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>
This PR contains the first version of a
[FoundationDB-like](https://www.youtube.com/watch?v=4fFDFbi3toc)
simulation testing for safekeeper and walproposer.
### desim
This is a core "framework" for running determenistic simulation. It
operates on threads, allowing to test syncronous code (like walproposer).
`libs/desim/src/executor.rs` contains implementation of a determenistic
thread execution. This is achieved by blocking all threads, and each
time allowing only a single thread to make an execution step. All
executor's threads are blocked using `yield_me(after_ms)` function. This
function is called when a thread wants to sleep or wait for an external
notification (like blocking on a channel until it has a ready message).
`libs/desim/src/chan.rs` contains implementation of a channel (basic
sync primitive). It has unlimited capacity and any thread can push or
read messages to/from it.
`libs/desim/src/network.rs` has a very naive implementation of a network
(only reliable TCP-like connections are supported for now), that can
have arbitrary delays for each package and failure injections for
breaking connections with some probability.
`libs/desim/src/world.rs` ties everything together, to have a concept of
virtual nodes that can have network connections between them.
### walproposer_sim
Has everything to run walproposer and safekeepers in a simulation.
`safekeeper.rs` reimplements all necesary stuff from `receive_wal.rs`,
`send_wal.rs` and `timelines_global_map.rs`.
`walproposer_api.rs` implements all walproposer callback to use
simulation library.
`simulation.rs` defines a schedule – a set of events like `restart <sk>`
or `write_wal` that should happen at time `<ts>`. It also has code to
spawn walproposer/safekeeper threads and provide config to them.
### tests
`simple_test.rs` has tests that just start walproposer and 3 safekeepers
together in a simulation, and tests that they are not crashing right
away.
`misc_test.rs` has tests checking more advanced simulation cases, like
crashing or restarting threads, testing memory deallocation, etc.
`random_test.rs` is the main test, it checks thousands of random seeds
(schedules) for correctness. It roughly corresponds to running a real
python integration test in an environment with very unstable network and
cpu, but in a determenistic way (each seed results in the same execution
log) and much much faster.
Closes#547
---------
Co-authored-by: Arseny Sher <sher-ars@yandex.ru>
## Problem
usernames and passwords can be URL 'percent' encoded in the connection
string URL provided by serverless driver.
## Summary of changes
Decode the parameters when getting conn info
## Problem
Running some memory profiling with high concurrent request rate shows
seemingly some memory fragmentation.
## Summary of changes
Eventually, we will want to separate global memory (caches) from local
memory (per connection handshake and per passthrough).
Using a string interner for project info cache helps reduce some of the
fragmentation of the global cache by having a single heap dedicated to
project strings, and not scattering them throughout all a requests.
At the same time, the interned key is 4 bytes vs the 24 bytes that
`SmolStr` offers.
Important: we should only store verified strings in the interner because
there's no way to remove them afterwards. Good for caching responses
from console.
## Problem
Passing secrets in via CLI/environment is awkward when using helm for
deployment, and not ideal for security (secrets may show up in ps,
/proc).
We can bypass these issues by simply connecting directly to the AWS
Secrets Manager service at runtime.
## Summary of changes
- Add dependency on aws-sdk-secretsmanager
- Update other aws dependencies to latest, to match transitive
dependency versions
- Add `Secrets` type in attachment service, using AWS SDK to load if
secrets are not provided on the command line.
The rust stdlib uses the efficient `posix_spawn` by default.
However, before this PR, pageserver used `pre_exec()` in our
`close_fds()` ext trait.
This PR moves the work that `close_fds()` did to the walredo C code.
I verified manually using `gdb` that we're now forking out the walredo
process using `posix_spawn`.
refs https://github.com/neondatabase/neon/issues/6565
## Problem
Measuring cardinality using logs is expensive and slow.
## Summary of changes
Implement a pre-aggregated HyperLogLog-based cardinality estimate.
