Service targeted for storing and retrieving LFC prewarm data.
Can be used for proxying S3 access for Postgres extensions like
pg_mooncake as well.
Requests must include a Bearer JWT token.
Token is validated using a pemfile (should be passed in infra/).
Note: app is not tolerant to extra trailing slashes, see app.rs
`delete_prefix` test for comments.
Resolves: https://github.com/neondatabase/cloud/issues/26342
Unrelated changes: gate a `rename_noreplace` feature and disable it in
`remote_storage` so as `object_storage` can be built with musl
We want to export performance traces from the pageserver in OTEL format.
End goal is to see them in Grafana.
To this end, there are two changes here:
1. Update the `tracing-utils` crate to allow for explicitly specifying
the export configuration. Pageserver configuration is loaded from a file
on start-up. This allows us to use the same flow for export configs
there.
2. Update the `utils::logging::init` common entry point to set up OTEL
tracing infrastructure if requested. Note that an entirely different
tracing subscriber is used. This is to avoid interference with the
existing tracing set-up. For now, no service uses this functionality.
PR to plug this into the pageserver is
[here](https://github.com/neondatabase/neon/pull/11140).
Related https://github.com/neondatabase/neon/issues/9873
## Problem
The code to generate symbolized pprof heap profiles and flamegraph SVGs
has been upstreamed to the `jemalloc_pprof` crate:
* https://github.com/polarsignals/rust-jemalloc-pprof/pull/22
* https://github.com/polarsignals/rust-jemalloc-pprof/pull/23
## Summary of changes
Use `jemalloc_pprof` to generate symbolized pprof heap profiles and
flamegraph SVGs.
This reintroduces a bunch of internal jemalloc stack frames that we'd
previously strip, e.g. each stack now always ends with
`prof_backtrace_impl` (where jemalloc takes a stack trace for heap
profiling), but that seems ok.
## Problem
We don't have good observability for "stuck" getpage requests.
Resolves https://github.com/neondatabase/cloud/issues/23808.
## Summary of changes
Log a periodic warning (every 30 seconds) if GetPage request execution
is slow to complete, to aid in debugging stuck GetPage requests.
This does not cover response flushing (we have separate logging for
that), nor reading the request from the socket and batching it (expected
to be insignificant and not straightforward to handle with the current
protocol).
This costs 95 nanoseconds on the happy path when awaiting a
`tokio::task::yield_now()`:
```
warn_slow/enabled=false time: [45.716 ns 46.116 ns 46.687 ns]
warn_slow/enabled=true time: [141.53 ns 141.83 ns 142.18 ns]
```
# Summary
In
- https://github.com/neondatabase/neon/pull/10813
we added slow flush logging but it didn't log the TCP send & recv queue
length.
This PR adds that data to the log message.
I believe the implementation to be safe & correct right now, but it's
brittle and thus this PR should be reverted or improved upon once the
investigation is over.
Refs:
- stacked atop https://github.com/neondatabase/neon/pull/10813
- context:
https://neondb.slack.com/archives/C08DE6Q9C3B/p1739464533762049?thread_ts=1739462628.361019&cid=C08DE6Q9C3B
- improves https://github.com/neondatabase/neon/issues/10668
- part of https://github.com/neondatabase/cloud/issues/23515
# How It Works
The trouble is two-fold:
1. getting to the raw socket file descriptor through the many Rust types
that wrap it and
2. integrating with the `measure()` function
Rust wraps it in types to model file descriptor lifetimes and ownership,
and usually one can get access using `as_raw_fd()`.
However, we `split()` the stream and the resulting
[`tokio::io::WriteHalf`](https://docs.rs/tokio/latest/tokio/io/struct.WriteHalf.html)
.
Check the PR commit history for my attempts to do it.
My solution is to get the socket fd before we wrap it in our protocol
types, and to store that fd in the new `PostgresBackend::socket_fd`
field.
I believe it's safe because the lifetime of `PostgresBackend::socket_fd`
value == the lifetime of the `TcpStream` that wrap and store in
`PostgresBackend::framed`.
Specifically, the only place that close()s the socket is the `impl Drop
for TcpStream`.
I think the protocol stack calls `TcpStream::shutdown()`, but, that
doesn't `close()` the file descriptor underneath.
Regarding integration with the `measure()` function, the trouble is that
`flush_fut` is currently a generic `Future` type. So, we just pass in
the `socket_fd` as a separate argument.
