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
## 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)
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.
```
# 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
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>
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.
If compression is enabled, we currently try compressing each image
larger than a specific size and if the compressed version is smaller, we
write that one, otherwise we use the uncompressed image. However, this
might sometimes be a wasteful process, if there is a substantial amount
of images that don't compress well.
The compression metrics added in #8420
`pageserver_compression_image_in_bytes_total` and
`pageserver_compression_image_out_bytes_total` are well designed for
answering the question how space efficient the total compression process
is end-to-end, which helps one to decide whether to enable it or not.
To answer the question of how much waste there is in terms of trial
compression, so CPU time, we add two metrics:
* one about the images that have been trial-compressed (considered), and
* one about the images where the compressed image has actually been
written (chosen).
There is different ways of weighting them, like for example one could
look at the count, or the compressed data. But the main contributor to
compression CPU usage is amount of data processed, so we weight the
images by their *uncompressed* size. In other words, the two metrics
are:
* `pageserver_compression_image_in_bytes_considered`
* `pageserver_compression_image_in_bytes_chosen`
Part of #5431
## Problem
The secondary download HTTP API is meant to return 200 if the download
is complete, and 202 if it is still in progress. In #8198 the download
implementation was changed to drop out with success early if it
over-runs a time budget, which resulted in 200 responses for incomplete
downloads.
This breaks storcon_cli's "tenant-warmup" command, which uses the OK
status to indicate download complete.
## Summary of changes
- Only return 200 if we get an Ok() _and_ the progress stats indicate
the download is complete.
Uses the Stream based `list_streaming` function added by #8457 in tenant
deletion, as suggested in https://github.com/neondatabase/neon/pull/7932#issuecomment-2150480180 .
We don't have to worry about retries, as the function is wrapped inside
an outer retry block. If there is a retryable error either during the
listing or during deletion, we just do a fresh start.
Also adds `+ Send` bounds as they are required by the
`delete_tenant_remote` function.
Persists whether a timeline is archived or not in `index_part.json`. We
only return success if the upload has actually worked successfully.
Also introduces a new `index_part.json` version number.
Fixes#8459
Part of #8088
close https://github.com/neondatabase/neon/issues/8435
## Summary of changes
If L0 compaction did not include all L0 layers, skip image generation.
There are multiple possible solutions to the original issue, i.e., an
alternative is to wrap the partial L0 compaction in a loop until it
compacts all L0 layers. However, considering that we should weight all
tenants equally, the current solution can ensure everyone gets a chance
to run compaction, and those who write too much won't get a chance to
create image layers. This creates a natural backpressure feedback that
they get a slower read due to no image layers are created, slowing down
their writes, and eventually compaction could keep up with their writes
+ generate image layers.
Consider deployment, we should add an alert on "skipping image layer
generation", so that we won't run into the case that image layers are
not generated => incidents again.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
Problem
-------
wait_lsn timeouts result in a user-facing errors like
```
$ /tmp/neon/pg_install/v16/bin/pgbench -s3424 -i -I dtGvp user=neondb_owner dbname=neondb host=ep-tiny-wave-w23owa37.eastus2.azure.neon.build sslmode=require options='-cstatement_timeout=0 '
dropping old tables...
NOTICE: table "pgbench_accounts" does not exist, skipping
NOTICE: table "pgbench_branches" does not exist, skipping
NOTICE: table "pgbench_history" does not exist, skipping
NOTICE: table "pgbench_tellers" does not exist, skipping
creating tables...
generating data (server-side)...
vacuuming...
pgbench: error: query failed: ERROR: [NEON_SMGR] [shard 0] could not read block 214338 in rel 1663/16389/16839.0 from page server at lsn C/E1C12828
DETAIL: page server returned error: LSN timeout: Timed out while waiting for WAL record at LSN C/E1418528 to arrive, last_record_lsn 6/999D9CA8 disk consistent LSN=6/999D9CA8, WalReceiver status: (update 2024-07-25 08:30:07): connecting to node 25, safekeeper candidates (id|update_time|commit_lsn): [(21|08:30:16|C/E1C129E0), (23|08:30:16|C/E1C129E0), (25|08:30:17|C/E1C129E0)]
CONTEXT: while scanning block 214338 of relation "public.pgbench_accounts"
pgbench: detail: Query was: vacuum analyze pgbench_accounts
```
Solution
--------
Its better to be slow than to fail the queries.
If the app has a deadline, it can use `statement_timeout`.