HyperLogLog estimates the cardinality of a set by using the probability
that the uniform hash of a value will have a run of n 0s at the end is
`1/2^n`, therefore, having observed a run of `n` 0s suggests we have
measured `2^n` distinct values. By using multiple shards, we can use the
harmonic mean to get a more accurate estimate.
We record this into a Prometheus time-series. HyperLogLog counts can be
merged by taking the `max` of each shard. We can apply a `max_over_time`
in order to find the estimate of cardinality of distinct values over
time
## 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
Current cache doesn't support any updates from the cplane.
## Summary of changes
* Added redis notifier listner.
* Added cache which can be invalidated with the notifier. If the
notifier is not available, it's just a normal ttl cache.
* Updated cplane api.
The motivation behind this organization of the data is the following:
* In the Neon data model there are projects. Projects could have
multiple branches and each branch could have more than one endpoint.
* Also there is one special `main` branch.
* Password reset works per branch.
* Allowed IPs are the same for every branch in the project (except,
maybe, the main one).
* The main branch can be changed to the other branch.
* The endpoint can be moved between branches.
Every event described above requires some special processing on the
porxy (or cplane) side.
The idea of invalidating for the project is that whenever one of the
events above is happening with the project, proxy can invalidate all
entries for the entire project.
This approach also requires some additional API change (returning
project_id inside the auth info).
## Summary of changes
### RequestMonitoring
We want to add an event stream with information on each request for
easier analysis than what we can do with diagnostic logs alone
(https://github.com/neondatabase/cloud/issues/8807). This
RequestMonitoring will keep a record of the final state of a request. On
drop it will be pushed into a queue to be uploaded.
Because this context is a bag of data, I don't want this information to
impact logic of request handling. I personally think that weakly typed
data (such as all these options) makes for spaghetti code. I will
however allow for this data to impact rate-limiting and blocking of
requests, as this does not _really_ change how a request is handled.
### Parquet
Each `RequestMonitoring` is flushed into a channel where it is converted
into `RequestData`, which is accumulated into parquet files. Each file
will have a certain number of rows per row group, and several row groups
will eventually fill up the file, which we then upload to S3.
We will also upload smaller files if they take too long to construct.
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
Part of getpage@lsn benchmark epic:
https://github.com/neondatabase/neon/issues/5771
This PR moves the control plane's spread-all-over-the-place client for
the pageserver management API into a separate module within the
pageserver crate.
I need that client to be async in my benchmarking work, so, this PR
switches to the async version of `reqwest`.
That is also the right direction generally IMO.
The switch to async in turn mandated converting most of the
`control_plane/` code to async.
Note that some of the client methods should be taking `TenantShardId`
instead of `TenantId`, but, none of the callers seem to be
sharding-aware.
Leaving that for another time:
https://github.com/neondatabase/neon/issues/6154
## Problem
The cancellation code was confusing and error prone (as seen before in
our memory leaks).
## Summary of changes
* Use the new `TaskTracker` primitve instead of JoinSet to gracefully
wait for tasks to shutdown.
* Updated libs/utils/completion to use `TaskTracker`
* Remove `tokio::select` in favour of `futures::future::select` in a
specialised `run_until_cancelled()` helper function
## Problem
no problem
## Summary of changes
replaces boxstr with arcstr as it's cheaper to clone. mild perf
improvement.
probably should look into other smallstring optimsations tbh, they will
likely be even better. The longest endpoint name I was able to construct
is something like `ep-weathered-wildflower-12345678` which is 32 bytes.
Most string optimisations top out at 23 bytes
## Problem
Per-project IP allowlist:
https://github.com/neondatabase/cloud/issues/8116
## Summary of changes
Implemented IP filtering on the proxy side.
To retrieve ip allowlist for all scenarios, added `get_auth_info` call
to the control plane for:
* sql-over-http
* password_hack
* cleartext_hack
Added cache with ttl for sql-over-http path
This might slow down a bit, consider using redis in the future.
