ebaf536449
lock_tables_metadata() acquires a write lock on tables_metadata._cf_lock on every shard. It used invoke_on_all(), which dispatches lock acquisitions to all shards in parallel via parallel_for_each + smp::submit_to. When two fibers call lock_tables_metadata() concurrently, this can deadlock. parallel_for_each starts all iterations unconditionally: even when the local shard's lock attempt blocks (because the other fiber already holds it), SMP messages are still sent to remote shards. Both fibers' lock-acquisition messages land in the per-shard SMP queues. The SMP queue itself is FIFO, but process_incoming() drains it and schedules each item as a reactor task via add_task(), which — in debug and sanitize builds with SEASTAR_SHUFFLE_TASK_QUEUE — shuffles each newly added task against all pending tasks in the same scheduling group's reactor task queue. This means fiber A's lock acquisition can be reordered past fiber B's (and past unrelated tasks) on a given shard. If fiber A wins the lock on shard X while fiber B wins on shard Y, this creates a classic cross-shard lock-ordering deadlock (circular wait). In production builds without SEASTAR_SHUFFLE_TASK_QUEUE, the reactor task queue is FIFO. Still, even in release builds, the SMP queues can reorder messages even, so the deadlock is still possible, even if it's much less likely. In debug and sanitize builds, the task-queue shuffle makes the deadlock very likely whenever both fibers' lock-acquisition tasks are pending simultaneously in the reactor task queue on any shard. This deadlock was exposed byce00d61917("db: implement large_data virtual tables with feature flag gating", merged as88a8324e68), which introduced legacy_drop_table_on_all_shards as a second caller of lock_tables_metadata(). When LARGE_DATA_VIRTUAL_TABLES is enabled during topology_state_load (via feature_service::enable), two fibers can race: 1. activate_large_data_virtual_tables() — calls legacy_drop_table_on_all_shards() which calls lock_tables_metadata() synchronously via .get() 2. reload_schema_in_bg() — fires as a background fiber from TABLE_DIGEST_INSENSITIVE_TO_EXPIRY, eventually reaches schema_applier::commit() which also calls lock_tables_metadata() If both reach lock_tables_metadata() while the lock is free on all shards, the parallel acquisition creates the deadlock opportunity. The deadlock blocks topology_state_load() from completing, which prevents the bootstrapping node from finishing its topology state transitions. The coordinator's topology coordinator then waits for the node to reach the expected state, but the node is stuck, so eventually the read_barrier times out after 300 seconds. Fix by acquiring the shard 0 lock first before attempting to acquire any other lock. Whichever fiber wins shard 0 is guaranteed to acquire all remaining shards before the other fiber can proceed past shard 0, eliminating the circular-wait condition. Tested manually with 2 approaches: 1. causing different shard locks to be acquired by different lock_tables_metadata() calls by adding different sleeps depending on the lock_tables_metadata() call and target shard - this reproduced the issue consistently 2. matching the time point at which both fibers reach lock_tables_metadata() adding a single sleep to one of the fibers - this heavily depends on the machine so we can't create a universal reproducer this way, but it did result in the observed failure on my machine after finding the right sleep time Also added a unit test for concurrent lock_tables_metadata() calls. Fixes: SCYLLADB-1694 Fixes: SCYLLADB-1644 Fixes: SCYLLADB-1684 Closes scylladb/scylladb#29678
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.
Execution with pytest
To run all tests with pytest execute
pytest test/boost
To execute all tests in one file, provide the path to the source filename as a parameter
pytest test/boost/aggregate_fcts_test.cc
Since it's a normal path, autocompletion works in the terminal out of the box.
To execute only one test function, provide the path to the source file and function name
pytest --mode dev test/boost/aggregate_fcts_test.cc::test_aggregate_avg
To provide a specific mode, use the next parameter --mode dev,
if parameter isn't provided pytest tries to use ninja mode_list to find out the compiled modes.
Parallel execution is controlled by pytest-xdist and the parameter -n auto.
This command starts tests with the number of workers equal to CPU cores.
The useful command to discover the tests in the file or directory is
pytest --collect-only -q --mode dev test/boost/aggregate_fcts_test.cc
That will return all test functions in the file.
To execute only one function from the test, you can invoke the output from the previous command.
However, suffix for mode should be skipped.
For example,
output shows in the terminal something like this test/boost/aggregate_fcts_test.cc::test_aggregate_avg.dev.
So to execute this specific test function, please use the next command
pytest --mode dev test/boost/aggregate_fcts_test.cc::test_aggregate_avg
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.