Files
scylladb/test/boost
Botond Dénes 39bcf99f8e Merge 'Apply hard limit to partition range vectors in secondary index queries' from Nikos Dragazis
Secondary index queries fetch partition keys from the index view and store them in an `std::vector`. The vector size is currently limited by the user's page size and the page memory limit (1MiB). These are not enough to prevent large contiguous allocations (which can lead to stalls).

This series introduces a hard limit to the vector size to ensure it does not exceed the allocator's preferred max contiguous allocation size (128KiB). With the size of each element being 120 bytes, this allows for 1092 partition keys. The limit was set to 1000. Any partitions above this limit are discarded.

Discarding partitions breaks the querier cache on the replicas, causing a performance regression, as can be seen from the following measurements:
```
* Cluster: 3 nodes (local Docker containers), 1 vCPU, 4GB memory, dev mode
* Schema:
  CREATE KEYSPACE ks WITH replication = {'class': 'org.apache.cassandra.locator.NetworkTopologyStrategy', 'datacenter1': '3'} AND durable_writes = true AND tablets = {'enabled': false};
  CREATE TABLE ks.t1 (pk1 int, pk2 int, ck int, value int, PRIMARY KEY ((pk1, pk2), ck));
  CREATE INDEX t1_pk2_idx ON ks.t1(pk2);
* Query: CONSISTENCY LOCAL_QUORUM; SELECT * FROM ks.t1 where pk2 = 1;

+------------+-------------------+-------------------+
|  Page Size |      Master       |   Vector Limit    |
+============+===================+===================+
|            |   Latency (sec)   |   Latency (sec)   |
+------------+-------------------+-------------------+
|     100    |  5.80 ± 0.13      |  5.64 ± 0.10      |
+------------+-------------------+-------------------+
|    1000    |  4.77 ± 0.07      |  4.62 ± 0.06      |
+------------+-------------------+-------------------+
|    2000    |  4.67 ± 0.07      |  5.13 ± 0.03      |
+------------+-------------------+-------------------+
|    5000    |  4.82 ± 0.09      |  6.25 ± 0.06      |
+------------+-------------------+-------------------+
|   10000    |  4.89 ± 0.36      |  7.52 ± 0.13      |
+------------+-------------------+-------------------+
|     -1     |  4.90 ± 0.67      |  4.79 ± 0.33      |
+------------+-------------------+-------------------+
```
We expect this to be fixed with adaptive paging in a future PR. Until then, users can avoid regressions by adjusting their page size.

Additionally, this series changes the `untyped_result_set` to store rows in a `chunked_vector` instead of an `std::vector`, similarly to the `result_set`. Secondary index queries use an `untyped_result_set` to store the raw result from the index view before processing. With 1MiB results, the `std::vector` would cause a large allocation of this magnitude.

Finally, a unit test is added to reproduce the bug.

Fixes #18536.

The PR fixes stalls of up to 100ms, but there is an easy workaround: adjust the page size. No need to backport.

Closes scylladb/scylladb#22682

* github.com:scylladb/scylladb:
  cql3: secondary index: Limit page size for single-row partitions
  cql3: secondary index: Limit the size of partition range vectors
  cql3: untyped_result_set: Store rows in chunked_vector
  test: Reproduce bug with large allocations from secondary index
2025-03-14 15:06:07 +02:00
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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:

  1. Some simple tests that check stand-alone C++ functions or classes use Boost's BOOST_AUTO_TEST_CASE.

  2. Some tests require Seastar features, and need to be declared with Seastar's extensions to Boost.Test, namely SEASTAR_TEST_CASE.

  3. 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() or do_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.