Including, but not limited to:
* Fixes to neon management code to support walproposer-as-an-extension
* Fix issue in expected output of pg settings serialization.
* Show the logs of a failed --sync-safekeepers process in CI
* Add compat layer for renamed GUCs in postgres.conf
* Update vendor/postgres to the latest origin/main
* Do not create initial tenant and timeline (adjust Python tests for that)
* Rework config handling during init, add --update-config to manage local config updates
This patch makes walreceiver logic more complicated, but it should work better in most cases. Added `test_wal_lagging` to test scenarios where alive safekeepers can lag behind other alive safekeepers.
- There was a bug which looks like `etcd_info.timeline.commit_lsn > Some(self.local_timeline.get_last_record_lsn())` filtered all safekeepers in some strange cases. I removed this filter, it should probably help with #2237
- Now walreceiver_connection reports status, including commit_lsn. This allows keeping safekeeper connection even when etcd is down.
- Safekeeper connection now fails if pageserver doesn't receive safekeeper messages for some time. Usually safekeeper sends messages at least once per second.
- `LaggingWal` check now uses `commit_lsn` directly from safekeeper. This fixes the issue with often reconnects, when compute generates WAL really fast.
- `NoWalTimeout` is rewritten to trigger only when we know about the new WAL and the connected safekeeper doesn't stream any WAL. This allows setting a small `lagging_wal_timeout` because it will trigger only when we observe that the connected safekeeper has stuck.
The new format has a few benefits: it's shorter, simpler and
human-readable as well. We don't use base64 anymore, since
url encoding got us covered.
We also show a better error in case we couldn't parse the
payload; the users should know it's all about passing the
correct project name.
This test failed consistently on `main` now. It's better to temporarily disable it to avoid blocking others' PRs while investigating the root cause for the test failure.
See: #2255, #2256
Resolves#2212.
- use `wait_for_last_flush_lsn` in `test_timeline_physical_size_*` tests
## Context
Need to wait for the pageserver to catch up with the compute's last flush LSN because during the timeline physical size API call, it's possible that there are running `LayerFlushThread` threads. These threads flush new layers into disk and hence update the physical size. This results in a mismatch between the physical size reported by the API and the actual physical size on disk.
### Note
The `LayerFlushThread` threads are processed **concurrently**, so it's possible that the above error still persists even with this patch. However, making the tests wait to finish processing all the WALs (not flushing) before calculating the physical size should help reduce the "flakiness" significantly
Resolves#2097
- use timeline modification's `lsn` and timeline's `last_record_lsn` to determine the corresponding LSN to query data in `DatadirModification::get`
- update `test_import_from_pageserver`. Split the test into 2 variants: `small` and `multisegment`.
+ `small` is the old test
+ `multisegment` is to simulate #2097 by using a larger number of inserted rows to create multiple segment files of a relation. `multisegment` is configured to only run with a `release` build
To flush inmemory layer eventually when no new data arrives, which helps
safekeepers to suspend activity (stop pushing to the broker). Default 10m should
be ok.
This script can be used to migrate a tenant across breaking storage versions, or (in the future) upgrading postgres versions. See the comment at the top for an overview.
Co-authored-by: Anastasia Lubennikova <anastasia@neon.tech>
Newer version of mypy fixes buggy error when trying to update only boto3 stubs.
However it brings new checks and starts to yell when we index into
cusror.fetchone without checking for None first. So this introduces a wrapper
to simplify quering for scalar values. I tried to use cursor_factory connection
argument but without success. There can be a better way to do that,
but this looks the simplest
Move all the fields that were returned by the wal_receiver endpoint into
timeline_detail. Internally, move those fields from the separate global
WAL_RECEIVERS hash into the LayeredTimeline struct. That way, all the
information about a timeline is kept in one place.
In the passing, I noted that the 'thread_id' field was removed from
WalReceiverEntry in commit e5cb727572, but it forgot to update
openapi_spec.yml. This commit removes that too.
What the WAL receiver really connects to is the safekeeper. The
"producer" term is a bit misleading, as the safekeeper doesn't produce
the WAL, the compute node does.
This change also applies to the name of the field used in the mgmt API
in in the response of the
'/v1/tenant/:tenant_id/timeline/:timeline_id/wal_receiver' endpoint.
AFAICS that's not used anywhere else than one python test, so it
should be OK to change it.
Ref #1902.
- Track the layered timeline's `physical_size` using `pageserver_current_physical_size` metric when updating the layer map.
- Report the local timeline's `physical_size` in timeline GET APIs.
- Add `include-non-incremental-physical-size` URL flag to also report the local timeline's `physical_size_non_incremental` (similar to `logical_size_non_incremental`)
- Add a `UIntGaugeVec` and `UIntGauge` to represent `u64` prometheus metrics
Co-authored-by: Dmitry Rodionov <dmitry@neon.tech>
[proxy] Add the `password hack` authentication flow
This lets us authenticate users which can use neither
SNI (due to old libpq) nor connection string `options`
(due to restrictions in other client libraries).
Note: `PasswordHack` will accept passwords which are not
encoded in base64 via the "password" field. The assumption
is that most user passwords will be valid utf-8 strings,
and the rest may still be passed via "password_".
