing upload-related state without synchronization (it
belongs to HeatmapUploader, rather than being some Mutex<>'d part of
Tenant)
- Avoid further expanding the scope of Tenant/Timeline types, which are
already among the largest in the codebase
- You might reasonably wonder how much of the uploader code could be a
generic job manager thing. Probably some of it: but let's defer pulling
that out until we have at least two users (perhaps secondary downloads
will be the second one) to highlight which bits are really generic.
Compromises:
- Later, instead of using digests of heatmaps to decide whether anything
changed, I would prefer to avoid walking the layers in tenants that
don't have changes: tracking that will be a bit invasive, as it needs
input from both remote_timeline_client and Layer.