A clean implementation would convert the `pgb_writer.flush()` to a named
future that provides an accessor for the socket fd while not being
polled.
I tried (see PR history), but failed to break through the `WriteHalf`.
# Testing
Tested locally by running
```
./target/debug/pagebench get-page-latest-lsn --num-clients=1000 --queue-depth=1000
```
in one terminal, waiting a bit, then
```
pkill -STOP pagebench
```
then wait for slow logs to show up in `pageserver.log`.
Pick one of the slow log message's port pairs, e.g., `127.0.0.1:39500`,
and then checking sockstat output
```
ss -ntp | grep '127.0.0.1:39500'
```
to ensure that send & recv queue size match those in the log message.
Avoids compiling the crate and its dependencies into binaries that don't
need them. Shrinks the compute_ctl binary from about 31MB to 28MB in the
release-line-debug-size-lto profile.
## Problem
Unlike CPU profiles, the `/profile/heap` endpoint can't automatically
generate SVG flamegraphs. This requires the user to install and use
`pprof` tooling, which is unnecessary and annoying.
Resolves#10203.
## Summary of changes
Add `format=svg` for the `/profile/heap` route, and generate an SVG
flamegraph using the `inferno` crate, similarly to what `pprof-rs`
already does for CPU profiles.
## Problem
Jemalloc heap profiles aren't symbolized. This is inconvenient, and
doesn't work with Grafana Cloud Profiles.
Resolves#9964.
## Summary of changes
Symbolize the heap profiles in-process, and strip unnecessary cruft.
This uses about 100 MB additional memory to cache the DWARF information,
but I believe this is already the case with CPU profiles, which use the
same library for symbolization. With cached DWARF information, the
symbolization CPU overhead is negligible.
Example profiles:
*
[pageserver.pb.gz](https://github.com/user-attachments/files/18141395/pageserver.pb.gz)
*
[safekeeper.pb.gz](https://github.com/user-attachments/files/18141396/safekeeper.pb.gz)
## Problem
We don't have good observability for memory usage. This would be useful
e.g. to debug OOM incidents or optimize performance or resource usage.
We would also like to use continuous profiling with e.g. [Grafana Cloud
Profiles](https://grafana.com/products/cloud/profiles-for-continuous-profiling/)
(see https://github.com/neondatabase/cloud/issues/14888).
This PR is intended as a proof of concept, to try it out in staging and
drive further discussions about profiling more broadly.
Touches https://github.com/neondatabase/neon/issues/9534.
Touches https://github.com/neondatabase/cloud/issues/14888.
Depends on #9779.
Depends on #9780.
## Summary of changes
Adds a HTTP route `/profile/heap` that takes a heap profile and returns
it. Query parameters:
* `format`: output format (`jemalloc` or `pprof`; default `pprof`).
Unlike CPU profiles (see #9764), heap profiles are not symbolized and
require the original binary to translate addresses to function names. To
make this work with Grafana, we'll probably have to symbolize the
process server-side -- this is left as future work, as is other output
formats like SVG.
Heap profiles don't work on macOS due to limitations in jemalloc.
# Problem
The timeout-based batching adds latency to unbatchable workloads.
We can choose a short batching timeout (e.g. 10us) but that requires
high-resolution timers, which tokio doesn't have.
I thoroughly explored options to use OS timers (see
[this](https://github.com/neondatabase/neon/pull/9822) abandoned PR).
In short, it's not an attractive option because any timer implementation
adds non-trivial overheads.
# Solution
The insight is that, in the steady state of a batchable workload, the
time we spend in `get_vectored` will be hundreds of microseconds anyway.
If we prepare the next batch concurrently to `get_vectored`, we will
have a sizeable batch ready once `get_vectored` of the current batch is
done and do not need an explicit timeout.
This can be reasonably described as **pipelining of the protocol
handler**.
# Implementation
We model the sub-protocol handler for pagestream requests
(`handle_pagrequests`) as two futures that form a pipeline:
2. Batching: read requests from the connection and fill the current
batch
3. Execution: `take` the current batch, execute it using `get_vectored`,
and send the response.
The Reading and Batching stage are connected through a new type of
channel called `spsc_fold`.
See the long comment in the `handle_pagerequests_pipelined` for details.