In the long term, we want to eliminate wait_lsn timeout.
In the short term (this PR), we bump the wait_lsn timeout to
a larger value to reduce the frequency at which these wait_lsn timeouts
occur.
We will observe SLOs and specifically
`pageserver_wait_lsn_seconds_bucket`
before we eliminate the timeout completely.
## Problem
Vectored get is already enabled in all prod regions without validation.
The pageserver defaults
are out of sync however.
## Summary of changes
Update the pageserver defaults to match the prod config. Also means that
when running tests locally,
people don't have to use the env vars to get the prod config.
## Problem
The scrubber would like to check the highest mtime in a tenant's objects
as a safety check during purges. It recently switched to use
GenericRemoteStorage, so we need to expose that in the listing methods.
## Summary of changes
- In Listing.keys, return a ListingObject{} including a last_modified
field, instead of a RemotePath
---------
Co-authored-by: Arpad Müller <arpad-m@users.noreply.github.com>
There is a race condition between timeline shutdown and the split task.
Timeline shutdown first shuts down the upload queue, and only then fires
the cancellation token. A parallel running timeline split operation
might thus encounter a cancelled upload queue before the cancellation
token is fired, and print a noisy error.
Fix this by mapping `anyhow::Error{ NotInitialized::ShuttingDown }) to
`FlushLayerError::Cancelled` instead of `FlushLayerError::Other(_)`.
Fixes#8496
This pull request (should) fix the failure of test_gc_feedback. See the
explanation in the newly-added test case.
Part of https://github.com/neondatabase/neon/issues/8002
Allow incomplete history for the compaction algorithm.
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
Re-attach blocks the pageserver http server from starting up. Hence, it
can't reply to heartbeats
until that's done. This makes the storage controller mark the node
off-line (not good). We worked
around this by setting the interval after which nodes are marked offline
to 5 minutes. This isn't a
long term solution.
## Summary of changes
* Introduce a new `NodeAvailability` state: `WarmingUp`. This state
models the following time interval:
* From receiving the re-attach request until the pageserver replies to
the first heartbeat post re-attach
* The heartbeat delta generator becomes aware of this state and uses a
separate longer interval
* Flag `max-warming-up-interval` now models the longer timeout and
`max-offline-interval` the shorter one to
match the names of the states
Closes https://github.com/neondatabase/neon/issues/7552
Before this PR
1.The circuit breaker would trip on CompactionError::Shutdown. That's
wrong, we want to ignore those cases.
2. remote timeline client shutdown would not be mapped to
CompactionError::Shutdown in all circumstances.
We observed this in staging, see
https://neondb.slack.com/archives/C033RQ5SPDH/p1721829745384449
This PR fixes (1) with a simple `match` statement, and (2) by switching
a bunch of `anyhow` usage over to distinguished errors that ultimately
get mapped to `CompactionError::Shutdown`.
I removed the implicit `#[from]` conversion from `anyhow::Error` to
`CompactionError::Other` to discover all the places that were mapping
remote timeline client shutdown to `anyhow::Error`.
In my opinion `#[from]` is an antipattern and we should avoid it,
especially for `anyhow::Error`. If some callee is going to return
anyhow, the very least the caller should to is to acknowledge, through a
`map_err(MyError::Other)` that they're conflating different failure
reasons.
## Problem
PR that modified compaction raced with PR that modified the GcInfo
structure
## Summary of changes
Fix it
Co-authored-by: Vlad Lazar <vlalazar.vlad@gmail.com>
## Problem
The in-memory layer vectored read was very slow in some conditions
(walingest::test_large_rel) test. Upon profiling, I realised that 80% of
the time was spent building up the binary heap of reads. This stage
isn't actually needed.
## Summary of changes
Remove the planning stage as we never took advantage of it in order to
merge reads. There should be no functional change from this patch.
## Problem
Previously, Timeline::gc_info was only updated in a batch operation at
the start of GC. That means that timelines didn't generally have
accurate information about who their children were before the first GC,
or between GC cycles.
Knowledge of child branches is important for calculating layer
visibility in #8398
## Summary of changes
- Split out part of refresh_gc_info into initialize_gc_info, which is
now called early in startup
- Include TimelineId in retain_lsns so that we can later add/remove the
LSNs for particular children
- When timelines are added/removed, update their parent's retain_lsns
## Problem
In `test_basebackup_with_high_slru_count`, the pageserver is sometimes
mysteriously hanging on startup, having been started+stopped earlier in
the test setup while populating template tenant data.