---------
Co-authored-by: Conrad Ludgate <conrad@neon.tech>
Remove handcrafted TenantConf deserialization code. Use
`serde_path_to_error` to include the field which failed parsing. Leaves
the duplicated TenantConf in pageserver and models, does not touch
PageserverConf handcrafted deserialization.
Error change:
- before change: "configure option `checkpoint_distance` cannot be
negative"
- after change: "`checkpoint_distance`: invalid value: integer `-1`,
expected u64"
Fixes: #5300
Cc: #3682
---------
Signed-off-by: Rahul Modpur <rmodpur2@gmail.com>
Co-authored-by: Shany Pozin <shany@neon.tech>
Co-authored-by: Joonas Koivunen <joonas@neon.tech>
## Problem
See #2592
## Summary of changes
Compresses the results of initdb into a .tar.zst file and uploads them
to S3, to enable usage in recovery from lsn.
Generations should not be involved I think because we do this only once
at the very beginning of a timeline.
---------
Co-authored-by: Joonas Koivunen <joonas@neon.tech>
This way, `cargo update -p tokio-postgres` just works. The `Cargo.toml`
communicates more clearly that we're referring to the `main` branch. And
the git revision is still pinned in `Cargo.lock`.
## Problem
A user can perform many database connections at the same instant of time
- these will all cache miss and materialise as requests to the control
plane. #5705
## Summary of changes
I am using a `DashMap` (a sharded `RwLock<HashMap>`) of endpoints ->
semaphores to apply a limiter. If the limiter is enabled (permits > 0),
the semaphore will be retrieved per endpoint and a permit will be
awaited before continuing to call the wake_compute endpoint.
### Important details
This dashmap would grow uncontrollably without maintenance. It's not a
cache so I don't think an LRU-based reclamation makes sense. Instead,
I've made use of the sharding functionality of DashMap to lock a single
shard and clear out unused semaphores periodically.
I ran a test in release, using 128 tokio tasks among 12 threads each
pushing 1000 entries into the map per second, clearing a shard every 2
seconds (64 second epoch with 32 shards). The endpoint names were
sampled from a gamma distribution to make sure some overlap would occur,
and each permit was held for 1ms. The histogram for time to clear each
shard settled between 256-512us without any variance in my testing.
Holding a lock for under a millisecond for 1 of the shards does not
concern me as blocking
## Problem
Currently, we aren't doing any explicit slowdown in response to 429
responses. Recently, as we hit remote storage a bit harder (pageserver
does more ListObjectsv2 requests than it used to since #5580 ), we're
seeing storms of 429 responses that may be the result of not just doing
too may requests, but continuing to do those extra requests without
backing off any more than our usual backoff::exponential.
## Summary of changes
Switch from AWS's "Standard" retry policy to "Adaptive" -- docs describe
this as experimental but it has been around for a long time. The main
difference between Standard and Adaptive is that Adaptive rate-limits
the client in response to feedback from the server, which is meant to
avoid scenarios where the client would otherwise repeatedly hit
throttling responses.
## Problem
For quickly rotating JWT secrets, we want to be able to reload the JWT
public key file in the pageserver, and also support multiple JWT keys.
See #4897.
## Summary of changes
* Allow directories for the `auth_validation_public_key_path` config
param instead of just files. for the safekeepers, all of their config options
also support multiple JWT keys.
* For the pageservers, make the JWT public keys easily globally swappable
by using the `arc-swap` crate.
* Add an endpoint to the pageserver, triggered by a POST to
`/v1/reload_auth_validation_keys`, that reloads the JWT public keys from
the pre-configured path (for security reasons, you cannot upload any
keys yourself).
Fixes#4897
---------
Co-authored-by: Heikki Linnakangas <heikki@neon.tech>
Co-authored-by: Joonas Koivunen <joonas@neon.tech>
Improve the serde impl for several types (`Lsn`, `TenantId`,
`TimelineId`) by making them sensitive to
`Serializer::is_human_readadable` (true for json, false for bincode).