# Changes
- Refactor `handle_pagerequests`
- separate functions for
- reading one protocol message; produces a `BatchedFeMessage` with just
one page request in it
- batching; tried to merge an incoming `BatchedFeMessage` into an
existing `BatchedFeMessage`; returns `None` on success and returns back
the incoming message in case merging isn't possible
- execution of a batched message
- unify the timeline handle acquisition & request span construction; it
now happen in the function that reads the protocol message
- Implement serial and pipelined model
- serial: what we had before any of the batching changes
- read one protocol message
- execute protocol messages
- pipelined: the design described above
- optionality for execution of the pipeline: either via concurrent
futures vs tokio tasks
- Pageserver config
- remove batching timeout field
- add ability to configure pipelining mode
- add ability to limit max batch size for pipelined configurations
(required for the rollout, cf
https://github.com/neondatabase/cloud/issues/20620 )
- ability to configure execution mode
- Tests
- remove `batch_timeout` parametrization
- rename `test_getpage_merge_smoke` to `test_throughput`
- add parametrization to test different max batch sizes and execution
moes
- rename `test_timer_precision` to `test_latency`
- rename the test case file to `test_page_service_batching.py`
- better descriptions of what the tests actually do
## On the holding The `TimelineHandle` in the pending batch
While batching, we hold the `TimelineHandle` in the pending batch.
Therefore, the timeline will not finish shutting down while we're
batching.
This is not a problem in practice because the concurrently ongoing
`get_vectored` call will fail quickly with an error indicating that the
timeline is shutting down.
This results in the Execution stage returning a `QueryError::Shutdown`,
which causes the pipeline / entire page service connection to shut down.
This drops all references to the
`Arc<Mutex<Option<Box<BatchedFeMessage>>>>` object, thereby dropping the
contained `TimelineHandle`s.
- => fixes https://github.com/neondatabase/neon/issues/9850
# Performance
Local run of the benchmarks, results in [this empty
commit](1cf5b1463f)
in the PR branch.
Key take-aways:
* `concurrent-futures` and `tasks` deliver identical `batching_factor`
* tail latency impact unknown, cf
https://github.com/neondatabase/neon/issues/9837
* `concurrent-futures` has higher throughput than `tasks` in all
workloads (=lower `time` metric)
* In unbatchable workloads, `concurrent-futures` has 5% higher
`CPU-per-throughput` than that of `tasks`, and 15% higher than that of
`serial`.
* In batchable-32 workload, `concurrent-futures` has 8% lower
`CPU-per-throughput` than that of `tasks` (comparison to tput of
`serial` is irrelevant)
* in unbatchable workloads, mean and tail latencies of
`concurrent-futures` is practically identical to `serial`, whereas
`tasks` adds 20-30us of overhead
Overall, `concurrent-futures` seems like a slightly more attractive
choice.
# Rollout
This change is disabled-by-default.
Rollout plan:
- https://github.com/neondatabase/cloud/issues/20620
# Refs
- epic: https://github.com/neondatabase/neon/issues/9376
- this sub-task: https://github.com/neondatabase/neon/issues/9377
- the abandoned attempt to improve batching timeout resolution:
https://github.com/neondatabase/neon/pull/9820
- closes https://github.com/neondatabase/neon/issues/9850
- fixes https://github.com/neondatabase/neon/issues/9835
## Problem
For any given tenant shard, pageservers receive all of the tenant's WAL
from the safekeeper.
This soft-blocks us from using larger shard counts due to bandwidth
concerns and CPU overhead of filtering
out the records.
## Summary of changes
This PR lifts the decoding and interpretation of WAL from the pageserver
into the safekeeper.
A customised PG replication protocol is used where instead of sending
raw WAL, the safekeeper sends
filtered, interpreted records. The receiver drives the protocol
selection, so, on the pageserver side, usage
of the new protocol is gated by a new pageserver config:
`wal_receiver_protocol`.
More granularly the changes are:
1. Optionally inject the protocol and shard identity into the arguments
used for starting replication
2. On the safekeeper side, implement a new wal sending primitive which
decodes and interprets records
before sending them over
3. On the pageserver side, implement the ingestion of this new
replication message type. It's very similar
to what we already have for raw wal (minus decoding and interpreting).
## Notes
* This PR currently uses my [branch of
rust-postgres](https://github.com/neondatabase/rust-postgres/tree/vlad/interpreted-wal-record-replication-support)
which includes the deserialization logic for the new replication message
type. PR for that is open
[here](https://github.com/neondatabase/rust-postgres/pull/32).
