Part of #7497
## Problem
Static computes pinned at some fix LSN could be created initially within
PITR interval but eventually go out it. To make sure that Static
computes are not affected by GC, we need to start using the LSN lease
API (introduced in #8084) in compute_ctl.
## Summary of changes
**compute_ctl**
- Spawn a thread for when a static compute starts to periodically ping
pageserver(s) to make LSN lease requests.
- Add `test_readonly_node_gc` to test if static compute can read all
pages without error.
- (test will fail on main without the code change here)
**page_service**
- `wait_or_get_last_lsn` will now allow `request_lsn` less than
`latest_gc_cutoff_lsn` to proceed if there is a lease on `request_lsn`.
Signed-off-by: Yuchen Liang <yuchen@neon.tech>
Co-authored-by: Alexey Kondratov <kondratov.aleksey@gmail.com>
Part of [Epic: Bypass PageCache for user data
blocks](https://github.com/neondatabase/neon/issues/7386).
# Problem
`InMemoryLayer` still uses the `PageCache` for all data stored in the
`VirtualFile` that underlies the `EphemeralFile`.
# Background
Before this PR, `EphemeralFile` is a fancy and (code-bloated) buffered
writer around a `VirtualFile` that supports `blob_io`.
The `InMemoryLayerInner::index` stores offsets into the `EphemeralFile`.
At those offset, we find a varint length followed by the serialized
`Value`.
Vectored reads (`get_values_reconstruct_data`) are not in fact vectored
- each `Value` that needs to be read is read sequentially.
The `will_init` bit of information which we use to early-exit the
`get_values_reconstruct_data` for a given key is stored in the
serialized `Value`, meaning we have to read & deserialize the `Value`
from the `EphemeralFile`.
The L0 flushing **also** needs to re-determine the `will_init` bit of
information, by deserializing each value during L0 flush.
# Changes
1. Store the value length and `will_init` information in the
`InMemoryLayer::index`. The `EphemeralFile` thus only needs to store the
values.
2. For `get_values_reconstruct_data`:
- Use the in-memory `index` figures out which values need to be read.
Having the `will_init` stored in the index enables us to do that.
- View the EphemeralFile as a byte array of "DIO chunks", each 512 bytes
in size (adjustable constant). A "DIO chunk" is the minimal unit that we
can read under direct IO.
- Figure out which chunks need to be read to retrieve the serialized
bytes for thes values we need to read.
- Coalesce chunk reads such that each DIO chunk is only read once to
serve all value reads that need data from that chunk.
- Merge adjacent chunk reads into larger
`EphemeralFile::read_exact_at_eof_ok` of up to 128k (adjustable
constant).
3. The new `EphemeralFile::read_exact_at_eof_ok` fills the IO buffer
from the underlying VirtualFile and/or its in-memory buffer.
4. The L0 flush code is changed to use the `index` directly, `blob_io`
5. We can remove the `ephemeral_file::page_caching` construct now.
The `get_values_reconstruct_data` changes seem like a bit overkill but
they are necessary so we issue the equivalent amount of read system
calls compared to before this PR where it was highly likely that even if
the first PageCache access was a miss, remaining reads within the same
`get_values_reconstruct_data` call from the same `EphemeralFile` page
were a hit.
The "DIO chunk" stuff is truly unnecessary for page cache bypass, but,
since we're working on [direct
IO](https://github.com/neondatabase/neon/issues/8130) and
https://github.com/neondatabase/neon/issues/8719 specifically, we need
to do _something_ like this anyways in the near future.
# Alternative Design
The original plan was to use the `vectored_blob_io` code it relies on
the invariant of Delta&Image layers that `index order == values order`.
Further, `vectored_blob_io` code's strategy for merging IOs is limited
to adjacent reads. However, with direct IO, there is another level of
merging that should be done, specifically, if multiple reads map to the
same "DIO chunk" (=alignment-requirement-sized and -aligned region of
the file), then it's "free" to read the chunk into an IO buffer and
serve the two reads from that buffer.
=> https://github.com/neondatabase/neon/issues/8719
# Testing / Performance
Correctness of the IO merging code is ensured by unit tests.
Additionally, minimal tests are added for the `EphemeralFile`
implementation and the bit-packed `InMemoryLayerIndexValue`.
