Timeline cancellation running in parallel with gc yields error log lines
like:
```
Gc failed 1 times, retrying in 2s: TimelineCancelled
```
They are completely harmless though and normal to occur. Therefore, only
print those messages at an info level. Still print them at all so that
we know what is going on if we focus on a single timeline.
Part of #8128.
## Problem
Currently, scrubber `scan_metadata` command will return with an error
code if the metadata on remote storage is corrupted with fatal errors.
To safely deploy this command in a cronjob, we want to differentiate
between failures while running scrubber command and the erroneous
metadata. At the same time, we also want our regression tests to catch
corrupted metadata using the scrubber command.
## Summary of changes
- Return with error code only when the scrubber command fails
- Uses explicit checks on errors and warnings to determine metadata
health in regression tests.
**Resolve conflict with `tenant-snapshot` command (after shard split):**
[`test_scrubber_tenant_snapshot`](https://github.com/neondatabase/neon/blob/yuchen/scrubber-scan-cleanup-before-prod/test_runner/regress/test_storage_scrubber.py#L23)
failed before applying 422a8443dd
- When taking a snapshot, the old `index_part.json` in the unsharded
tenant directory is not kept.
- The current `list_timeline_blobs` implementation consider no
`index_part.json` as a parse error.
- During the scan, we are only analyzing shards with highest shard
count, so we will not get a parse error. but we do need to add the
layers to tenant object listing, otherwise we will get index is
referencing a layer that is not in remote storage error.
- **Action:** Add s3_layers from `list_timeline_blobs` regardless of
parsing error
Signed-off-by: Yuchen Liang <yuchen@neon.tech>
## Problem
We lack a rust bench for the inmemory layer and delta layer write paths:
it is useful to benchmark these components independent of postgres & WAL
decoding.
Related: https://github.com/neondatabase/neon/issues/8452
## Summary of changes
- Refactor DeltaLayerWriter to avoid carrying a Timeline, so that it can
be cleanly tested + benched without a Tenant/Timeline test harness. It
only needed the Timeline for building `Layer`, so this can be done in a
separate step.
- Add `bench_ingest`, which exercises a variety of workload "shapes"
(big values, small values, sequential keys, random keys)
- Include a small uncontroversial optimization: in `freeze`, only
exhaustively walk values to assert ordering relative to end_lsn in debug
mode.
These benches are limited by drive performance on a lot of machines, but
still useful as a local tool for iterating on CPU/memory improvements
around this code path.
Anecdotal measurements on Hetzner AX102 (Ryzen 7950xd):
```
ingest-small-values/ingest 128MB/100b seq
time: [1.1160 s 1.1230 s 1.1289 s]
thrpt: [113.38 MiB/s 113.98 MiB/s 114.70 MiB/s]
Found 1 outliers among 10 measurements (10.00%)
1 (10.00%) low mild
Benchmarking ingest-small-values/ingest 128MB/100b rand: Warming up for 3.0000 s
Warning: Unable to complete 10 samples in 10.0s. You may wish to increase target time to 18.9s.
ingest-small-values/ingest 128MB/100b rand
time: [1.9001 s 1.9056 s 1.9110 s]
thrpt: [66.982 MiB/s 67.171 MiB/s 67.365 MiB/s]
Benchmarking ingest-small-values/ingest 128MB/100b rand-1024keys: Warming up for 3.0000 s
Warning: Unable to complete 10 samples in 10.0s. You may wish to increase target time to 11.0s.