* This PR contains changes for both pageservers and safekeepers. It's
safe to merge because the new protocol is disabled by default on the
pageserver side. We can gradually start enabling it in subsequent
releases.
* CI tests are running on https://github.com/neondatabase/neon/pull/9747
## Links
Related: https://github.com/neondatabase/neon/issues/9336
Epic: https://github.com/neondatabase/neon/issues/9329
## Problem
We don't have a convenient way to gather CPU profiles from a running
binary, e.g. during production incidents or end-to-end benchmarks, nor
during microbenchmarks (particularly on macOS).
We would also like to have continuous profiling in production, likely
using [Grafana Cloud
Profiles](https://grafana.com/products/cloud/profiles-for-continuous-profiling/).
We may choose to use either eBPF profiles or pprof profiles for this
(pending testing and discussion with SREs), but pprof profiles appear
useful regardless for the reasons listed above. See
https://github.com/neondatabase/cloud/issues/14888.
This PR is intended as a proof of concept, to try it out in staging and
drive further discussions about profiling more broadly.
Touches #9534.
Touches https://github.com/neondatabase/cloud/issues/14888.
## Summary of changes
Adds a HTTP route `/profile/cpu` that takes a CPU profile and returns
it. Defaults to a 5-second pprof Protobuf profile for use with e.g.
`pprof` or Grafana Alloy, but can also emit an SVG flamegraph. Query
parameters:
* `format`: output format (`pprof` or `svg`)
* `frequency`: sampling frequency in microseconds (default 100)
* `seconds`: number of seconds to profile (default 5)
Also integrates pprof profiles into Criterion benchmarks, such that
flamegraph reports can be taken with `cargo bench ... --profile-duration
<seconds>`. Output under `target/criterion/*/profile/flamegraph.svg`.
Example profiles:
* pprof profile (use [`pprof`](https://github.com/google/pprof)):
[profile.pb.gz](https://github.com/user-attachments/files/17756788/profile.pb.gz)
* Web interface: `pprof -http :6060 profile.pb.gz`
* Interactive flamegraph:
[profile.svg.gz](https://github.com/user-attachments/files/17756782/profile.svg.gz)
Follow-up of #9234 to give hyper 1.0 the version-free name, and the
legacy version of hyper the one with the version number inside. As we
move away from hyper 0.14, we can remove the `hyper0` name piece by
piece.
Part of #9255
Removes additional async_trait usages from safekeeper and neon_local.
Also removes now redundant dependencies of the `async_trait` crate.
cc earlier work: #6305, #6464, #7303, #7342, #7212, #8296
In proxy I switched to a leaky-bucket impl using the GCRA algorithm. I
figured I could share the code with pageserver and remove the
leaky_bucket crate dependency with some very basic tokio timers and
queues for fairness.
The underlying algorithm should be fairly clear how it works from the
comments I have left in the code.
---
In benchmarking pageserver, @problame found that the new implementation
fixes a getpage throughput discontinuity in pageserver under the
`pagebench get-page-latest-lsn` benchmark with the clickbench dataset
(`test_perf_olap.py`).
The discontinuity is that for any of `--num-clients={2,3,4}`, getpage
throughput remains 10k.
With `--num-clients=5` and greater, getpage throughput then jumps to the
configured 20k rate limit.
With the changes in this PR, the discontinuity is gone, and we scale
throughput linearly to `--num-clients` until the configured rate limit.
More context in
https://github.com/neondatabase/cloud/issues/16886#issuecomment-2315257641.
closes https://github.com/neondatabase/cloud/issues/16886
---------
Co-authored-by: Joonas Koivunen <joonas@neon.tech>
Co-authored-by: Christian Schwarz <christian@neon.tech>
This removes workspace hack from all libs, not from any binaries. This
does not change the behaviour of the hack.
Running
```
cargo clean
cargo build --release --bin proxy
```
Before this change took 5m16s. After this change took 3m3s. This is
because this allows the build to be parallelisable much more.
## Problem
LayerAccessStats contains a lot of detail that we don't use: short
histories of most recent accesses, specifics on what kind of task
accessed a layer, etc. This is all stored inside a Mutex, which is
locked every time something accesses a layer.
## Summary of changes
- Store timestamps at a very low resolution (to the nearest second),
sufficient for use on the timescales of eviction.
- Pack access time and last residence change time into a single u64
- Use the high bits of the u64 for other flags, including the new layer
visibility concept.
