Files
scylladb/test/boost
Avi Kivity 1f7dca0225 Merge 'Fix bad performance for densely populated partition index pages' from Tomasz Grabiec
This applies to small partition workload where index pages have high partition count, and the index doesn't fit in cache. It was observed that the count can be in the order of hundreds. In such a workload pages undergo constant population, LSA compaction, and LSA eviction, which has severe impact on CPU utilization.

Refs https://scylladb.atlassian.net/browse/SCYLLADB-620

This PR reduces the impact by several changes:

  - reducing memory footprint in the partition index. Assuming partition key size is 16 bytes, the cost dropped from 96 bytes to 36 bytes per partition.

  - flattening the object graph and amortizing storage. Storing entries directly in the vector. Storing all key values in a single managed_bytes. Making index_entry a trivial struct.

  - index entries and key storage are now trivially moveable, and batched inside vector storage
    so LSA migration can use memcpy(), which amortizes the cost per key. This reduces the cost of LSA segment compaction.

 - LSA eviction is now pretty much constant time for the whole page
   regardless of the number of entries, because elements are trivial and batched inside vectors.
   Page eviction cost dropped from 50 us to 1 us.

Performance evaluated with:

   scylla perf-simple-query -c1 -m200M --partitions=1000000

Before:

```
7774.96 tps (166.0 allocs/op, 521.7 logallocs/op,  54.0 tasks/op,  802428 insns/op,  430457 cycles/op,        0 errors)
7511.08 tps (166.1 allocs/op, 527.2 logallocs/op,  54.0 tasks/op,  804185 insns/op,  430752 cycles/op,        0 errors)
7740.44 tps (166.3 allocs/op, 526.2 logallocs/op,  54.2 tasks/op,  805347 insns/op,  432117 cycles/op,        0 errors)
7818.72 tps (165.2 allocs/op, 517.6 logallocs/op,  53.7 tasks/op,  794965 insns/op,  427751 cycles/op,        0 errors)
7865.49 tps (165.1 allocs/op, 513.3 logallocs/op,  53.6 tasks/op,  788898 insns/op,  425171 cycles/op,        0 errors)
```

After (+318%):

```
32492.40 tps (130.7 allocs/op,  12.8 logallocs/op,  36.1 tasks/op,  109236 insns/op,  103203 cycles/op,        0 errors)
32591.99 tps (130.4 allocs/op,  12.8 logallocs/op,  36.0 tasks/op,  108947 insns/op,  102889 cycles/op,        0 errors)
32514.52 tps (130.6 allocs/op,  12.8 logallocs/op,  36.0 tasks/op,  109118 insns/op,  103219 cycles/op,        0 errors)
32491.14 tps (130.6 allocs/op,  12.8 logallocs/op,  36.0 tasks/op,  109349 insns/op,  103272 cycles/op,        0 errors)
32582.90 tps (130.5 allocs/op,  12.8 logallocs/op,  36.0 tasks/op,  109269 insns/op,  102872 cycles/op,        0 errors)
32479.43 tps (130.6 allocs/op,  12.8 logallocs/op,  36.0 tasks/op,  109313 insns/op,  103242 cycles/op,        0 errors)
32418.48 tps (130.7 allocs/op,  12.8 logallocs/op,  36.1 tasks/op,  109201 insns/op,  103301 cycles/op,        0 errors)
31394.14 tps (130.7 allocs/op,  12.8 logallocs/op,  36.1 tasks/op,  109267 insns/op,  103301 cycles/op,        0 errors)
32298.55 tps (130.7 allocs/op,  12.8 logallocs/op,  36.1 tasks/op,  109323 insns/op,  103551 cycles/op,        0 errors)
```

When the workload is miss-only, with both row cache and index cache disabled (no cache maintenance cost):

  perf-simple-query -c1 -m200M --duration 6000 --partitions=100000 --enable-index-cache=0 --enable-cache=0

Before:

```
9124.57 tps (146.2 allocs/op, 789.0 logallocs/op,  45.3 tasks/op,  889320 insns/op,  357937 cycles/op,        0 errors)
9437.23 tps (146.1 allocs/op, 789.3 logallocs/op,  45.3 tasks/op,  889613 insns/op,  357782 cycles/op,        0 errors)
9455.65 tps (146.0 allocs/op, 787.4 logallocs/op,  45.2 tasks/op,  887606 insns/op,  357167 cycles/op,        0 errors)
9451.22 tps (146.0 allocs/op, 787.4 logallocs/op,  45.3 tasks/op,  887627 insns/op,  357357 cycles/op,        0 errors)
9429.50 tps (146.0 allocs/op, 787.4 logallocs/op,  45.3 tasks/op,  887761 insns/op,  358148 cycles/op,        0 errors)
9430.29 tps (146.1 allocs/op, 788.2 logallocs/op,  45.3 tasks/op,  888501 insns/op,  357679 cycles/op,        0 errors)
9454.08 tps (146.0 allocs/op, 787.3 logallocs/op,  45.3 tasks/op,  887545 insns/op,  357132 cycles/op,        0 errors)
```