Performance testing results are presented below.
All pref testing done on my M2 MacBook Pro, running a Linux VM.
It's a release build without `--features testing`.
We see definitive improvement in ingest performance microbenchmark and
an ad-hoc microbenchmark for getpage against InMemoryLayer.
```
baseline: commit 7c74112b2a origin/main
HEAD: ef1c55c52e
```
<details>
```
cargo bench --bench bench_ingest -- 'ingest 128MB/100b seq, no delta'
baseline
ingest-small-values/ingest 128MB/100b seq, no delta
time: [483.50 ms 498.73 ms 522.53 ms]
thrpt: [244.96 MiB/s 256.65 MiB/s 264.73 MiB/s]
HEAD
ingest-small-values/ingest 128MB/100b seq, no delta
time: [479.22 ms 482.92 ms 487.35 ms]
thrpt: [262.64 MiB/s 265.06 MiB/s 267.10 MiB/s]
```
</details>
We don't have a micro-benchmark for InMemoryLayer and it's quite
cumbersome to add one. So, I did manual testing in `neon_local`.
<details>
```
./target/release/neon_local stop
rm -rf .neon
./target/release/neon_local init
./target/release/neon_local start
./target/release/neon_local tenant create --set-default
./target/release/neon_local endpoint create foo
./target/release/neon_local endpoint start foo
psql 'postgresql://cloud_admin@127.0.0.1:55432/postgres'
psql (13.16 (Debian 13.16-0+deb11u1), server 15.7)
CREATE TABLE wal_test (
id SERIAL PRIMARY KEY,
data TEXT
);
DO $$
DECLARE
i INTEGER := 1;
BEGIN
WHILE i <= 500000 LOOP
INSERT INTO wal_test (data) VALUES ('data');
i := i + 1;
END LOOP;
END $$;
-- => result is one L0 from initdb and one 137M-sized ephemeral-2
DO $$
DECLARE
i INTEGER := 1;
random_id INTEGER;
random_record wal_test%ROWTYPE;
start_time TIMESTAMP := clock_timestamp();
selects_completed INTEGER := 0;
min_id INTEGER := 1; -- Minimum ID value
max_id INTEGER := 100000; -- Maximum ID value, based on your insert range
iters INTEGER := 100000000; -- Number of iterations to run
BEGIN
WHILE i <= iters LOOP
-- Generate a random ID within the known range
random_id := min_id + floor(random() * (max_id - min_id + 1))::int;
-- Select the row with the generated random ID
SELECT * INTO random_record
FROM wal_test
WHERE id = random_id;
-- Increment the select counter
selects_completed := selects_completed + 1;
-- Check if a second has passed
IF EXTRACT(EPOCH FROM clock_timestamp() - start_time) >= 1 THEN
-- Print the number of selects completed in the last second
RAISE NOTICE 'Selects completed in last second: %', selects_completed;
-- Reset counters for the next second
selects_completed := 0;
start_time := clock_timestamp();
END IF;
-- Increment the loop counter
i := i + 1;
END LOOP;
END $$;
./target/release/neon_local stop
baseline: commit 7c74112b2a origin/main
NOTICE: Selects completed in last second: 1864
NOTICE: Selects completed in last second: 1850
NOTICE: Selects completed in last second: 1851
NOTICE: Selects completed in last second: 1918
NOTICE: Selects completed in last second: 1911
NOTICE: Selects completed in last second: 1879
NOTICE: Selects completed in last second: 1858
NOTICE: Selects completed in last second: 1827
NOTICE: Selects completed in last second: 1933
ours
NOTICE: Selects completed in last second: 1915
NOTICE: Selects completed in last second: 1928
NOTICE: Selects completed in last second: 1913
NOTICE: Selects completed in last second: 1932
NOTICE: Selects completed in last second: 1846
NOTICE: Selects completed in last second: 1955
NOTICE: Selects completed in last second: 1991
NOTICE: Selects completed in last second: 1973
```
NB: the ephemeral file sizes differ by ca 1MiB, ours being 1MiB smaller.
</details>
# Rollout
This PR changes the code in-place and is not gated by a feature flag.
## Problem
In order to build AZ aware scheduling, the storage controller needs to
know what AZ pageservers are in.