- Simplify the external-facing model for access stats to just include
what we now track.
Note that the `HistoryBufferWithDropCounter` is removed here because it
is no longer used. I do not dislike this type, we just happen not to use
it for anything else at present.
Co-authored-by: Christian Schwarz <christian@neon.tech>
Before this PR, `RemoteStorageConfig::from_toml` would support
deserializing an
empty `{}` TOML inline table to a `None`, otherwise try `Some()`.
We can instead let
* in proxy: let clap derive handle the Option
* in PS & SK: assume that if the field is specified, it must be a valid
RemtoeStorageConfig
(This PR started with a much simpler goal of factoring out the
`deserialize_item` function because I need that in another PR).
## 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.
Before any json parsing from the http api only returned errors were per
field errors. Now they are done using `serde_path_to_error`, which at
least helped greatly with the `disk_usage_eviction_run` used for
testing. I don't think this can conflict with anything added in #5310.
## 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>
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
Currently, anything that uses backoff::retry will delay the join of its
task by however long its backoff sleep is, multiplied by its max
retries.
Whenever we call a function that sleeps, we should be passing in a
CancellationToken.
## Summary of changes
- Add a `Cancel` type to backoff::retry that wraps a CancellationToken
and an error `Fn` to generate an error if the cancellation token fires.
- In call sites that already run in a `task_mgr` task, use
`shutdown_token()` to provide the token. In other locations, use a dead
`CancellationToken` to satisfy the interface, and leave a TODO to fix it
up when we broaden the use of explicit cancellation tokens.
## Problem
Binaries created from PRs (both in docker images and for tests) have
wrong git-env versions, they point to phantom merge commits.
## Summary of changes
- Prefer GIT_VERSION env variable even if git information was accessible
- Use `${{ github.event.pull_request.head.sha || github.sha }}` instead
of `${{ github.sha }}` for `GIT_VERSION` in workflows
So the builds will still happen from this phantom commit, but we will
report the PR commit.
---------
Co-authored-by: Joonas Koivunen <joonas@neon.tech>
Allure does not support ansi colored logs, yet `compute_ctl` has them.
Upgrade criterion to get rid of atty dependency, disable ansi colors,
remove atty dependency and disable ansi feature of tracing-subscriber.
This is a heavy-handed approach. I am not aware of a workflow where
you'd want to connect a terminal directly to for example `compute_ctl`,
usually you find the logs in a file. If someone had been using colors,
they will now need to:
- turn the `tracing-subscriber.default-features` to `true`
- edit their wanted project to have colors
I decided to explicitly disable ansi colors in case we would have in
future a dependency accidentally enabling the feature on
`tracing-subscriber`, which would be quite surprising but not
unimagineable.
By getting rid of `atty` from dependencies we get rid of
<https://github.com/advisories/GHSA-g98v-hv3f-hcfr>.
- Remove repeated tenant & timeline from span
- Demote logging of the path to debug level
- Log completion at info level, in the same function where we log errors
- distinguish between layer file download success & on-demand download
succeeding as a whole in the log message wording
- Assert that the span contains a tenant id and a timeline id
fixes https://github.com/neondatabase/neon/issues/3945
Before:
```
INFO compaction_loop{tenant_id=$TENANT_ID}:compact_timeline{timeline=$TIMELINE_ID}:download_remote_layer{tenant_id=$TENANT_ID timeline_id=$TIMELINE_ID layer=000000000000000000000000000000000000-FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF__00000000020C8A71-00000000020CAF91}: download complete: /storage/pageserver/data/tenants/$TENANT_ID/timelines/$TIMELINE_ID/000000000000000000000000000000000000-FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF__00000000020C8A71-00000000020CAF91
INFO compaction_loop{tenant_id=$TENANT_ID}:compact_timeline{timeline=$TIMELINE_ID}:download_remote_layer{tenant_id=$TENANT_ID timeline_id=$TIMELINE_ID layer=000000000000000000000000000000000000-FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF__00000000020C8A71-00000000020CAF91}: Rebuilt layer map. Did 9 insertions to process a batch of 1 updates.
```
After:
```
INFO compaction_loop{tenant_id=$TENANT_ID}:compact_timeline{timeline=$TIMELINE_ID}:download_remote_layer{layer=000000000000000000000000000000000000-FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF__00000000020C8A71-00000000020CAF91}: layer file download finished
INFO compaction_loop{tenant_id=$TENANT_ID}:compact_timeline{timeline=$TIMELINE_ID}:download_remote_layer{layer=000000000000000000000000000000000000-FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF__00000000020C8A71-00000000020CAF91}: Rebuilt layer map. Did 9 insertions to process a batch of 1 updates.