After (+55%):

```
14484.84 tps (150.7 allocs/op,   6.5 logallocs/op,  44.7 tasks/op,  396164 insns/op,  229490 cycles/op,        0 errors)
14526.21 tps (150.8 allocs/op,   6.5 logallocs/op,  44.8 tasks/op,  396401 insns/op,  228824 cycles/op,        0 errors)
14567.53 tps (150.7 allocs/op,   6.5 logallocs/op,  44.7 tasks/op,  396319 insns/op,  228701 cycles/op,        0 errors)
14545.63 tps (150.6 allocs/op,   6.5 logallocs/op,  44.7 tasks/op,  395889 insns/op,  228493 cycles/op,        0 errors)
14626.06 tps (150.5 allocs/op,   6.5 logallocs/op,  44.7 tasks/op,  395254 insns/op,  227891 cycles/op,        0 errors)
14593.74 tps (150.5 allocs/op,   6.5 logallocs/op,  44.7 tasks/op,  395480 insns/op,  227993 cycles/op,        0 errors)
14538.10 tps (150.8 allocs/op,   6.5 logallocs/op,  44.8 tasks/op,  397035 insns/op,  228831 cycles/op,        0 errors)
14527.18 tps (150.8 allocs/op,   6.5 logallocs/op,  44.8 tasks/op,  396992 insns/op,  228839 cycles/op,        0 errors)
```

Same as above, but with summary ratio increased from 0.0005 to 0.005 (smaller pages):

Before:

```
33906.70 tps (146.1 allocs/op,  83.6 logallocs/op,  45.1 tasks/op,  170553 insns/op,   98104 cycles/op,        0 errors)
32696.16 tps (146.0 allocs/op,  83.5 logallocs/op,  45.1 tasks/op,  170369 insns/op,   98405 cycles/op,        0 errors)
33889.05 tps (146.1 allocs/op,  83.6 logallocs/op,  45.1 tasks/op,  170551 insns/op,   98135 cycles/op,        0 errors)
33893.24 tps (146.1 allocs/op,  83.5 logallocs/op,  45.1 tasks/op,  170488 insns/op,   98168 cycles/op,        0 errors)
33836.73 tps (146.1 allocs/op,  83.6 logallocs/op,  45.1 tasks/op,  170528 insns/op,   98226 cycles/op,        0 errors)
33897.61 tps (146.0 allocs/op,  83.5 logallocs/op,  45.1 tasks/op,  170428 insns/op,   98081 cycles/op,        0 errors)
33834.73 tps (146.1 allocs/op,  83.5 logallocs/op,  45.1 tasks/op,  170438 insns/op,   98178 cycles/op,        0 errors)
33776.31 tps (146.3 allocs/op,  83.9 logallocs/op,  45.2 tasks/op,  170958 insns/op,   98418 cycles/op,        0 errors)
33808.08 tps (146.3 allocs/op,  83.9 logallocs/op,  45.2 tasks/op,  170940 insns/op,   98388 cycles/op,        0 errors)
```

After (+18%):

```
40081.51 tps (148.2 allocs/op,   4.4 logallocs/op,  45.0 tasks/op,  121047 insns/op,   82231 cycles/op,        0 errors)
40005.85 tps (148.6 allocs/op,   4.4 logallocs/op,  45.2 tasks/op,  121327 insns/op,   82545 cycles/op,        0 errors)
39816.75 tps (148.3 allocs/op,   4.4 logallocs/op,  45.1 tasks/op,  121067 insns/op,   82419 cycles/op,        0 errors)
39953.11 tps (148.1 allocs/op,   4.4 logallocs/op,  45.0 tasks/op,  121027 insns/op,   82258 cycles/op,        0 errors)
40073.96 tps (148.2 allocs/op,   4.4 logallocs/op,  45.0 tasks/op,  121006 insns/op,   82313 cycles/op,        0 errors)
39882.25 tps (148.2 allocs/op,   4.4 logallocs/op,  45.0 tasks/op,  120925 insns/op,   82320 cycles/op,        0 errors)
39916.08 tps (148.3 allocs/op,   4.4 logallocs/op,  45.1 tasks/op,  121054 insns/op,   82393 cycles/op,        0 errors)
39786.30 tps (148.2 allocs/op,   4.4 logallocs/op,  45.0 tasks/op,  121027 insns/op,   82465 cycles/op,        0 errors)
38662.45 tps (148.3 allocs/op,   4.4 logallocs/op,  45.0 tasks/op,  121108 insns/op,   82312 cycles/op,        0 errors)
39849.42 tps (148.3 allocs/op,   4.4 logallocs/op,  45.1 tasks/op,  121098 insns/op,   82447 cycles/op,        0 errors)
```

Closes scylladb/scylladb#28603

* github.com:scylladb/scylladb:
  sstables: mx: index_reader: Optimize parsing for no promoted index case
  vint: Use std::countl_zero()
  test: sstable_partition_index_cache_test: Validate scenario of pages with sparse promoted index placement
  sstables: mx: index_reader: Amoritze partition key storage
  managed_bytes: Hoist write_fragmented() to common header
  utils: managed_vector: Use std::uninitialized_move() to move objects
  sstables: mx: index_reader: Keep promoted_index info next to index_entry
  sstables: mx: index_reader: Extract partition_index_page::clear_gently()
  sstables: mx: index_reader: Shave-off 16 bytes from index_entry by using raw_token
  sstables: mx: index_reader: Reduce allocation_section overhead during index page parsing by batching allocation
  sstables: mx: index_reader: Keep index_entry directly in the vector
  dht: Introduce raw_token
  test: perf_simple_query: Add 'sstable-format' command-line option
  test: perf_simple_query: Add 'sstable-summary-ratio' command-line option
  test: perf-simple-query: Add option to disable index cache
  test: cql_test_env: Respect enable-index-cache config

(cherry picked from commit 5e7fb08bf3)

Closes scylladb/scylladb#29136

Closes scylladb/scylladb#29140
2026-03-20 10:58:26 +02:00
..
2024-12-23 23:37:02 +01:00

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.