Related https://github.com/neondatabase/neon/issues/8848
## Summary of changes
This patch set adds a new nullable column to the `nodes` table:
`availability_zone_id`. The node registration
request is extended to include the AZ id (pageservers already have this
in their `metadata.json` file).
If the node is already registered, then we update the persistent and
in-memory state with the provided AZ.
Otherwise, we add the node with the AZ to begin with.
A couple assumptions are made here:
1. Pageserver AZ ids are stable
2. AZ ids do not change over time
Once all pageservers have a configured AZ, we can remove the optionals
in the code and make the database column not nullable.
Part of #8130, closes#8719.
## Problem
Currently, vectored blob io only coalesce blocks if they are immediately
adjacent to each other. When we switch to Direct IO, we need a way to
coalesce blobs that are within the dio-aligned boundary but has gap
between them.
## Summary of changes
- Introduces a `VectoredReadCoalesceMode` for `VectoredReadPlanner` and
`StreamingVectoredReadPlanner` which has two modes:
- `AdjacentOnly` (current implementation)
- `Chunked(<alignment requirement>)`
- New `ChunkedVectorBuilder` that considers batching `dio-align`-sized
read, the start and end of the vectored read will respect
`stx_dio_offset_align` / `stx_dio_mem_align` (`vectored_read.start` and
`vectored_read.blobs_at.first().start_offset` will be two different
value).
- Since we break the assumption that blobs within single `VectoredRead`
are next to each other (implicit end offset), we start to store blob end
offsets in the `VectoredRead`.
- Adapted existing tests to run in both `VectoredReadCoalesceMode`.
- The io alignment can also be live configured at runtime.
Signed-off-by: Yuchen Liang <yuchen@neon.tech>
Protocol version 2 has been the default for a while now, and we no
longer have any computes running in production that used protocol
version 1. This completes the migration by removing support for v1 in
both the pageserver and the compute.
See issue #6211.
Part of #8002, the final big PR in the batch.
## Summary of changes
This pull request uses the new split layer writer in the gc-compaction.
* It changes how layers are split. Previously, we split layers based on
the original split point, but this creates too many layers
(test_gc_feedback has one key per layer).
* Therefore, we first verify if the layer map can be processed by the
current algorithm (See https://github.com/neondatabase/neon/pull/8191,
it's basically the same check)
* On that, we proceed with the compaction. This way, it creates a large
enough layer close to the target layer size.
* Added a new set of functions `with_discard` in the split layer writer.
This helps us skip layers if we are going to produce the same persistent
key.
* The delta writer will keep the updates of the same key in a single
file. This might create a super large layer, but we can optimize it
later.
* The split layer writer is used in the gc-compaction algorithm, and it
will split layers based on size.
* Fix the image layer summary block encoded the wrong key range.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
Co-authored-by: Arpad Müller <arpad-m@users.noreply.github.com>
Co-authored-by: Christian Schwarz <christian@neon.tech>
refs https://github.com/neondatabase/neon/issues/6989
Problem
-------
After unclean shutdown, we get restarted, start reading the local
filesystem,
and make decisions based on those reads. However, some of the data might
have
not yet been fsynced when the unclean shutdown completed.
Durability matters even though Pageservers are conceptually just a cache
of state in S3. For example:
- the cloud control plane is no control loop => pageserver responses
to tenant attachmentm, etc, needs to be durable.
- the storage controller does not rely on this (as much?)
- we don't have layer file checksumming, so, downloaded+renamed but not
fsynced layer files are technically not to be trusted
- https://github.com/neondatabase/neon/issues/2683
Solution
--------
`syncfs` the tenants directory during startup, before we start reading
from it.
This is a bit overkill because we do remove some temp files
(InMemoryLayer!)
later during startup. Further, these temp files are particularly likely
to
be dirty in the kernel page cache. However, we don't want to refactor
that
cleanup code right now, and the dirty data on pageservers is generally
not that high. Last, with [direct
IO](https://github.com/neondatabase/neon/issues/8130) we're going to
have near-zero kernel page cache anyway quite soon.
This PR:
* Implements the rule that archived timelines require all of their
children to be archived as well, as specified in the RFC. There is no
fancy locking mechanism though, so the precondition can still be broken.
As a TODO for later, we still allow unarchiving timelines with archived
parents.