ingest-small-values/ingest 128MB/100b rand-1024keys
time: [1.0715 s 1.0828 s 1.0937 s]
thrpt: [117.04 MiB/s 118.21 MiB/s 119.46 MiB/s]
ingest-small-values/ingest 128MB/100b seq, no delta
time: [425.49 ms 429.07 ms 432.04 ms]
thrpt: [296.27 MiB/s 298.32 MiB/s 300.83 MiB/s]
Found 1 outliers among 10 measurements (10.00%)
1 (10.00%) low mild
ingest-big-values/ingest 128MB/8k seq
time: [373.03 ms 375.84 ms 379.17 ms]
thrpt: [337.58 MiB/s 340.57 MiB/s 343.13 MiB/s]
Found 1 outliers among 10 measurements (10.00%)
1 (10.00%) high mild
ingest-big-values/ingest 128MB/8k seq, no delta
time: [81.534 ms 82.811 ms 83.364 ms]
thrpt: [1.4994 GiB/s 1.5095 GiB/s 1.5331 GiB/s]
Found 1 outliers among 10 measurements (10.00%)
```
## Problem
Sometimes, a layer is Covered by hasn't yet been evicted from local disk
(e.g. shortly after image layer generation). It is not good use of
resources to download these to a secondary location, as there's a good
chance they will never be read.
This follows the previous change that added layer visibility:
- #8511
Part of epic:
- https://github.com/neondatabase/neon/issues/8398
## Summary of changes
- When generating heatmaps, only include Visible layers
- Update test_secondary_downloads to filter to visible layers when
listing layers from an attached location
## Problem
In staging, we could see that occasionally tenants were wrapping their
pageserver_visible_physical_size metric past zero to 2^64.
This is harmless right now, but will matter more later when we start
using visible size in things like the /utilization endpoint.
## Summary of changes
- Add debug asserts that detect this case. `test_gc_of_remote_layers`
works as a reproducer for this issue once the asserts are added.
- Tighten up the interface around access_stats so that only Layer can
mutate it.
- In Layer, wrap calls to `record_access` in code that will update the
visible size statistic if the access implicitly marks the layer visible
(this was what caused the bug)
- In LayerManager::rewrite_layers, use the proper set_visibility layer
function instead of directly using access_stats (this is an additional
path where metrics could go bad.)
- Removed unused instances of LayerAccessStats in DeltaLayer and
ImageLayer which I noticed while reviewing the code paths that call
record_access.
## Problem
The controller scale test does random migrations. These mutate secondary
locations, and therefore can cause secondary optimizations to happen in
the background, violating the test's expectation that consistency_check
will work as there are no reconciliations running.
Example:
https://neon-github-public-dev.s3.amazonaws.com/reports/main/10247161379/index.html#suites/07874de07c4a1c9effe0d92da7755ebf/6316beacd3fb3060/
## Summary of changes
- Only migrate to existing secondary locations, not randomly picked
nodes, so that we can do a fast reconcile_until_idle (otherwise
reconcile_until_idle is takes a long time to create new secondary
locations).
- Do a reconcile_until_idle before consistency_check.
## Problem
We need to test the logical replication with some external consumers.
## Summary of changes
A test of the logical replication with Debezium as a consumer was added.
---------
Co-authored-by: Alexander Bayandin <alexander@neon.tech>
We don't use it for packaging, and 'poetry install' will soon error
otherwise. Also remove name and version fields as these are not required for
non-packaging mode.
#8600 missed the hunk changing index_part.json informative version.
Include it in this PR, in addition add more non-warning index_part.json
versions to scrubber.
## Problem
We have been maintaining two read paths (legacy and vectored) for a
while now. The legacy read-path was only used for cross validation in some tests.
## Summary of changes
* Tweak all tests that were using the legacy read path to use the
vectored read path instead
* Remove the read path dispatching based on the pageserver configs
* Remove the legacy read path code
We will be able to remove the single blob io code in
`pageserver/src/tenant/blob_io.rs` when https://github.com/neondatabase/neon/issues/7386 is complete.
Closes https://github.com/neondatabase/neon/issues/8005
Currently, we do not have facilities to persistently block GC on a
tenant for whatever reason. We could do a tenant configuration update,
but that is risky for generation numbers and would also be transient.
Introduce a `gc_block` facility in the tenant, which manages per
timeline blocking reasons.
Additionally, add HTTP endpoints for enabling/disabling manual gc
blocking for a specific timeline. For debugging, individual tenant
status now includes a similar string representation logged when GC is
skipped.
