[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.
Simplifies the workflow. Makes the overall build a little faster, as
the build_postgres step doesn't need to upload the pg.tgz artifact,
and the build_neon step doesn't need to download it again.
This effectively reverts commit a490f64a68. That commit changed the
workflow so that the Postgres binaries were not included in the
neon.tgz artifact. With this commit, the pg.tgz artifact is gone, and
the Postgres binaries are part of neon.tgz again.
The "cargo metadata" and "cargo test --no-run" are used in the workflow
to just list names of the final binaries, but unless the same cargo
options like --release or --debug are used in those calls, they will in
fact recompile everything.
Reorganize existing READMEs and other documentation files into mdbook
format. The resulting Table of Contents is a mix of placeholders for
docs that we should write, and documentation files that we already had,
dropped into the most appropriate place.
Update the Pageserver overview diagram. Add sections on thread
management and WAL redo processes.
Add all the RFCs to the mdbook Table of Content too.
Per github issue #1979
On ProposerElected message receival WAL is truncated at streaming point; this
code expected that, once vote is given for the proposer / term switch happened,
flush_lsn can be advanced only by this proposer (or higher one). However, that
didn't take into account possibility of accumulating written WAL and flushing it
after vote is given -- flushing goes without term checks. Which eventually led
to the violation in question.
ref #2048
* Deduce `last_segment` automatically
* Get rid of local `wal_dir`/`wal_seg_size` variables
* Prepare to test parsing of WAL from multiple specific points, not just the start;
extract `check_end_of_wal` function to check both partial and non-partial WAL segments.
neon.tgz artifact in the github workflow included the contents of
'tmp_install', but that seems pointless, because the same files are
included earlier already in the pg.tgz artifact.
Uploading large artifacts is slow in github actions. To speed that up,
make the artifact smaller.
The code coverage tool doesn't require debug symbols, so remove them.
We've discussed doing the same for *all* binaries, but it's nice to
have debugging symbols for debugging purposes, and so that you get
more complete stack traces. The discussion is ongoing, but let's at
least do this for the test symbols now.
- Updated dependencies with "cargo update"
- Updated workspace_hack with "cargo hakari generate"
There's no particular reason to do this now, just a periodic refresh.
"cargo clippy" started to complain about these, after running "cargo
update". Not sure why it didn't complain before, but seems reasonable to
fix these. (The "cargo update" is not included in this commit)
Change the build options to enable basic optimizations even in debug
mode, and always build dependencies with more optimizations. That
makes the debug-mode binaries somewhat faster, without messing up
stack traces and line-by-line debugging too much.
See https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#concurrency
* Previously there was a single concurrency group per each branch.
As the `main` branch got pushed into frequently, very few commits got
tested to the end. It resulted in "broken" `main` branch as there were
no fully successful workflow runs.
Now the `main` branch gets a separate concurrency group for each commit.
* As GitHub Actions syntax does not have the conditional operator, it is
emulated via logical and/or operations. Although undocumented, they
return one of their operands instead of plain true/false.
* Replace 3-space indentation with 2-space indentation while we are here
to be consistent with the rest of the file.
* 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.
We need both storage **and** compute images for deploy, because control plane
picks the compute version based on the storage version. If it notices a fresh
storage it may bump the compute version. And if compute image failed to build
it may break things badly.