* Adds an `is_archived` flag to `TimelineInfo`
* Adds timeline_archival_config to `PageserverHttpClient`
* Adds a new `test_timeline_archive` test, loosely based on
`test_timeline_delete`
Part of #8088
## Problem
Previously, the controller only used the shard counts for scheduling.
This works well when hosting only many-sharded tenants, but works much
less well when hosting single-sharded tenants that have a greater
deviation in size-per-shard.
Closes: https://github.com/neondatabase/neon/issues/7798
## Summary of changes
- Instead of UtilizationScore, carry the full PageserverUtilization
through into the Scheduler.
- Use the PageserverUtilization::score() instead of shard count when
ordering nodes in scheduling.
Q: Why did test_sharding_split_smoke need updating in this PR?
A: There's an interesting side effect during shard splits: because we do
not decrement the shard count in the utilization when we de-schedule the
shards from before the split, the controller will now prefer to pick
_different_ nodes for shards compared with which ones held secondaries
before the split. We could use our knowledge of splitting to fix up the
utilizations more actively in this situation, but I'm leaning toward
leaving the code simpler, as in practical systems the impact of one
shard on the utilization of a node should be fairly low (single digit
%).
In case of corrupted delta layers, we can detect the corruption and bail
out the compaction.
## Summary of changes
* Detect wrong delta desc of key range
* Detect unordered deltas
Signed-off-by: Alex Chi Z <chi@neon.tech>
close https://github.com/neondatabase/neon/issues/8579
## Summary of changes
The `is_l0` check now takes both layer key range and the layer type.
This allows us to have image layers covering the full key range in
btm-most compaction (upcoming PR). However, we still don't allow delta
layers to cover the full key range, and I will make btm-most compaction
to generate delta layers with the key range of the keys existing in the
layer instead of `Key::MIN..Key::HACK_MAX` (upcoming PR).
Signed-off-by: Alex Chi Z <chi@neon.tech>
part of https://github.com/neondatabase/neon/issues/8623
We want to discover potential aux v1 customers that we might have missed
from the migrations.
## Summary of changes
Log warnings on basebackup, load timeline, and the first put_file.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem/Solution
TimelineWriter::put_batch is simply a loop over individual puts. Each
put acquires and releases locks, and checks for potentially starting a
new layer. Batching these is more efficient, but more importantly
unlocks future changes where we can pre-build serialized buffers much
earlier in the ingest process, potentially even on the safekeeper
(imagine a future model where some variant of DatadirModification lives
on the safekeeper).
Ensuring that the values in put_batch are written to one layer also
enables a simplification upstream, where we no longer need to write
values in LSN-order. This saves us a sort, but also simplifies follow-on
refactors to DatadirModification: we can store metadata keys and data
keys separately at that level without needing to zip them together in
LSN order later.
## Why?
In this PR, these changes are simplify optimizations, but they are
motivated by evolving the ingest path in the direction of disentangling
extracting DatadirModification from Timeline. It may not obvious how
right now, but the general idea is that we'll end up with three phases
of ingest:
- A) Decode walrecords and build a datadirmodification with all the
simple data contents already in a big serialized buffer ready to write
to an ephemeral layer **<-- this part can be pipelined and parallelized,
and done on a safekeeper!**
- B) Let that datadirmodification see a Timeline, so that it can also
generate all the metadata updates that require a read-modify-write of
existing pages
- C) Dump the results of B into an ephemeral layer.
Related: https://github.com/neondatabase/neon/issues/8452
## Caveats
Doing a big monolithic buffer of values to write to disk is ordinarily
an anti-pattern: we prefer nice streaming I/O. However:
- In future, when we do this first decode stage on the safekeeper, it
would be inefficient to serialize a Vec of Value, and then later
deserialize it just to add blob size headers while writing into the
ephemeral layer format. The idea is that for bulk write data, we will
serialize exactly once.
- The monolithic buffer is a stepping stone to pipelining more of this:
by seriailizing earlier (rather than at the final put_value), we will be
able to parallelize the wal decoding and bulk serialization of data page
writes.
- The ephemeral layer's buffered writer already stalls writes while it
waits to flush: so while yes we'll stall for a couple milliseconds to
write a couple megabytes, we already have stalls like this, just
distributed across smaller writes.