Cc: #6994
Add dry-run mode that does not produce any image layer + delta layer. I
will use this code to do some experiments and see how much space we can
reclaim for tenants on staging. Part of
https://github.com/neondatabase/neon/issues/8002
* Add dry-run mode that runs the full compaction process without
updating the layer map. (We never call finish on the writers and the
files will be removed before exiting the function).
* Add compaction statistics and print them at the end of compaction.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
> Currently, long-running LR tests recreate endpoints every night. We'd
like to have along-running buildup of history to exercise the pageserver
in this case (instead of "unit-testing" the same behavior everynight).
Closes#8317
## Summary of changes
- Update Postgres version for replication tests
- Set `BENCHMARK_PROJECT_ID_PUB`/`BENCHMARK_PROJECT_ID_SUB` env vars to
projects that were created for this purpose
---------
Co-authored-by: Sasha Krassovsky <krassovskysasha@gmail.com>
Currently if `GET
/v1/tenant/x/timeline/y?force-await-initial-logical-size=true` is
requested for a root timeline created within the current pageserver
session, the request handler panics hitting the debug assertion. These
timelines will always have an accurate (at initdb import) calculated
logical size. Fix is to never attempt prioritizing timeline size
calculation if we already have an exact value.
Split off from #8528.
## Problem
In some cases, a deadlock between `build-and-test` and
`trigger-e2e-tests` workflows can happen:
```
Build and Test
Canceling since a deadlock for concurrency group 'Build and Test-8600/merge-anysha' was detected between 'top level workflow' and 'trigger-e2e-tests'
```
I don't understand the reason completely, probably `${{ github.workflow
}}` got evaluated to the same value and somehow caused the issue.
We don't need to limit concurrency for `trigger-e2e-tests`
workflow.
See
https://neondb.slack.com/archives/C059ZC138NR/p1722869486708179?thread_ts=1722869027.960029&cid=C059ZC138NR
## Problem
We don't trigger e2e tests for draft PRs, but we do trigger them once a
PR is in the "Ready for review" state.
Sometimes, a PR can be marked as "Ready for review" before we finish
image building. In such cases, triggering e2e tests fails.
## Summary of changes
- Make `trigger-e2e-tests` job poll status of `promote-images` job from
the build-and-test workflow for the last commit. And trigger only if the
status is `success`
- Remove explicit image checking from the workflow
- Add `concurrency` for `triggere-e2e-tests` workflow to make it
possible to cancel jobs in progress (if PR moves from "Draft" to "Ready
for review" several times in a row)
## Problem
PR #7992 was merged without correspondent changes in Postgres submodules
and this is why test_oid_overflow.py is failed now.
## Summary of changes
Bump Postgres versions
## 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>
## Problem
There is an unused safekeeper option `partial_backup_enabled`.
`partial_backup_enabled` was implemented in #6530, but this option was
always turned into enabled in #8022.
If you intended to keep this option for a specific reason, I will close
this PR.
## Summary of changes
I removed an unused safekeeper option `partial_backup_enabled`.
part of https://github.com/neondatabase/neon/issues/8002
## Summary of changes
Add a `SplitImageWriter` that automatically splits image layer based on
estimated target image layer size. This does not consider compression
and we might need a better metrics.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
Co-authored-by: Arpad Müller <arpad-m@users.noreply.github.com>
We need both compaction and gc lock for gc-compaction. The lock order
should be the same everywhere, otherwise there could be a deadlock where
A waits for B and B waits for A.
We also had a double-lock issue. The compaction lock gets acquired in
the outer `compact` function. Note that the unit tests directly call
`compact_with_gc`, and therefore not triggering the issue.
## Summary of changes
Ensure all places acquire compact lock and then gc lock. Remove an extra
compact lock acqusition.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
Currently, our backward compatibility tests only look one release back.
That means, for example, that when we switch on image layer compression
by default, we'll test reading of uncompressed layers for one release,
and then stop doing it. When we make an index_part.json format change,
we'll test against the old format for a week, then stop (unless we write
separate unit tests for each old format).
