6165124fcc
The statement_restrictions code is responsible for analyzing the WHERE clause, deciding on the query plan (which index to use), and extracting the partition and clustering keys to use for the index. Currently, it suffers from repetition in making its decisions: there are 15 calls to expr::visit in statement_restrictions.cc, and 14 find_binop calls. This reduces to 2 visits (one nested in the other) and 6 find_binop calls. The analysis of binary operators is done once, then reused. The key data structure introduced is the predicate. While an expression takes inputs from the row evaluated, constants, and bind variables, and produces a boolean result, predicates ask which values for a column (or a number of columns) are needed to satisfy (part of) the WHERE clause. The WHERE clause is then expressed as a conjunction of such predicates. The analyzer uses the predicates to select the index, then uses the predicates to compute the partition and clustering keys. The refactoring is composed of these parts (but patches from different parts are interspersed): 1. an exhaustive regression test is added as the first commit, to ensure behavior doesn't change 2. move computation from query time to prepare time 3. introduce, gradually enrich, and use predicates to implement the statement_restrictions API Major refactoring, and no bugs fixed, so definitely not backporting. Closes scylladb/scylladb#29114 * github.com:scylladb/scylladb: cql3: statement_restrictions: replace has_eq_restriction_on_column with precomputed set cql3: statement_restrictions: replace multi_column_range_accumulator_builder with direct predicate iteration cql3: statement_restrictions: use predicate fields in build_get_clustering_bounds_fn cql3: statement_restrictions: remove extract_single_column_restrictions_for_column cql3: statement_restrictions: use predicate vectors in prepare_indexed_local cql3: statement_restrictions: use predicate vector size for clustering prefix length cql3: statement_restrictions: replace do_find_idx and is_supported_by with predicate-based versions cql3: statement_restrictions: remove expression-based has_supporting_index and index_supports_some_column cql3: statement_restrictions: replace multi-column and PK index support checks with predicate-based versions cql3: statement_restrictions: add predicate-based index support checking cql3: statement_restrictions: use pre-built single-column maps for index support checks cql3: statement_restrictions: build clustering-prefix restrictions incrementally cql3: statement_restrictions: build partition-range restrictions incrementally cql3: statement_restrictions: build clustering-key single-column restrictions map incrementally cql3: statement_restrictions: build partition-key single-column restrictions map incrementally cql3: statement_restrictions: build non-primary-key single-column restrictions map incrementally cql3: statement_restrictions: use tracked has_mc_clustering for _has_multi_column cql3: statement_restrictions: track has-token state incrementally cql3: statement_restrictions: track partition-key-empty state incrementally cql3: statement_restrictions: track first multi-column predicate incrementally cql3: statement_restrictions: track last clustering column incrementally cql3: statement_restrictions: track clustering-has-slice incrementally cql3: statement_restrictions: track has-multi-column-clustering incrementally cql3: statement_restrictions: track clustering-empty state incrementally cql3: statement_restrictions: replace restr bridge variable with pred.filter cql3: statement_restrictions: convert single-column branch to use predicate properties cql3: statement_restrictions: convert multi-column branch to use predicate properties cql3: statement_restrictions: convert constructor loop to iterate over predicates cql3: statement_restrictions: annotate predicates with operator properties cql3: statement_restrictions: annotate predicates with is_not_null and is_multi_column cql3: statement_restrictions: complete preparation early cql3: statement_restrictions: convert expressions to predicates without being directed at a specific column cql3: statement_restrictions: refine possible_lhs_values() function_call processing cql3: statement_restrictions: return nullptr for function solver if not token cql3: statement_restrictions: refine possible_lhs_values() subscript solving cql3: statement_restrictions: return nullptr from possible_lhs_values instead of on_internal_error cql3: statement_restrictions: convert possible_lhs_values into a solver cql3: statement_restrictions: split _where to boolean factors in preparation for predicates conversion cql3: statement_restrictions: refactor IS NOT NULL processing cql3: statement_restrictions: fold add_single_column_nonprimary_key_restriction() into its caller cql3: statement_restrictions: fold add_single_column_clustering_key_restriction() into its caller cql3: statement_restrictions: fold add_single_column_partition_key_restriction() into its caller cql3: statement_restrictions: fold add_token_partition_key_restriction() into its caller cql3: statement_restrictions: fold add_multi_column_clustering_key_restriction() into its caller cql3: statement_restrictions: avoid early return in add_multi_column_clustering_key_restrictions cql3: statement_restrictions: fold add_is_not_restriction() into its caller cql3: statement_restrictions: fold add_restriction() into its caller cql3: statement_restrictions: remove possible_partition_token_values() cql3: statement_restrictions: remove possible_column_values cql3: statement_restrictions: pass schema to possible_column_values() cql3: statement_restrictions: remove fallback path in solve() cql3: statement_restrictions: reorder possible_lhs_column parameters cql3: statement_restrictions: prepare solver for multi-column restrictions cql3: statement_restrictions: add solver for token restriction on index cql3: statement_restrictions: pre-analyze column in value_for() cql3: statement_restrictions: don't handle boolean constants in multi_column_range_accumulator_builder cql3: statement_restrictions: split range_from_raw_bounds into prepare phase and query phase cql3: statement_restrictions: adjust signature of range_from_raw_bounds cql3: statement_restrictions: split multi_column_range_accumulator into prepare-time and query-time phases cql3: statement_restrictions: make get_multi_column_clustering_bounds a builder cql3: statement_restrictions: multi-key clustering restrictions one layer deeper cql3: statement_restrictions: push multi-column post-processing into get_multi_column_clustering_bounds() cql3: statement_restrictions: pre-analyze single-column clustering key restrictions cql3: statement_restrictions: wrap value_for_index_partition_key() cql3: statement_restrictions: hide value_for() cql3: statement_restrictions: push down clustering prefix wrapper one level cql3: statement_restrictions: wrap functions that return clustering ranges cql3: statement_restrictions: do not pass view schema back and forth cql3: statement_restrictions: pre-analyze token range restrictions cql3: statement_restrictions: pre-analyze partition key columns cql3: statement_restrictions: do not collect subscripted partition key columns cql3: statement_restrictions: split _partition_range_restrictions into three cases cql3: statement_restrictions: move value_list, value_set to header file cql3: statement_restrictions: wrap get_partition_key_ranges cql3: statement_restrictions: prepare statement_restrictions for capturing `this` test: statement_restrictions: add index_selection regression test
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.