## Benchmarks
This PR is primarily a stepping stone to safekeeper ingest filtering,
but also provides a modest efficiency improvement to the `wal_recovery`
part of `test_bulk_ingest`.
test_bulk_ingest:
```
test_bulk_insert[neon-release-pg16].insert: 23.659 s
test_bulk_insert[neon-release-pg16].pageserver_writes: 5,428 MB
test_bulk_insert[neon-release-pg16].peak_mem: 626 MB
test_bulk_insert[neon-release-pg16].size: 0 MB
test_bulk_insert[neon-release-pg16].data_uploaded: 1,922 MB
test_bulk_insert[neon-release-pg16].num_files_uploaded: 8
test_bulk_insert[neon-release-pg16].wal_written: 1,382 MB
test_bulk_insert[neon-release-pg16].wal_recovery: 18.981 s
test_bulk_insert[neon-release-pg16].compaction: 0.055 s
vs. tip of main:
test_bulk_insert[neon-release-pg16].insert: 24.001 s
test_bulk_insert[neon-release-pg16].pageserver_writes: 5,428 MB
test_bulk_insert[neon-release-pg16].peak_mem: 604 MB
test_bulk_insert[neon-release-pg16].size: 0 MB
test_bulk_insert[neon-release-pg16].data_uploaded: 1,922 MB
test_bulk_insert[neon-release-pg16].num_files_uploaded: 8
test_bulk_insert[neon-release-pg16].wal_written: 1,382 MB
test_bulk_insert[neon-release-pg16].wal_recovery: 23.586 s
test_bulk_insert[neon-release-pg16].compaction: 0.054 s
```
close https://github.com/neondatabase/neon/issues/8558
* Directly generate image layers for sparse keyspaces during initdb
optimization.
* Support force image layer generation for sparse keyspaces.
* Fix a bug of incorrect image layer key range in case of duplicated
keys. (The added line: `start = img_range.end;`) This can cause
overlapping image layers and keys to disappear.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
After #8655, we needed to mark some tests to shut down immediately. To
aid these tests, try the new pattern of `flush_ep_to_pageserver`
followed by a non-compacting checkpoint. This moves the general graceful
shutdown problem of having too much to flush at shutdown into the test.
Also, add logging for how long the graceful shutdown took, if we got to
complete it for faster log eyeballing.
Fixes: #8712
Cc: #8715, #8708
## Problem
Compaction jobs and other background loops are concurrency-limited
through a global semaphore.
The current counters allow quantifying how _many_ tasks are waiting.
But there is no way to tell how _much_ delay is added by the semaphore.
So, add a counter that aggregates the wall clock time seconds spent
acquiring the semaphore.
The metrics can be used as follows:
* retroactively calculate average acquisition time in a given time range
* compare the degree of background loop backlog among pageservers
The metric is insufficient to calculate
* run-up of ongoing acquisitions that haven't finished acquiring yet
* Not easily feasible because ["Cancelling a call to acquire makes you
lose your place in the
queue"](https://docs.rs/tokio/latest/tokio/sync/struct.Semaphore.html#method.acquire)
## Summary of changes
* Refactor the metrics to follow the current best practice for typed
metrics in `metrics.rs`.
* Add the new counter.
## Problem
We don't have a convenient way for a human to ask "how far are secondary
downloads along for this tenant".
This is useful when driving migrations of tenants to the storage
controller, as we first create a secondary location and want to see it
warm up before we cut over. That can already be done via storcon_cli,
but we would like a way that doesn't require direct API access.
## Summary of changes
Add a metric that reports to total size of layers in the heatmap: this
may be used in conjunction with the existing
`pageserver_secondary_resident_physical_size` to estimate "warmth" of
the secondary location.
## Problem
The default Postgres version is set to 15 in code, while we use 16 in
most of the other places (and Postgres 17 is coming)
## Summary of changes
- Run `benchmarks` job with Postgres 16 (instead of Postgres 14)
- Set `DEFAULT_PG_VERSION` to 16 in all places
- Remove deprecated `--pg-version` pytest argument
- Update `test_metadata_bincode_serde_ensure_roundtrip` for Postgres 16
It's been rolled out everywhere, no configs are referencing it.
All code that's made dead by the removal of the config option is removed
as part of this PR.