The reality in the field is that data in old formats will continue to
exist for weeks/months/years. When we make major format changes, we
should retain examples of the old format data, and continuously verify
that the latest code can still read them.
This test uses contents from a new path in the public S3 bucket,
`compatibility-data-snapshots/`. It is populated by hand. The first
important artifact is one from before we switch on compression, so that
we will keep testing reads of uncompressed data. We will generate more
artifacts ahead of other key changes, like when we update remote storage
format for archival timelines.
Closes: https://github.com/neondatabase/cloud/issues/15576
This commit tries to fix regular load spikes on staging, caused by too
many eviction and partial upload operations running at the same time.
Usually it was hapenning after restart, for partial backup the load was
delayed.
- Add a semaphore for evictions (2 permits by default)
- Rename `resident_since` to `evict_not_before` and smooth out the curve
by using random duration
- Use random duration in partial uploads as well
related to https://github.com/neondatabase/neon/issues/6338
some discussion in
https://neondb.slack.com/archives/C033RQ5SPDH/p1720601531744029
Makes `flush_frozen_layer` add a barrier to the upload queue and makes
it wait for that barrier to be reached until it lets the flushing be
completed.
This gives us backpressure and ensures that writes can't build up in an
unbounded fashion.
Fixes#7317
Chaos injection bridges the gap between automated testing (where we do
lots of different things with small, short-lived tenants), and staging
(where we do many fewer things, but with larger, long-lived tenants).
This PR adds a first type of chaos which isn't really very chaotic: it's
live migration of tenants between healthy pageservers. This nevertheless
provides continuous checks that things like clean, prompt shutdown of
tenants works for realistically deployed pageservers with realistically
large tenants.
## Problem
Previously, when we do a timeline deletion, shards will delete layers
that belong to an ancestor. That is not a correctness issue, because
when we delete a timeline, we're always deleting it from all shards, and
destroying data for that timeline is clearly fine.
However, there exists a race where one shard might start doing this
deletion while another shard has not yet received the deletion request,
and might try to access an ancestral layer. This creates ambiguity over
the "all layers referenced by my index should always exist" invariant,
which is important to detecting and reporting corruption.
Now that we have a GC mode for clearing up ancestral layers, we can rely
on that to clean up such layers, and avoid deleting them right away.
This makes things easier to reason about: there are now no cases where a
shard will delete a layer that belongs to a ShardIndex other than
itself.
## Summary of changes
- Modify behavior of RemoteTimelineClient::delete_all
- Add `test_scrubber_physical_gc_timeline_deletion` to exercise this
case
- Tweak AWS SDK config in the scrubber to enable retries. Motivated by
seeing the test for this feature encounter some transient "service
error" S3 errors (which are probably nothing to do with the changes in
this PR)
## Problem
`allure_attach_from_dir` method might create `tar.zst` archives even
if `--alluredir` is not set (i.e. Allure results collection is disabled)
## Summary of changes
- Don't run `allure_attach_from_dir` if `--alluredir` is not set
part of https://github.com/neondatabase/neon/issues/8002
Due to the limitation of the current layer map implementation, we cannot
directly replace a layer. It's interpreted as an insert and a deletion,
and there will be file exist error when renaming the newly-created layer
to replace the old layer. We work around that by changing the end key of
the image layer. A long-term fix would involve a refactor around the
layer file naming. For delta layers, we simply skip layers with the same
key range produced, though it is possible to add an extra key as an
alternative solution.
* The image layer range for the layers generated from gc-compaction will
be Key::MIN..(Key..MAX-1), to avoid being recognized as an L0 delta
layer.
* Skip existing layers if it turns out that we need to generate a layer
with the same persistent key in the same generation.
Note that it is possible that the newly-generated layer has different
content from the existing layer. For example, when the user drops a
retain_lsn, the compaction could have combined or dropped some records,
therefore creating a smaller layer than the existing one. We discard the
"optimized" layer for now because we cannot deal with such rewrites
within the same generation.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
Co-authored-by: Christian Schwarz <christian@neon.tech>
## Problem
We recently added a "visibility" state to layers, but nothing
initializes it.