- #7586
We can't see why this is hanging in this particular test. The test does
some weird stuff though, like attaching a load of broken tenants and
then doing a SIGQUIT kill of a pageserver.
## Summary of changes
- Attach tenants normally instead of doing a failpoint dance to attach
them as broken
- Shut the pageserver down gracefully during init instead of using
immediate mode
- Remove the "sequential" variant of the unstable test, as this is going
away soon anyway
- Log before trying to acquire lock file, so that if it hangs we have a
clearer sense of if that's really where it's hanging. It seems like it
is, but that code does a non-blocking flock so it's surprising.
## 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>
part of https://github.com/neondatabase/neon/issues/8002
The main thing in this pull request is the new `generate_key_retention`
function. It decides which deltas to retain and generate images for a
given key based on its history + retain_lsn + horizon.
On that, we generate a flat single level of delta layers over all deltas
included in the compaction. In the future, we can decide whether to
split them over the LSN axis as described in the RFC.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
Co-authored-by: Christian Schwarz <christian@neon.tech>
## Problem
Postgres is using `access()` function in `GetNewRelFileNumber` to check
if assigned relfilenumber is not used for any other relation. This check
will not work in Neon, because we do not have all files in local
storage.
## Summary of changes
Use smgrexists() instead which will check at page server if such
relfilenode is used.
## 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
As described in https://github.com/neondatabase/neon/issues/8398, layer
visibility is a new hint that will help us manage disk space more
efficiently.
## Summary of changes
- Introduce LayerVisibilityHint and store it as part of access stats
- Automatically mark a layer visible if it is accessed, or when it is
created.
The impact on the access stats size will be reversed in
https://github.com/neondatabase/neon/pull/8431
This is functionally a no-op change: subsequent PRs will add the logic
that sets layers to Covered, and which uses the layer visibility as an
input to eviction and heatmap generation.
---------
Co-authored-by: Joonas Koivunen <joonas@neon.tech>
## Problem
This test sometimes found that ancestors were getting cleaned up before
it had done any compaction.
Compaction was happening implicitly via Workload.
Example:
https://neon-github-public-dev.s3.amazonaws.com/reports/pr-8298/10032173390/index.html#testresult/fb04786402f80822/retries
## Summary of changes
- Set upload=False when writing data after shard split, to avoid doing a
checkpoint
- Add a checkpoint_period & explicit wait for uploads so that we ensure
data lands in S3 without doing a checkpoint
## Motivation & Context
We want to move away from `task_mgr` towards explicit tracking of child
tasks.
This PR is extracted from https://github.com/neondatabase/neon/pull/8339
where I refactor `PageRequestHandler` to not depend on task_mgr anymore.
## Changes
This PR refactors all global tasks but `PageRequestHandler` to use some
combination of `JoinHandle`/`JoinSet` + `CancellationToken`.
The `task_mgr::spawn(.., shutdown_process_on_error)` functionality is
preserved through the new `exit_on_panic_or_error` wrapper.
Some global tasks were not using it before, but as of this PR, they are.
The rationale is that all global tasks are relevant for correct
operation of the overall Neon system in one way or another.
## Future Work
After #8339, we can make `task_mgr::spawn` require a `TenantId` instead
of an `Option<TenantId>` which concludes this step of cleanup work and
will help discourage future usage of task_mgr for global tasks.
Part of #8128.
## Problem
Scrubber uses `scan_metadata` command to flag metadata inconsistencies.
To trust it at scale, we need to make sure the errors we emit is a
reflection of real scenario. One check performed in the scrubber is to
see whether layers listed in the latest `index_part.json` is present in
object listing. Currently, the scrubber does not robustly handle the
case where objects are uploaded/deleted during the scan.
## Summary of changes
**Condition for success:** An object in the index is (1) in the object
listing we acquire from S3 or (2) found in a HeadObject request (new
object).
- Add in the `HeadObject` requests for the layers missing from the
object listing.
- Keep the order of first getting the object listing and then
downloading the layers.
- Update check to only consider shards with highest shard count.
- Skip analyzing a timeline if `deleted_at` tombstone is marked in
`index_part.json`.
- Add new test to see if scrubber actually detect the metadata
inconsistency.
_Misc_
- A timeline with no ancestor should always have some layers.
- Removed experimental histograms
_Caveat_
- Ancestor layer is not cleaned until #8308 is implemented. If ancestor
layers reference non-existing layers in the index, the scrubber will
emit false positives.