The `page_caching::PreWarmingWriter` in `::No` mode is equivalent to a
`size_tracking_writer`, so, use that.
part of https://github.com/neondatabase/neon/issues/7418
After the rollout has succeeded, we now set the default image
compression to be enabled.
We also remove its explicit mention from `neon_fixtures.py` added in
#8368 as it is now the default (and we switch to `zstd(1)` which is a
bit nicer on CPU time).
Part of https://github.com/neondatabase/neon/issues/5431
## Problem
When a secondary location is trying to catch up while a tenant is
receiving new writes, it can become quite wasteful:
- Downloading L0s which are soon destroyed by compaction to L1s
- Downloading older layer files which are soon made irrelevant when
covered by image layers.
## Summary of changes
Sort the layer files in the heatmap:
- L0 layers are the lowest priority
- Other layers are sorted to download the highest LSNs first.
## Problem
On macOS, clippy fails with the following error:
```
error: unused import: `crate::virtual_file::owned_buffers_io::io_buf_ext::IoBufExt`
--> pageserver/src/tenant/remote_timeline_client/download.rs:26:5
|
26 | use crate::virtual_file::owned_buffers_io::io_buf_ext::IoBufExt;
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
= note: `-D unused-imports` implied by `-D warnings`
= help: to override `-D warnings` add `#[allow(unused_imports)]`
```
Introduced in https://github.com/neondatabase/neon/pull/8717
## Summary of changes
- allow `unused_imports` for
`crate::virtual_file::owned_buffers_io::io_buf_ext::IoBufExt` on macOS
in download.rs
The `tokio_epoll_uring::Slice` / `tokio_uring::Slice` type is weird.
The new `FullSlice` newtype is better. See the doc comment for details.
The naming is not ideal, but we'll clean that up in a future refactoring
where we move the `FullSlice` into `tokio_epoll_uring`. Then, we'll do
the following:
* tokio_epoll_uring::Slice is removed
* `FullSlice` becomes `tokio_epoll_uring::IoBufView`
* new type `tokio_epoll_uring::IoBufMutView` for the current
`tokio_epoll_uring::Slice<IoBufMut>`
Context
-------
I did this work in preparation for
https://github.com/neondatabase/neon/pull/8537.
There, I'm changing the type that the `inmemory_layer.rs` passes to
`DeltaLayerWriter::put_value_bytes` and thus it seemed like a good
opportunity to make this cleanup first.
Some benchmarks and tests might still fail because of #8655 (tracked in
#8708) because we are not fast enough to shut down ([one evidence]).
Partially this is explained by the current validation mode of streaming
k-merge, but otherwise because that is where we use a lot of time in
compaction. Outside of L0 => L1 compaction, the image layer generation
is already guarded by vectored reads doing cancellation checks.
32768 is a wild guess based on looking how many keys we put in each
layer in a bench (1-2 million), but I assume it will be good enough
divisor. Doing checks more often will start showing up as contention
which we cannot currently measure. Doing checks less often might be
reasonable.
[one evidence]:
https://neon-github-public-dev.s3.amazonaws.com/reports/main/10384136483/index.html#suites/9681106e61a1222669b9d22ab136d07b/96e6d53af234924/
Earlier PR: #8706.
We can get CompactionError::Other(Cancelled) via the error handling with
a few ways.
[evidence](https://neon-github-public-dev.s3.amazonaws.com/reports/pr-8655/10301613380/index.html#suites/cae012a1e6acdd9fdd8b81541972b6ce/653a33de17802bb1/).
Hopefully fix it by:
1. replace the `map_err` which hid the
`GetReadyAncestorError::Cancelled` with `From<GetReadyAncestorError> for
GetVectoredError` conversion
2. simplifying the code in pgdatadir_mapping to eliminate the token
anyhow wrapping for deserialization errors
3. stop wrapping GetVectoredError as anyhow errors
4. stop wrapping PageReconstructError as anyhow errors
Additionally, produce warnings if we treat any other error (as was legal
before this PR) as missing key.
Cc: #8708.
## Problem
When pageservers do compaction, they frequently create image layers that
make earlier layers un-needed for reads, but then keep those earlier
layers around for 24 hours waiting for time-based eviction to expire
them.
Now that we track layer visibility, we can use it as an input to
eviction, and avoid the 24 hour "disk bump" that happens around
pageserver restarts.