Part of:
- #8398
## Summary of changes
- Add a dependency on `range-set-blaze`, which is used as a fast
incrementally updated alternative to KeySpace. We could also use this to
replace the internals of KeySpaceRandomAccum if we wanted to. Writing a
type that does this kind of "BtreeMap & merge overlapping entries" thing
isn't super complicated, but no reason to write this ourselves when
there's a third party impl available.
- Add a function to layermap to calculate visibilities for each layer
- Add a function to Timeline to call into layermap and then apply these
visibilities to the Layer objects.
- Invoke the calculation during startup, after image layer creations,
and when removing branches. Branch removal and image layer creation are
the two ways that a layer can go from Visible to Covered.
- Add unit test & benchmark for the visibility calculation
- Expose `pageserver_visible_physical_size` metric, which should always
be <= `pageserver_remote_physical_size`.
- This metric will feed into the /v1/utilization endpoint later: the
visible size indicates how much space we would like to use on this
pageserver for this tenant.
- When `pageserver_visible_physical_size` is greater than
`pageserver_resident_physical_size`, this is a sign that the tenant has
long-idle branches, which result in layers that are visible in
principle, but not used in practice.
This does not keep visibility hints up to date in all cases:
particularly, when creating a child timeline, any previously covered
layers will not get marked Visible until they are accessed.
Updates after image layer creation could be implemented as more of a
special case, but this would require more new code: the existing depth
calculation code doesn't maintain+yield the list of deltas that would be
covered by an image layer.
## Performance
This operation is done rarely (at startup and at timeline deletion), so
needs to be efficient but not ultra-fast.
There is a new `visibility` bench that measures runtime for a synthetic
100k layers case (`sequential`) and a real layer map (`real_map`) with
~26k layers.
The benchmark shows runtimes of single digit milliseconds (on a ryzen
7950). This confirms that the runtime shouldn't be a problem at startup
(as we already incur S3-level latencies there), but that it's slow
enough that we definitely shouldn't call it more often than necessary,
and it may be worthwhile to optimize further later (things like: when
removing a branch, only bother scanning layers below the branchpoint)
```
visibility/sequential time: [4.5087 ms 4.5894 ms 4.6775 ms]
change: [+2.0826% +3.9097% +5.8995%] (p = 0.00 < 0.05)
Performance has regressed.
Found 24 outliers among 100 measurements (24.00%)
2 (2.00%) high mild
22 (22.00%) high severe
min: 0/1696070, max: 93/1C0887F0
visibility/real_map time: [7.0796 ms 7.0832 ms 7.0871 ms]
change: [+0.3900% +0.4505% +0.5164%] (p = 0.00 < 0.05)
Change within noise threshold.
Found 4 outliers among 100 measurements (4.00%)
3 (3.00%) high mild
1 (1.00%) high severe
min: 0/1696070, max: 93/1C0887F0
visibility/real_map_many_branches
time: [4.5285 ms 4.5355 ms 4.5434 ms]
change: [-1.0012% -0.8004% -0.5969%] (p = 0.00 < 0.05)
Change within noise threshold.
```
Before, we had four versions of linux-raw-sys in our dependency graph:
```
linux-raw-sys@0.1.4
linux-raw-sys@0.3.8
linux-raw-sys@0.4.13
linux-raw-sys@0.6.4
```
now it's only two:
```
linux-raw-sys@0.4.13
linux-raw-sys@0.6.4
```
The changes in this PR are minimal. In order to get to its state one
only has to update procfs in Cargo.toml to 0.16 and do `cargo update -p
tempfile -p is-terminal -p prometheus`.
# Motivation
The working theory for hung systemd during PS deploy
(https://github.com/neondatabase/cloud/issues/11387) is that leftover
walredo processes trigger a race condition.
In https://github.com/neondatabase/neon/pull/8150 I arranged that a
clean Tenant shutdown does actually kill its walredo processes.