Signed-off-by: Yuchen Liang <yuchen@neon.tech>
## Problem
Deployed pageserver configurations are all like this:
```
disk_usage_based_eviction:
max_usage_pct: 85
min_avail_bytes: 0
period: "10s"
eviction_order:
type: "RelativeAccessed"
args:
highest_layer_count_loses_first: true
```
But we're maintaining this optional absolute order eviction, with test
cases etc.
## Summary of changes
- Remove absolute order eviction. Make the default eviction policy the
same as how we really deploy pageservers.
PR #8299 has switched the storage scrubber to use
`DefaultCredentialsChain`. Now we do this for `remote_storage`, as it
allows us to use `remote_storage` from inside kubernetes. Most of the
diff is due to `GenericRemoteStorage::from_config` becoming `async fn`.
This adds an archival_config endpoint to the pageserver. Currently it
has no effect, and always "works", but later the intent is that it will
make a timeline archived/unarchived.
- [x] add yml spec
- [x] add endpoint handler
Part of https://github.com/neondatabase/neon/issues/8088
## Problem
There are some swagger errors in `pageserver/src/http/openapi_spec.yml`
```
Error 431 15000 Object includes not allowed fields
Error 569 3100401 should always have a 'required'
Error 569 15000 Object includes not allowed fields
Error 1111 10037 properties members must be schemas
```
## Summary of changes
Fixed the above errors.
## Problem
After a shard split, the pageserver leaves the ancestor shard's content
in place. It may be referenced by child shards, but eventually child
shards will de-reference most ancestor layers as they write their own
data and do GC. We would like to eventually clean up those ancestor
layers to reclaim space.
## Summary of changes
- Extend the physical GC command with `--mode=full`, which includes
cleaning up unreferenced ancestor shard layers
- Add test `test_scrubber_physical_gc_ancestors`
- Remove colored log output: in testing this is irritating ANSI code
spam in logs, and in interactive use doesn't add much.
- Refactor storage controller API client code out of storcon_client into
a `storage_controller/client` crate
- During physical GC of ancestors, call into the storage controller to
check that the latest shards seen in S3 reflect the latest state of the
tenant, and there is no shard split in progress.
We're removing the usage of this long-meaningless config field in
https://github.com/neondatabase/aws/pull/1599
Once that PR has been deployed to staging and prod, we can merge this
PR.
Successor of #8288 , just enable zstd in tests. Also adds a test that
creates easily compressable data.
Part of #5431
---------
Co-authored-by: John Spray <john@neon.tech>
Co-authored-by: Joonas Koivunen <joonas@neon.tech>
Use the k-merge iterator in the compaction process to reduce memory
footprint.
part of https://github.com/neondatabase/neon/issues/8002
## Summary of changes
* refactor the bottom-most compaction code to use k-merge iterator
* add Send bound on some structs as it is used across the await points
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
Co-authored-by: Arpad Müller <arpad-m@users.noreply.github.com>
## Problem
We lack insight into:
- How much of a tenant's physical size is image vs. delta layers
- Average sizes of image vs. delta layers
- Total layer counts per timeline, indicating size of index_part object
As well as general observability love, this is motivated by
https://github.com/neondatabase/neon/issues/6738, where we need to
define some sensible thresholds for storage amplification, and using
total physical size may not work well (if someone does a lot of DROPs
then it's legitimate for the physical-synthetic ratio to be huge), but
the ratio between image layer size and delta layer size may be a better
indicator of whether we're generating unreasonable quantities of image
layers.
## Summary of changes
- Add pageserver_layer_bytes and pageserver_layer_count metrics,
labelled by timeline and `kind` (delta or image)
- Add & subtract these with LayerInner's lifetime.
I'm intentionally avoiding using a generic metric RAII guard object, to
avoid bloating LayerInner: it already has all the information it needs
to update metric on new+drop.
Existing tenants and some selection of layers might produce duplicated
keys. Add tests to ensure the k-merge iterator handles it correctly. We
also enforced ordering of the k-merge iterator to put images before
deltas.
part of https://github.com/neondatabase/neon/issues/8002
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
Co-authored-by: Arpad Müller <arpad-m@users.noreply.github.com>
## Problem
ValueRef is an unnecessarily large structure, because it carries a
cursor. L0 compaction currently instantiates gigabytes of these under
some circumstances.
## Summary of changes
- Carry a ref to the parent layer instead of a cursor, and construct a
cursor on demand.
This reduces RSS high watermark during L0 compaction by about 20%.