## Summary of changes
- During time-based eviction, if a layer is marked Covered, use the
eviction period as the threshold: i.e. these layers get to remain
resident for at least one iteration of the eviction loop, but then get
evicted. With current settings this means they get evicted after 1h
instead of 24h.
- During disk usage eviction, prioritized evicting covered layers above
all other layers.
Caveats:
- Using the period as the threshold for time based eviction in this case
is a bit of a hack, but it avoids adding yet another configuration
property, and in any case the value of a new property would be somewhat
arbitrary: there's no "right" length of time to keep covered layers
around just in case.
- We had previously planned on removing time-based eviction: this change
would motivate us to keep it around, but we can still simplify the code
later to just do the eviction of covered layers, rather than applying a
TTL policy to all layers.
With additional phases from #8430 the `detach_ancestor::Error` became
untenable. Split it up into phases, and introduce laundering for
remaining `anyhow::Error` to propagate them as most often
`Error::ShuttingDown`.
Additionally, complete FIXMEs.
Cc: #6994
## Problem
The storage scrubber was reporting warnings for lots of timelines like:
```
WARN Missed some shards at count ShardCount(0) tenant_id=25eb7a83d9a2f90ac0b765b6ca84cf4c
```
These were spurious: these tenants are fine. There was a bug in
accumulating the ShardIndex for each tenant, whereby multiple timelines
would lead us to add the same ShardIndex more than one.
Closes: #8646
## Summary of changes
- Accumulate ShardIndex in a BTreeSet instead of a Vec
- Extend the test to reproduce the issue
With the persistent gc blocking, we can now retry reparenting timelines
which had failed for whatever reason on the previous attempt(s).
Restructure the detach_ancestor into three phases:
- prepare (insert persistent gc blocking, copy lsn prefix, layers)
- detach and reparent
- reparenting can fail, so we might need to retry this portion
- complete (remove persistent gc blocking)
Cc: #6994
A few of the benchmarks have started failing after #8655 where they are
waiting for compactor task. Reads done by image layer creation should
already be cancellation sensitive because vectored get does a check each
time, but try sprinkling additional cancellation points to:
- each partition
- after each vectored read batch
## Problem
When the utilization API was added, it was just a stub with disk space
information.
Disk space information isn't a very good metric for assigning tenants to
pageservers, because pageservers making full use of their disks would
always just have 85% utilization, irrespective of how much pressure they
had for disk space.
## Summary of changes
- Use the new layer visibiilty metric to calculate a "wanted size" per
tenant, and sum these to get a total local disk space wanted per
pageserver. This acts as the primary signal for utilization.
- Also use the shard count to calculate a utilization score, and take
the max of this and the disk-driven utilization. The shard count limit
is currently set as a constant 20,000, which matches contemporary
operational practices when loading pageservers.
The shard count limit means that for tiny/empty tenants, on a machine
with 3.84TB disk, each tiny tenant influences the utilization score as
if it had size 160MB.
## Problem
Pageserver exposes some vectored get related configs which are not in
use.
## Summary of changes
Remove the following pageserver configs: get_impl, get_vectored_impl,
and `validate_get_vectored`.
They are not used in the pageserver since
https://github.com/neondatabase/neon/pull/8601.
Manual overrides have been removed from the aws repo in
https://github.com/neondatabase/aws/pull/1664.
## Problem
This follows a PR that insists all input keys are representable in 16
bytes:
- https://github.com/neondatabase/neon/pull/8648
& a PR that prevents postgres from sending us keys that use the high
bits of field2:
- https://github.com/neondatabase/neon/pull/8657
Motivation for this change:
1. Ingest is bottlenecked on CPU
2. InMemoryLayer can create huge (~1M value) BTreeMap<Key,_> for its
index.
3. Maps over i128 are much faster than maps over an arbitrary 18 byte
struct.
It may still be worthwhile to make the index two-tier to optimize for
the case where only the last 4 bytes (blkno) of the key vary frequently,
but simply using the i128 representation of keys has a big impact for
very little effort.
Related: #8452
## Summary of changes
- Introduce `CompactKey` type which contains an i128
- Use this instead of Key in InMemoryLayer's index, converting back and
forth as needed.
## Performance
All the small-value `bench_ingest` cases show improved throughput.