But many prod machines don't manage to shut down all their tenants until
the 10s systemd timeout hits and, presumably, triggers the race
condition in systemd / the Linux kernel that causes the frozen systemd
# Solution
This PR bolts on a rather ugly mechanism to shut down tenant managers
out of order 8s after we've received the SIGTERM from systemd.
# Changes
- add a global registry of `Weak<WalRedoManager>`
- add a special thread spawned during `shutdown_pageserver` that sleeps
for 8s, then shuts down all redo managers in the registry and prevents
new redo managers from being created
- propagate the new failure mode of tenant spawning throughout the code
base
- make sure shut down tenant manager results in
PageReconstructError::Cancelled so that if Timeline::get calls come in
after the shutdown, they do the right thing
## Problem
In https://github.com/neondatabase/neon/pull/8241 I've accidentally
removed `create-test-report` dependency on `benchmarks` job
## Summary of changes
- Run `create-test-report` after `benchmarks` job
Uses the newly added APIs from #8541 named `stream_tenants_generic` and
`stream_objects_with_retries` and extends them with
`list_objects_with_retries_generic` and
`stream_tenant_timelines_generic` to migrate the `find-garbage` command
of the scrubber to `GenericRemoteStorage`.
Part of https://github.com/neondatabase/neon/issues/7547
## Problem
This code was confusing, untested and covered:
- an impossible case, where intent state is AttacheStale (we never do
this)
- a rare edge case (going from AttachedMulti to Attached), which we were
not testing, and in any case the pageserver internally does the same
Tenant reset in this transition as it would do if we incremented
generation.
Closes: https://github.com/neondatabase/neon/issues/8367
## Summary of changes
- Simplify the logic to only skip incrementing the generation if the
location already has the expected generation and the exact same mode.
In some cases, we can get a negative metric for replication_delay_bytes.
My best guess from all the research I've done is that we evaluate
pg_last_wal_receive_lsn() before pg_last_wal_replay_lsn(), and that by
the time everything is said and done, the replay LSN has advanced past
the receive LSN. In this case, our lag can effectively be modeled as
0 due to the speed of the WAL reception and replay.
Since the introduction of sharding, the protocol handling loop in
`handle_pagerequests` cannot know anymore which concrete
`Tenant`/`Timeline` object any of the incoming `PagestreamFeMessage`
resolves to.
In fact, one message might resolve to one `Tenant`/`Timeline` while
the next one may resolve to another one.
To avoid going to tenant manager, we added the `shard_timelines` which
acted as an ever-growing cache that held timeline gate guards open for
the lifetime of the connection.
The consequence of holding the gate guards open was that we had to be
sensitive to every cached `Timeline::cancel` on each interaction with
the network connection, so that Timeline shutdown would not have to wait
for network connection interaction.
We can do better than that, meaning more efficiency & better
abstraction.
I proposed a sketch for it in
* https://github.com/neondatabase/neon/pull/8286
and this PR implements an evolution of that sketch.
The main idea is is that `mod page_service` shall be solely concerned
with the following:
1. receiving requests by speaking the protocol / pagestream subprotocol
2. dispatching the request to a corresponding method on the correct
shard/`Timeline` object
3. sending response by speaking the protocol / pagestream subprotocol.
The cancellation sensitivity responsibilities are clear cut:
* while in `page_service` code, sensitivity to page_service cancellation
is sufficient
* while in `Timeline` code, sensitivity to `Timeline::cancel` is
sufficient
To enforce these responsibilities, we introduce the notion of a
`timeline::handle::Handle` to a `Timeline` object that is checked out
from a `timeline::handle::Cache` for **each request**.
The `Handle` derefs to `Timeline` and is supposed to be used for a
single async method invocation on `Timeline`.
See the lengthy doc comment in `mod handle` for details of the design.
part of https://github.com/neondatabase/neon/issues/8002
For child branches, we will pull the image of the modified keys from the
parant into the child branch, which creates a full history for
generating key retention. If there are not enough delta keys, the image
won't be wrote eventually, and we will only keep the deltas inside the
child branch. We could avoid the wasteful work to pull the image from
the parent if we can know the number of deltas in advance, in the future
(currently we always pull image for all modified keys in the child
branch)
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
We run regression tests on `release` & `debug` builds for each of the
three supported Postgres versions (6 in total).
