d5d251da9a
Add a custom implementation of boost::adaptors::uniqued that is compatible with C++20 ranges library. This bridges the gap between Boost.Range and the C++ standard library ranges until std::views::unique becomes available in C++26. Currently, the unique view is included in [P2214](https://www.open-std.org/jtc1/sc22/wg21/docs/papers/2023/p2760r0.html) "A Plan for C++ Ranges Evolution", which targets C++26. The implementation provides: - A lazy view adaptor that presents unique consecutive elements - No modification of source range - Compatibility with C++20 range views and concepts - Lighter header dependencies compared to Boost This resolves compilation errors when piping C++20 range views to boost::adaptors::uniqued, which fails due to concept requirements mismatch. For example: ```c++ auto range = std::views::take(n) | boost::adaptors::uniqued; // fails ``` This change also offers us a lightweight solution in terms of smaller header dependency. While std::ranges::unique exists in C++23, it's an eager algorithm that modifies the source range in-place, unlike boost::adaptors::uniqued which is a lazy view. The proposed std::views::unique (P2214) targeting C++26 would provide this functionality, but is not yet available. This implementation serves as an interim solution for filtering consecutive duplicate elements using range views until std::views::unique is standardized. For more details on the differences between `std::ranges::unique` and `boost::adaptors::uniqued`: - boost::adaptors::uniqued is a view adaptor that creates a lazy view over the original range. It: * Doesn't modify the source range * Returns a view that presents unique consecutive elements * Is non-destructive and lazy-evaluated * Can be composed with other views - std::ranges::unique is an algorithm that: * Modifies the source range in-place * Removes consecutive duplicates by shifting elements * Returns an iterator to the new logical end * Cannot be used as a view or composed with other range adaptors Signed-off-by: Kefu Chai <kefu.chai@scylladb.com>
Scylla unit tests using C++ and the Boost test framework
The source files in this directory are Scylla unit tests written in C++ using the Boost.Test framework. These unit tests come in three flavors:
-
Some simple tests that check stand-alone C++ functions or classes use Boost's
BOOST_AUTO_TEST_CASE. -
Some tests require Seastar features, and need to be declared with Seastar's extensions to Boost.Test, namely
SEASTAR_TEST_CASE. -
Even more elaborate tests require not just a functioning Seastar environment but also a complete (or partial) Scylla environment. Those tests use the
do_with_cql_env()ordo_with_cql_env_thread()function to set up a mostly-functioning environment behaving like a single-node Scylla, in which the test can run.
While we have many tests of the third flavor, writing new tests of this type should be reserved to white box tests - tests where it is necessary to inspect or control Scylla internals that do not have user-facing APIs such as CQL. In contrast, black-box tests - tests that can be written only using user-facing APIs, should be written in one of newer test frameworks that we offer - such as test/cqlpy or test/alternator (in Python, using the CQL or DynamoDB APIs respectively) or test/cql (using textual CQL commands), or - if more than one Scylla node is needed for a test - using the test/topology* framework.
Running tests
Because these are C++ tests, they need to be compiled before running.
To compile a single test executable row_cache_test, use a command like
ninja build/dev/test/boost/row_cache_test
You can also use ninja dev-test to build all C++ tests, or use
ninja deb-build to build the C++ tests and also the full Scylla executable
(however, note that full Scylla executable isn't needed to run Boost tests).
Replace "dev" by "debug" or "release" in the examples above and below to use the "debug" build mode (which, importantly, compiles the test with ASAN and UBSAN enabling on and helps catch difficult-to-catch use-after-free bugs) or the "release" build mode (optimized for run speed).
To run an entire test file row_cache_test, including all its test
functions, use a command like:
build/dev/test/boost/row_cache_test -- -c1 -m1G
to run a single test function test_reproduce_18045() from the longer test
file, use a command like:
build/dev/test/boost/row_cache_test -t test_reproduce_18045 -- -c1 -m1G
In these command lines, the parameters before the -- are passed to
Boost.Test, while the parameters after the -- are passed to the test code,
and in particular to Seastar. In this example Seastar is asked to run on one
CPU (-c1) and use 1G of memory (-m1G) instead of hogging the entire
machine. The Boost.Test option -t test_reproduce_18045 asks it to run just
this one test function instead of all the test functions in the executable.
Unfortunately, interrupting a running test with control-C while doesn't
work. This is a known bug (#5696). Kill a test with SIGKILL (-9) if you
need to kill it while it's running.
Boost tests can also be run using test.py - which is a script that provides a uniform way to run all tests in scylladb.git - C++ tests, Python tests, etc.
Writing tests
Because of the large build time and build size of each separate test executable, it is recommended to put test functions into relatively large source files. But not too large - to keep compilation time of a single source file (during development) at reasonable levels.
When adding new source files in test/boost, don't forget to list the new source file in configure.py and also in CMakeLists.txt. The former is needed by our CI, but the latter is preferred by some developers.