The one that exercises this index most directly shows a 35% throughput
increase:
```
ingest-small-values/ingest 128MB/100b seq, no delta
time: [374.29 ms 378.56 ms 383.38 ms]
thrpt: [333.88 MiB/s 338.13 MiB/s 341.98 MiB/s]
change:
time: [-26.993% -26.117% -25.111%] (p = 0.00 < 0.05)
thrpt: [+33.531% +35.349% +36.974%]
Performance has improved.
```
It should give us all possible allowed_errors more consistently.
While getting the workflows to pass on
https://github.com/neondatabase/neon/pull/8632 it was noticed that
allowed_errors are rarely hit (1/4). This made me realize that we always
do an immediate stop by default. Doing a graceful shutdown would had
made the draining more apparent and likely we would not have needed the
#8632 hotfix.
Downside of doing this is that we will see more timeouts if tests are
randomly leaving pause failpoints which fail the shutdown.
The net outcome should however be positive, we could even detect too
slow shutdowns caused by a bug or deadlock.
## Problem
Migrations of tenant shards with cold secondaries are holding up drains
in during production deployments.
## Summary of changes
If a secondary locations is lagging by more than 256MiB (configurable,
but that's the default), then skip cutting it over to the secondary as part of the node drain.
## Problem
This type of error can happen during shutdown & was triggering a circuit
breaker alert.
## Summary of changes
- Map NotIntialized::Stopped to CompactionError::ShuttingDown, so that
we may handle it cleanly
## Problem
This code was to mitigate risk in
https://github.com/neondatabase/neon/pull/8427
As expected, we did not hit this code path - the new continuous updates
of gc_info are working fine, we can remove this code now.
## Summary of changes
- Remove block that double-checks retain_lsns
avoid "leaking" the completions of BackgroundPurges by:
1. switching it to TaskTracker for provided close+wait
2. stop using tokio::fs::remove_dir_all which will consume two units of
memory instead of one blocking task
Additionally, use more graceful shutdown in tests which do actually some
background cleanup.
## Problem
Some developers build on MacOS, which doesn't have io_uring.
## Summary of changes
- Add `io_engine_for_bench`, which on linux will give io_uring or panic
if it's unavailable, and on MacOS will always panic.
We do not want to run such benchmarks with StdFs: the results aren't
interesting, and will actively waste the time of any developers who
start investigating performance before they realize they're using a
known-slow I/O backend.
Why not just conditionally compile this benchmark on linux only? Because
even on linux, I still want it to refuse to run if it can't get
io_uring.
Part of #8130, [RFC: Direct IO For Pageserver](https://github.com/neondatabase/neon/blob/problame/direct-io-rfc/docs/rfcs/034-direct-io-for-pageserver.md)
## Description
Add pageserver config for evaluating/enabling direct I/O.
- Disabled: current default, uses buffered io as is.
- Evaluate: still uses buffered io, but could do alignment checking and
perf simulation (pad latency by direct io RW to a fake file).
- Enabled: uses direct io, behavior on alignment error is configurable.
Signed-off-by: Yuchen Liang <yuchen@neon.tech>
We've noticed increased memory usage with the latest release. Drain the
joinset of `page_service` connection handlers to avoid leaking them
until shutdown. An alternative would be to use a TaskTracker.
TaskTracker was not discussed in original PR #8339 review, so not hot
fixing it in here either.
Earlier I was thinking we'd need a (ancestor_lsn, timeline_id) ordered
list of reparented. Turns out we did not need it at all. Replace it with
an unordered hashset. Additionally refactor the reparented direct
children query out, it will later be used from more places.
Split off from #8430.
Cc: #6994
Ephemeral files cleanup on drop but did not delay shutdown, leading to
problems with restarting the tenant. The solution is as proposed:
- make ephemeral files carry the gate guard to delay `Timeline::gate`
closing
- flush in-memory layers and strong references to those on
`Timeline::shutdown`
The above are realized by making LayerManager an `enum` with `Open` and
`Closed` variants, and fail requests to modify `LayerMap`.
Additionally:
- fix too eager anyhow conversions in compaction
- unify how we freeze layers and handle errors
- optimize likely_resident_layers to read LayerFileManager hashmap
values instead of bouncing through LayerMap
Fixes: #7830
