RequestContext is used to track each "operation" or "task" in a way that's not tied to tokio tasks. It provides support for fine-grained cancellation of individual operations, or all tasks working on an active tenant or timeline. Most async functions now take a RequestContext argument. RequestContexts form a hierarchy, so that you have a top-level context e.g. for a TCP listener task, a child context for each task handling a connection, and perhaps a grandchild context for each individual client request. In addition to the hierarchy, each RequestContext can be associated with a Tenant or Timeline object. This is used to prevent a Tenant or Timeline from being deleted or detached while there are still tasks accessing it. This fixes a long-standing race conditions between GC/compaction and deletion (see issues #2914 and compiler in any way, but the functions like `get_active_timeline` make it easy to do the right thing. This replaces most of the machinery in `task_mgr.rs`. We don't track running tasks as such anymore, only RequestContexts. In practice, every task holds onto a RequestContext. In addition to supporting cancellation, the RequestContext specifies the desired behavior if a remote layer is needed for the operation. This replaces the `with_ondemand_download_sync` and `no_ondemand_download` macros. The on-demand download now happens deep in the call stack, in get_reconstruct_data(), and the caller is no longer involved in the download, except by passing a RequestContext that specifies whether to do on-demand download or not. The PageReconstructResult type is gone but the PageReconstructError::NeedsDownload variant remains. It's now returned if the context specified "don't do on-demand download", and a layer is missing. TODO: - Enforce better that you hold a RequestContext associated with a Tenant or Timeline. - All the fields in RequestContext are currently 'pub', but things will break if you modify the tenant/timeline fields directly. Make that more safe. - When you create a subcontext, should it inherit the Tenant / Timeline of its parent? - Can the walreceiver::TaskHandle stuff be replaced with this? - Extract smaller patches: - What else could we extract?
Neon test runner
This directory contains integration tests.
Prerequisites:
- Correctly configured Python, see
/docs/sourcetree.md - Neon and Postgres binaries
- See the root README.md for build directions
If you want to test tests with test-only APIs, you would need to add
--features testingto Rust code build commands. For convenience, repository cargo config containsbuild_testingalias, that serves as a subcommand, adding the required feature flags. Usage example:cargo build_testing --releaseis equivalent tocargo build --features testing --release - Tests can be run from the git tree; or see the environment variables below to run from other directories.
- See the root README.md for build directions
If you want to test tests with test-only APIs, you would need to add
- The neon git repo, including the postgres submodule
(for some tests, e.g.
pg_regress)
Test Organization
Regression tests are in the 'regress' directory. They can be run in
parallel to minimize total runtime. Most regression test sets up their
environment with its own pageservers and safekeepers (but see
TEST_SHARED_FIXTURES).
'pg_clients' contains tests for connecting with various client libraries. Each client test uses a Dockerfile that pulls an image that contains the client, and connects to PostgreSQL with it. The client tests can be run against an existing PostgreSQL or Neon installation.
'performance' contains performance regression tests. Each test exercises a particular scenario or workload, and outputs measurements. They should be run serially, to avoid the tests interfering with the performance of each other. Some performance tests set up their own Neon environment, while others can be run against an existing PostgreSQL or Neon environment.
Running the tests
There is a wrapper script to invoke pytest: ./scripts/pytest.
It accepts all the arguments that are accepted by pytest.
Depending on your installation options pytest might be invoked directly.
Test state (postgres data, pageserver state, and log files) will
be stored under a directory test_output.
You can run all the tests with:
./scripts/pytest
If you want to run all the tests in a particular file:
./scripts/pytest test_pgbench.py
If you want to run all tests that have the string "bench" in their names:
./scripts/pytest -k bench
To run tests in parellel we utilize pytest-xdist plugin. By default everything runs single threaded. Number of workers can be specified with -n argument:
./scripts/pytest -n4
By default performance tests are excluded. To run them explicitly pass performance tests selection to the script:
./scripts/pytest test_runner/performance
Useful environment variables:
NEON_BIN: The directory where neon binaries can be found.
POSTGRES_DISTRIB_DIR: The directory where postgres distribution can be found.
Since pageserver supports several postgres versions, POSTGRES_DISTRIB_DIR must contain
a subdirectory for each version with naming convention v{PG_VERSION}/.
Inside that dir, a bin/postgres binary should be present.
DEFAULT_PG_VERSION: The version of Postgres to use,
This is used to construct full path to the postgres binaries.
Format is 2-digit major version nubmer, i.e. DEFAULT_PG_VERSION="14"
TEST_OUTPUT: Set the directory where test state and test output files
should go.
TEST_SHARED_FIXTURES: Try to re-use a single pageserver for all the tests.
NEON_PAGESERVER_OVERRIDES: add a ;-separated set of configs that will be passed as
RUST_LOG: logging configuration to pass into Neon CLI
Useful parameters and commands:
--pageserver-config-override=${value} -c values to pass into pageserver through neon_local cli
--preserve-database-files to preserve pageserver (layer) and safekeer (segment) timeline files on disk
after running a test suite. Such files might be large, so removed by default; but might be useful for debugging or creation of svg images with layer file contents.
Let stdout, stderr and INFO log messages go to the terminal instead of capturing them:
./scripts/pytest -s --log-cli-level=INFO ...
(Note many tests capture subprocess outputs separately, so this may not
show much.)
Exit after the first test failure:
./scripts/pytest -x ...
(there are many more pytest options; run pytest -h to see them.)
Writing a test
Every test needs a Neon Environment, or NeonEnv to operate in. A Neon Environment is like a little cloud-in-a-box, and consists of a Pageserver, 0-N Safekeepers, and compute Postgres nodes. The connections between them can be configured to use JWT authentication tokens, and some other configuration options can be tweaked too.
The easiest way to get access to a Neon Environment is by using the neon_simple_env
fixture. The 'simple' env may be shared across multiple tests, so don't shut down the nodes
or make other destructive changes in that environment. Also don't assume that
there are no tenants or branches or data in the cluster. For convenience, there is a
branch called empty, though. The convention is to create a test-specific branch of
that and load any test data there, instead of the 'main' branch.
For more complicated cases, you can build a custom Neon Environment, with the neon_env
fixture:
def test_foobar(neon_env_builder: NeonEnvBuilder):
# Prescribe the environment.
# We want to have 3 safekeeper nodes, and use JWT authentication in the
# connections to the page server
neon_env_builder.num_safekeepers = 3
neon_env_builder.set_pageserver_auth(True)
# Now create the environment. This initializes the repository, and starts
# up the page server and the safekeepers
env = neon_env_builder.init_start()
# Run the test
...
For more information about pytest fixtures, see https://docs.pytest.org/en/stable/fixture.html
At the end of a test, all the nodes in the environment are automatically stopped, so you
don't need to worry about cleaning up. Logs and test data are preserved for the analysis,
in a directory under ../test_output/<testname>
Before submitting a patch
Ensure that you pass all obligatory checks.
Also consider:
- Writing a couple of docstrings to clarify the reasoning behind a new test.
- Adding more type hints to your code to avoid
Any, especially:- For fixture parameters, they are not automatically deduced.
- For function arguments and return values.