Fixes#3511 by:
- Implement the custom serde for `Lsn`
- Implement the custom serde for `Id`
- Add the helper module `serde_as_u64` in `libs/utils/src/lsn.rs`
- Remove the unnecessary attr `#[serde_as(as = "DisplayFromStr")]` in
all possible structs
Additionally some safekeeper types gained serde tests.
---------
Co-authored-by: Joonas Koivunen <joonas@neon.tech>
Create Rust bindings for C functions from walproposer. This allows to
write better tests with real walproposer code without spawning multiple
processes and starting up the whole environment.
`make walproposer-lib` stage was added to build static libraries
`libwalproposer.a`, `libpgport.a`, `libpgcommon.a`. These libraries can
be statically linked to any executable to call walproposer functions.
`libs/walproposer/src/walproposer.rs` contains
`test_simple_sync_safekeepers` to test that walproposer can be called
from Rust to emulate sync_safekeepers logic. It can also be used as a
usage example.
## Problem
Transactions break connections in the pool
fixes#4698
## Summary of changes
* Pool `Client`s are smart object that return themselves to the pool
* Pool `Client`s can be 'discard'ed
* Pool `Client`s are discarded when certain errors are encountered.
* Pool `Client`s are discarded when ReadyForQuery returns a non-idle
state.
Adds prototype-level support for [Azure blob storage](https://azure.microsoft.com/en-us/products/storage/blobs). Some corners were cut, see the TODOs and the followup issue #5567 for details.
Steps to try it out:
* Create a storage account with block blobs (this is a per-storage
account setting).
* Create a container inside that storage account.
* Set the appropriate env vars: `AZURE_STORAGE_ACCOUNT,
AZURE_STORAGE_ACCESS_KEY, REMOTE_STORAGE_AZURE_CONTAINER,
REMOTE_STORAGE_AZURE_REGION`
* Set the env var `ENABLE_REAL_AZURE_REMOTE_STORAGE=y` and run `cargo
test -p remote_storage azure`
Fixes #5562
Fixes#4689 by replacing all of `std::Path` , `std::PathBuf` with
`camino::Utf8Path`, `camino::Utf8PathBuf` in
- pageserver
- safekeeper
- control_plane
- libs/remote_storage
Co-authored-by: Joonas Koivunen <joonas@neon.tech>
## Problem
We need to count metrics always when a connection is open. Not only when
the transfer is 0.
We also need to count bytes usage for HTTP.
## Summary of changes
New structure for usage metrics. A `DashMap<Ids, Arc<Counters>>`.
If the arc has 1 owner (the map) then I can conclude that no connections
are open.
If the counters has "open_connections" non zero, then I can conclude a
new connection was opened in the last interval and should be reported
on.
Also, keep count of how many bytes processed for HTTP and report it
here.
Prepare to upgrade rust version to latest stable.
- `rustfmt` has learned to format `let irrefutable = $expr else { ...
};` blocks
- There's a new warning about virtual (workspace) crate resolver, picked
the latest resolver as I suspect everyone would expect it to be the
latest; should not matter anyways
- Some new clippies, which seem alright
## Problem
The S3 scrubber currently lives at
https://github.com/neondatabase/s3-scrubber
We don't have tests that use it, and it has copies of some data
structures that can get stale.
## Summary of changes
- Import the s3-scrubber as `s3_scrubber/
- Replace copied_definitions/ in the scrubber with direct access to the
`utils` and `pageserver` crates
- Modify visibility of a few definitions in `pageserver` to allow the
scrubber to use them
- Update scrubber code for recent changes to `IndexPart`
- Update `KNOWN_VERSIONS` for IndexPart and move the definition into
index.rs so that it is easier to keep up to date
As a future refinement, it would be good to pull the remote persistence
types (like IndexPart) out of `pageserver` into a separate library so
that the scrubber doesn't have to link against the whole pageserver, and
so that it's clearer which types need to be public.
Co-authored-by: Kirill Bulatov <kirill@neon.tech>
Co-authored-by: Dmitry Rodionov <dmitry@neon.tech>
Co-authored-by: Arpad Müller <arpad-m@users.noreply.github.com>