INFO compaction_loop{tenant_id=$TENANT_ID}:compact_timeline{timeline=$TIMELINE_ID}:download_remote_layer{layer=000000000000000000000000000000000000-FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF__00000000020C8A71-00000000020CAF91}: on-demand download successful
```
See https://github.com/neondatabase/neon/pull/3991
Brings the changes back with the right way to use new `toml_edit` to
deserialize values and a unit test for this.
All non-trivial updates extracted into separate commits, also `carho hakari` data and its manifest format were updated.
3 sets of crates remain unupdated:
* `base64` — touches proxy in a lot of places and changed its api (by 0.21 version) quite strongly since our version (0.13).
* `opentelemetry` and `opentelemetry-*` crates
```
error[E0308]: mismatched types
--> libs/tracing-utils/src/http.rs:65:21
|
65 | span.set_parent(parent_ctx);
| ---------- ^^^^^^^^^^ expected struct `opentelemetry_api::context::Context`, found struct `opentelemetry::Context`
| |
| arguments to this method are incorrect
|
= note: struct `opentelemetry::Context` and struct `opentelemetry_api::context::Context` have similar names, but are actually distinct types
note: struct `opentelemetry::Context` is defined in crate `opentelemetry_api`
--> /Users/someonetoignore/.cargo/registry/src/github.com-1ecc6299db9ec823/opentelemetry_api-0.19.0/src/context.rs:77:1
|
77 | pub struct Context {
| ^^^^^^^^^^^^^^^^^^
note: struct `opentelemetry_api::context::Context` is defined in crate `opentelemetry_api`
--> /Users/someonetoignore/.cargo/registry/src/github.com-1ecc6299db9ec823/opentelemetry_api-0.18.0/src/context.rs:77:1
|
77 | pub struct Context {
| ^^^^^^^^^^^^^^^^^^
= note: perhaps two different versions of crate `opentelemetry_api` are being used?
note: associated function defined here
--> /Users/someonetoignore/.cargo/registry/src/github.com-1ecc6299db9ec823/tracing-opentelemetry-0.18.0/src/span_ext.rs:43:8
|
43 | fn set_parent(&self, cx: Context);
| ^^^^^^^^^^
For more information about this error, try `rustc --explain E0308`.
error: could not compile `tracing-utils` due to previous error
warning: build failed, waiting for other jobs to finish...
error: could not compile `tracing-utils` due to previous error
```
`tracing-opentelemetry` of version `0.19` is not yet released, that is supposed to have the update we need.
* similarly, `rustls`, `tokio-rustls`, `rustls-*` and `tls-listener` crates have similar issue:
```
error[E0308]: mismatched types
--> libs/postgres_backend/tests/simple_select.rs:112:78
|
112 | let mut make_tls_connect = tokio_postgres_rustls::MakeRustlsConnect::new(client_cfg);
| --------------------------------------------- ^^^^^^^^^^ expected struct `rustls::client::client_conn::ClientConfig`, found struct `ClientConfig`
| |
| arguments to this function are incorrect
|
= note: struct `ClientConfig` and struct `rustls::client::client_conn::ClientConfig` have similar names, but are actually distinct types
note: struct `ClientConfig` is defined in crate `rustls`
--> /Users/someonetoignore/.cargo/registry/src/github.com-1ecc6299db9ec823/rustls-0.21.0/src/client/client_conn.rs:125:1
|
125 | pub struct ClientConfig {
| ^^^^^^^^^^^^^^^^^^^^^^^
note: struct `rustls::client::client_conn::ClientConfig` is defined in crate `rustls`
--> /Users/someonetoignore/.cargo/registry/src/github.com-1ecc6299db9ec823/rustls-0.20.8/src/client/client_conn.rs:91:1
|
91 | pub struct ClientConfig {
| ^^^^^^^^^^^^^^^^^^^^^^^
= note: perhaps two different versions of crate `rustls` are being used?
note: associated function defined here
--> /Users/someonetoignore/.cargo/registry/src/github.com-1ecc6299db9ec823/tokio-postgres-rustls-0.9.0/src/lib.rs:23:12
|
23 | pub fn new(config: ClientConfig) -> Self {
| ^^^
For more information about this error, try `rustc --explain E0308`.
error: could not compile `postgres_backend` due to previous error
warning: build failed, waiting for other jobs to finish...