## Overview
This patch reduces the number of memory allocations when running the page server under a heavy write workload. This mostly helps improve the speed of WAL record ingestion.
## Changes
- modified `DatadirModification` to allow reuse the struct's allocated memory after each modification
- modified `decode_wal_record` to allow passing a `DecodedWALRecord` reference. This helps reuse the struct in each `decode_wal_record` call
- added a reusable buffer for serializing object inside the `InMemoryLayer::put_value` function
- added a performance test simulating a heavy write workload for testing the changes in this patch
### Semi-related changes
- remove redundant serializations when calling `DeltaLayer::put_value` during `InMemoryLayer::write_to_disk` function call [1]
- removed the info span `info_span!("processing record", lsn = %lsn)` during each WAL ingestion [2]
## Notes
- [1]: in `InMemoryLayer::write_to_disk`, a deserialization is called
```
let val = Value::des(&buf)?;
delta_layer_writer.put_value(key, *lsn, val)?;
```
`DeltaLayer::put_value` then creates a serialization based on the previous deserialization
```
let off = self.blob_writer.write_blob(&Value::ser(&val)?)?;
```
- [2]: related: https://github.com/neondatabase/neon/issues/733
* More precisely control size of inmem layer
* Force recompaction of L0 layers if them contains large non-wallogged BLOBs to avoid too large layers
* Add modified version of test_hot_update test (test_dup_key.py) which should generate large layers without large number of tables
* Change test name in test_dup_key
* Add Layer::get_max_key_range function
* Add layer::key_iter method and implement new approach of splitting layers during compaction based on total size of all key values
* Add test_large_schema test for checking layer file size after compaction
* Make clippy happy
* Restore checking LSN distance threshold for checkpoint in-memory layer
* Optimize stoage keys iterator
* Update pageserver/src/layered_repository.rs
Co-authored-by: Heikki Linnakangas <heikki@zenith.tech>
* Update pageserver/src/layered_repository.rs
Co-authored-by: Heikki Linnakangas <heikki@zenith.tech>
* Update pageserver/src/layered_repository.rs
Co-authored-by: Heikki Linnakangas <heikki@zenith.tech>
* Update pageserver/src/layered_repository.rs
Co-authored-by: Heikki Linnakangas <heikki@zenith.tech>
* Update pageserver/src/layered_repository.rs
Co-authored-by: Heikki Linnakangas <heikki@zenith.tech>
* Fix code style
* Reduce number of tables in test_large_schema to make it fit in timeout with debug build
* Fix style of test_large_schema.py
* Fix handlng of duplicates layers
Co-authored-by: Heikki Linnakangas <heikki@zenith.tech>
We were getting a warning like this from the pg_regress tests:
=================== warnings summary ===================
/usr/lib/python3/dist-packages/_pytest/config/__init__.py:663
/usr/lib/python3/dist-packages/_pytest/config/__init__.py:663: PytestAssertRewriteWarning: Module already imported so cannot be rewritten: fixtures.pg_stats
self.import_plugin(import_spec)
-- Docs: https://docs.pytest.org/en/stable/warnings.html
------------------ Benchmark results -------------------
To fix, reorder the imports in conftest.py. I'm not sure what exactly
the problem was or why the order matters, but the warning is gone and
that's good enough for me.
If the WAL arrives at the pageserver slowly, it's possible that the
branch is created before all the data on the parent branch have
arrived. That results in a failure:
test_runner/batch_others/test_tenant_relocation.py:259: in test_tenant_relocation
timeline_id_second, current_lsn_second = populate_branch(pg_second, create_table=False, expected_sum=1001000)
test_runner/batch_others/test_tenant_relocation.py:133: in populate_branch
assert cur.fetchone() == (expected_sum, )
E assert (500500,) == (1001000,)
E At index 0 diff: 500500 != 1001000
E Full diff:
E - (1001000,)
E + (500500,)
To fix, specify the LSN to branch at, so that the pageserver will wait
for it arrive.
See https://github.com/neondatabase/neon/issues/2063
Resolves#2054
**Context**: branch creation needs to wait for GC to acquire `gc_cs` lock, which prevents creating new timelines during GC. However, because individual timeline GC iteration also requires `compaction_cs` lock, branch creation may also need to wait for compactions of multiple timelines. This results in large latency when creating a new branch, which we advertised as *"instantly"*.
This PR optimizes the latency of branch creation by separating GC into two phases:
1. Collect GC data (branching points, cutoff LSNs, etc)
2. Perform GC for each timeline
The GC bottleneck comes from step 2, which must wait for compaction of multiple timelines. This PR modifies the branch creation and GC functions to allow GC to hold the GC lock only in step 1. As a result, branch creation doesn't need to wait for compaction to finish but only needs to wait for GC data collection step, which is fast.
* Wait for all computes (except one) to complete before proceeding with
the single compute.
* It previously waited for too few seconds. As the test is randomized, it was
not failing all the time, but only in specific unlucky cases.
E.g. when there were no successfuly queries by concurrent computes,
and the single node had big timeouts and spent lots of time making the
transaction.
See https://github.com/neondatabase/neon/runs/7234456482?check_suite_focus=true
(around line 980).
* Wait for exactly one extra transaction by the single compute.