With upcoming ARM support and Postgres 17, the number of jobs will jump
to 16, which is a lot.
See the internal discussion here:
https://neondb.slack.com/archives/C033A2WE6BZ/p1722365908404329
## Summary of changes
- Run `regress-tests` job in debug builds only with the latest Postgres
version
- Do not do `debug` builds on release branches
part of https://github.com/neondatabase/neon/issues/8184
# Problem
We want to bypass PS PageCache for all data block reads, but
`compact_level0_phase1` currently uses `ValueRef::load` to load the WAL
records from delta layers.
Internally, that maps to `FileBlockReader:read_blk` which hits the
PageCache
[here](e78341e1c2/pageserver/src/tenant/block_io.rs (L229-L236)).
# Solution
This PR adds a mode for `compact_level0_phase1` that uses the
`MergeIterator` for reading the `Value`s from the delta layer files.
`MergeIterator` is a streaming k-merge that uses vectored blob_io under
the hood, which bypasses the PS PageCache for data blocks.
Other notable changes:
* change the `DiskBtreeReader::into_stream` to buffer the node, instead
of holding a `PageCache` `PageReadGuard`.
* Without this, we run out of page cache slots in
`test_pageserver_compaction_smoke`.
* Generally, `PageReadGuard`s aren't supposed to be held across await
points, so, this is a general bugfix.
# Testing / Validation / Performance
`MergeIterator` has not yet been used in production; it's being
developed as part of
* https://github.com/neondatabase/neon/issues/8002
Therefore, this PR adds a validation mode that compares the existing
approach's value iterator with the new approach's stream output, item by
item.
If they're not identical, we log a warning / fail the unit/regression
test.
To avoid flooding the logs, we apply a global rate limit of once per 10
seconds.
In any case, we use the existing approach's value.
Expected performance impact that will be monitored in staging / nightly
benchmarks / eventually pre-prod:
* with validation:
* increased CPU usage
* ~doubled VirtualFile read bytes/second metric
* no change in disk IO usage because the kernel page cache will likely
have the pages buffered on the second read
* without validation:
* slightly higher DRAM usage because each iterator participating in the
k-merge has a dedicated buffer (as opposed to before, where compactions
would rely on the PS PageCaceh as a shared evicting buffer)
* less disk IO if previously there were repeat PageCache misses (likely
case on a busy production Pageserver)
* lower CPU usage: PageCache out of the picture, fewer syscalls are made
(vectored blob io batches reads)
# Rollout
The new code is used with validation mode enabled-by-default.
This gets us validation everywhere by default, specifically in
- Rust unit tests
- Python tests
- Nightly pagebench (shouldn't really matter)
- Staging
Before the next release, I'll merge the following aws.git PR that
configures prod to continue using the existing behavior:
* https://github.com/neondatabase/aws/pull/1663
# Interactions With Other Features
This work & rollout should complete before Direct IO is enabled because
Direct IO would double the IOPS & latency for each compaction read
(#8240).
# Future Work
The streaming k-merge's memory usage is proportional to the amount of
memory per participating layer.
But `compact_level0_phase1` still loads all keys into memory for
`all_keys_iter`.
Thus, it continues to have active memory usage proportional to the
number of keys involved in the compaction.
Future work should replace `all_keys_iter` with a streaming keys
iterator.
This PR has a draft in its first commit, which I later reverted because
it's not necessary to achieve the goal of this PR / issue #8184.
Change Azure storage configuration to point to new variables/secrets. They have
the `_NEW` suffix in order not to disrupt any tests while we complete the
switch.
Part of #8128, followup to #8480. closes#8421.
Enable scrubber to optionally post metadata scan health results to
storage controller.
Signed-off-by: Yuchen Liang <yuchen@neon.tech>