```
* aws crates: I could not make new API to work with bucket endpoint overload, and console e2e tests failed.
Other our tests passed, further investigation is worth to be done in https://github.com/neondatabase/neon/issues/4008
All non-trivial updates extracted into separate commits, also `carho
hakari` data and its manifest format were updated.
3 sets of crates remain unupdated:
* `base64` — touches proxy in a lot of places and changed its api (by
0.21 version) quite strongly since our version (0.13).
* `opentelemetry` and `opentelemetry-*` crates
```
error[E0308]: mismatched types
--> libs/tracing-utils/src/http.rs:65:21
|
65 | span.set_parent(parent_ctx);
| ---------- ^^^^^^^^^^ expected struct `opentelemetry_api::context::Context`, found struct `opentelemetry::Context`
| |
| arguments to this method are incorrect
|
= note: struct `opentelemetry::Context` and struct `opentelemetry_api::context::Context` have similar names, but are actually distinct types
note: struct `opentelemetry::Context` is defined in crate `opentelemetry_api`
--> /Users/someonetoignore/.cargo/registry/src/github.com-1ecc6299db9ec823/opentelemetry_api-0.19.0/src/context.rs:77:1
|
77 | pub struct Context {
| ^^^^^^^^^^^^^^^^^^
note: struct `opentelemetry_api::context::Context` is defined in crate `opentelemetry_api`
--> /Users/someonetoignore/.cargo/registry/src/github.com-1ecc6299db9ec823/opentelemetry_api-0.18.0/src/context.rs:77:1
|
77 | pub struct Context {
| ^^^^^^^^^^^^^^^^^^
= note: perhaps two different versions of crate `opentelemetry_api` are being used?
note: associated function defined here
--> /Users/someonetoignore/.cargo/registry/src/github.com-1ecc6299db9ec823/tracing-opentelemetry-0.18.0/src/span_ext.rs:43:8
|
43 | fn set_parent(&self, cx: Context);
| ^^^^^^^^^^
For more information about this error, try `rustc --explain E0308`.
error: could not compile `tracing-utils` due to previous error
warning: build failed, waiting for other jobs to finish...
error: could not compile `tracing-utils` due to previous error
```
`tracing-opentelemetry` of version `0.19` is not yet released, that is
supposed to have the update we need.
* similarly, `rustls`, `tokio-rustls`, `rustls-*` and `tls-listener`
crates have similar issue:
```
error[E0308]: mismatched types
--> libs/postgres_backend/tests/simple_select.rs:112:78
|
112 | let mut make_tls_connect = tokio_postgres_rustls::MakeRustlsConnect::new(client_cfg);
| --------------------------------------------- ^^^^^^^^^^ expected struct `rustls::client::client_conn::ClientConfig`, found struct `ClientConfig`
| |
| arguments to this function are incorrect
|
= note: struct `ClientConfig` and struct `rustls::client::client_conn::ClientConfig` have similar names, but are actually distinct types
note: struct `ClientConfig` is defined in crate `rustls`
--> /Users/someonetoignore/.cargo/registry/src/github.com-1ecc6299db9ec823/rustls-0.21.0/src/client/client_conn.rs:125:1
|
125 | pub struct ClientConfig {
| ^^^^^^^^^^^^^^^^^^^^^^^
note: struct `rustls::client::client_conn::ClientConfig` is defined in crate `rustls`
--> /Users/someonetoignore/.cargo/registry/src/github.com-1ecc6299db9ec823/rustls-0.20.8/src/client/client_conn.rs:91:1
|
91 | pub struct ClientConfig {
| ^^^^^^^^^^^^^^^^^^^^^^^
= note: perhaps two different versions of crate `rustls` are being used?
note: associated function defined here
--> /Users/someonetoignore/.cargo/registry/src/github.com-1ecc6299db9ec823/tokio-postgres-rustls-0.9.0/src/lib.rs:23:12
|
23 | pub fn new(config: ClientConfig) -> Self {
| ^^^
For more information about this error, try `rustc --explain E0308`.
error: could not compile `postgres_backend` due to previous error
warning: build failed, waiting for other jobs to finish...
```
* aws crates: I could not make new API to work with bucket endpoint
overload, and console e2e tests failed.
Other our tests passed, further investigation is worth to be done in
https://github.com/neondatabase/neon/issues/4008
This patch adds a pageserver-global background loop that evicts layers
in response to a shortage of available bytes in the $repo/tenants
directory's filesystem.
The loop runs periodically at a configurable `period`.
Each loop iteration uses `statvfs` to determine filesystem-level space
usage. It compares the returned usage data against two different types
of thresholds. The iteration tries to evict layers until app-internal
accounting says we should be below the thresholds. We cross-check this
internal accounting with the real world by making another `statvfs` at
the end of the iteration. We're good if that second statvfs shows that
we're _actually_ below the configured thresholds. If we're still above
one or more thresholds, we emit a warning log message, leaving it to the
operator to investigate further.
There are two thresholds:
- `max_usage_pct` is the relative available space, expressed in percent
of the total filesystem space. If the actual usage is higher, the
threshold is exceeded.
- `min_avail_bytes` is the absolute available space in bytes. If the
actual usage is lower, the threshold is exceeded.
The iteration evicts layers in LRU fashion with a reservation of up to
`tenant_min_resident_size` bytes of the most recent layers per tenant.
The layers not part of the per-tenant reservation are evicted
least-recently-used first until we're below all thresholds. The
`tenant_min_resident_size` can be overridden per tenant as
`min_resident_size_override` (bytes).
In addition to the loop, there is also an HTTP endpoint to perform one
loop iteration synchronous to the request. The endpoint takes an
absolute number of bytes that the iteration needs to evict before
pressure is relieved. The tests use this endpoint, which is a great
simplification over setting up loopback-mounts in the tests, which would
be required to test the statvfs part of the implementation. We will rely
on manual testing in staging to test the statvfs parts.
The HTTP endpoint is also handy in emergencies where an operator wants
the pageserver to evict a given amount of space _now. Hence, it's
arguments documented in openapi_spec.yml. The response type isn't
documented though because we don't consider it stable. The endpoint
should _not_ be used by Console but it could be used by on-call.
Co-authored-by: Joonas Koivunen <joonas@neon.tech>
Co-authored-by: Dmitry Rodionov <dmitry@neon.tech>
Co-authored-by: Heikki Linnakangas <heikki@neon.tech>
- Add support for splitting async postgres_backend into read and write halfes.
Safekeeper needs this for bidirectional streams. To this end, encapsulate
reading-writing postgres messages to framed.rs with split support without any
additional changes (relying on BufRead for reading and BytesMut out buffer for
writing).
- Use async postgres_backend throughout safekeeper (and in proxy auth link
part).
- In both safekeeper COPY streams, do read-write from the same thread/task with
select! for easier error handling.
- Tidy up finishing CopyBoth streams in safekeeper sending and receiving WAL
-- join split parts back catching errors from them before returning.
Initially I hoped to do that read-write without split at all, through polling
IO:
https://github.com/neondatabase/neon/pull/3522
However that turned out to be more complicated than I initially expected
due to 1) borrow checking and 2) anon Future types. 1) required Rc<Refcell<...>>
which is Send construct just to satisfy the checker; 2) can be workaround with
transmute. But this is so messy that I decided to leave split.
To untie cyclic dependency between sync and async versions of postgres_backend,
copy QueryError and some logging/error routines to postgres_backend.rs. This is
temporal glue to make commits smaller, sync version will be dropped by the
upcoming commit completely.
## Describe your changes
## Issue ticket number and link
#3479
## Checklist before requesting a review
- [x] 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.
This patch adds basic access statistics for historic layers
and exposes them in the management API's `LayerMapInfo`.
We record the accesses in the `{Delta,Image}Layer::load()` function
because it's the common path of
* page_service (`Timline::get_reconstruct_data()`)
* Compaction (`PersistentLayer::iter()` and `PersistentLayer::key_iter()`)
The stats survive residence status changes, and record these as well.
When scraping the layer map endpoint to record its evolution over time,
one must account for stat resets because they are in-memory only and
will reset on pageserver restart.
Use the launch timestamp header added by (#3527) to identify pageserver restarts.
This is PR https://github.com/neondatabase/neon/pull/3496
- add parse_query_param()
- use Cow<> where possible
- move param parsing code to utils::http::request
This was originally PR https://github.com/neondatabase/neon/pull/3502
which targeted a different branch.
closes #3510
