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Annotation type Annotation details
2 @message
Performance problem

AssertionError: assert   
  - Medians ratio: acceptable
  + Medians ratio: /* perf_issue_tag */ POOR:   4.63889, more than threshold:       0.4
  + CPU times for each of 21 measures:
  + sp_name='hash_eval':
  + 0.37
  + 0.3999999999999999
  + 0.34000000000000075
  + 0.33999999999999986
  + 0.35999999999999943
  + 0.40000000000000036
  + 0.35999999999999943
  + 0.3899999999999988
  + 0.379999999999999
  + 0.3500000000000014
  + 0.33999999999999986
  + 0.46000000000000085
  + 0.370000000000001
  + 0.4499999999999993
  + 0.370000000000001
  + 0.33999999999999986
  + 0.35999999999999943
  + 0.35999999999999943
  + 0.3399999999999963
  + 0.37999999999999545
  + 0.35999999999999943
  + sp_name='udr_call':
  + 1.62
  + 1.6199999999999997
  + 1.67
  + 1.67
  + 1.6500000000000004
  + 1.6799999999999997
  + 1.6800000000000015
  + 1.6100000000000012
  + 1.6499999999999986
  + 1.6900000000000013
  + 1.629999999999999
  + 1.6899999999999977
  + 1.6700000000000017
  + 1.6999999999999993
  + 1.6799999999999997
  + 1.8000000000000007
  + 1.8100000000000023
  + 1.6499999999999986
  + 1.8000000000000043
  + 1.6100000000000065
  + 1.8200000000000003

LOG DETAILS:

2025-06-13 05:42:48.329
2025-06-13 05:42:48.335 act = <firebird.qa.plugin.Action object at [hex]>
2025-06-13 05:42:48.341 capsys = <_pytest.capture.CaptureFixture object at [hex]>
2025-06-13 05:42:48.346
2025-06-13 05:42:48.352 @pytest.mark.version('>=6.0')
2025-06-13 05:42:48.357 def test_1(act: Action, capsys):
2025-06-13 05:42:48.363
2025-06-13 05:42:48.369 with act.db.connect() as con:
2025-06-13 05:42:48.374 cur=con.cursor()
2025-06-13 05:42:48.382 cur.execute('select mon$server_pid as p from mon$attachments where mon$attachment_id = current_connection')
2025-06-13 05:42:48.393 fb_pid = int(cur.fetchone()[0])
2025-06-13 05:42:48.404
2025-06-13 05:42:48.410 times_map = {}
2025-06-13 05:42:48.418 for i in range(0, N_MEASURES):
2025-06-13 05:42:48.427 fb_info_init = psutil.Process(fb_pid).cpu_times()
2025-06-13 05:42:48.437 cur.callproc( 'sp_gen_hash', (N_HASH_EVALUATE_COUNT,) )
2025-06-13 05:42:48.446 fb_info_curr = psutil.Process(fb_pid).cpu_times()
2025-06-13 05:42:48.455 times_map[ 'hash_eval', i ]  = max(fb_info_curr.user - fb_info_init.user, 0.000001)
2025-06-13 05:42:48.462
2025-06-13 05:42:48.473 fb_info_init = psutil.Process(fb_pid).cpu_times()
2025-06-13 05:42:48.484 cur.callproc( 'sp_udr_call', (N_UDR_CALLS_COUNT,) )
2025-06-13 05:42:48.492 fb_info_curr = psutil.Process(fb_pid).cpu_times()
2025-06-13 05:42:48.500 times_map[ 'udr_call', i ]  = max(fb_info_curr.user - fb_info_init.user, 0.000001)
2025-06-13 05:42:48.506
2025-06-13 05:42:48.511
2025-06-13 05:42:48.520 sp_gen_hash_median = median([v for k,v in times_map.items() if k[0] == 'hash_eval'])
2025-06-13 05:42:48.526 sp_udr_call_median = median([v for k,v in times_map.items() if k[0] == 'udr_call'])
2025-06-13 05:42:48.531
2025-06-13 05:42:48.537 median_ratio = sp_udr_call_median / sp_gen_hash_median
2025-06-13 05:42:48.543
2025-06-13 05:42:48.551 print( 'Medians ratio: ' + ('acceptable' if median_ratio <= MAX_RATIO else '/* perf_issue_tag */ POOR: %s, more than threshold: %s' % ( '{:9g}'.format(median_ratio), '{:9g}'.format(MAX_RATIO) ) ) )
2025-06-13 05:42:48.563 if median_ratio > MAX_RATIO:
2025-06-13 05:42:48.570 print(f'CPU times for each of {N_MEASURES} measures:')
2025-06-13 05:42:48.576 for sp_name in ('hash_eval', 'udr_call', ):
2025-06-13 05:42:48.583 print(f'{sp_name=}:')
2025-06-13 05:42:48.588 for p in [v for k,v in times_map.items() if k[0] == sp_name]:
2025-06-13 05:42:48.594 print(p)
2025-06-13 05:42:48.599
2025-06-13 05:42:48.606 act.expected_stdout = expected_stdout
2025-06-13 05:42:48.613 act.stdout = capsys.readouterr().out
2025-06-13 05:42:48.620 >       assert act.clean_stdout == act.clean_expected_stdout
2025-06-13 05:42:48.627 E       AssertionError: assert
2025-06-13 05:42:48.634 E         - Medians ratio: acceptable
2025-06-13 05:42:48.641 E         + Medians ratio: /* perf_issue_tag */ POOR:   4.63889, more than threshold:       0.4
2025-06-13 05:42:48.648 E         + CPU times for each of 21 measures:
2025-06-13 05:42:48.654 E         + sp_name='hash_eval':
2025-06-13 05:42:48.661 E         + 0.37
2025-06-13 05:42:48.667 E         + 0.3999999999999999
2025-06-13 05:42:48.674 E         + 0.34000000000000075
2025-06-13 05:42:48.684 E         + 0.33999999999999986
2025-06-13 05:42:48.694 E         + 0.35999999999999943
2025-06-13 05:42:48.700 E         + 0.40000000000000036
2025-06-13 05:42:48.706 E         + 0.35999999999999943
2025-06-13 05:42:48.712 E         + 0.3899999999999988
2025-06-13 05:42:48.719 E         + 0.379999999999999
2025-06-13 05:42:48.727 E         + 0.3500000000000014
2025-06-13 05:42:48.739 E         + 0.33999999999999986
2025-06-13 05:42:48.749 E         + 0.46000000000000085
2025-06-13 05:42:48.758 E         + 0.370000000000001
2025-06-13 05:42:48.765 E         + 0.4499999999999993
2025-06-13 05:42:48.771 E         + 0.370000000000001
2025-06-13 05:42:48.777 E         + 0.33999999999999986
2025-06-13 05:42:48.783 E         + 0.35999999999999943
2025-06-13 05:42:48.790 E         + 0.35999999999999943
2025-06-13 05:42:48.795 E         + 0.3399999999999963
2025-06-13 05:42:48.801 E         + 0.37999999999999545
2025-06-13 05:42:48.807 E         + 0.35999999999999943
2025-06-13 05:42:48.816 E         + sp_name='udr_call':
2025-06-13 05:42:48.826 E         + 1.62
2025-06-13 05:42:48.832 E         + 1.6199999999999997
2025-06-13 05:42:48.838 E         + 1.67
2025-06-13 05:42:48.844 E         + 1.67
2025-06-13 05:42:48.850 E         + 1.6500000000000004
2025-06-13 05:42:48.856 E         + 1.6799999999999997
2025-06-13 05:42:48.862 E         + 1.6800000000000015
2025-06-13 05:42:48.868 E         + 1.6100000000000012
2025-06-13 05:42:48.874 E         + 1.6499999999999986
2025-06-13 05:42:48.880 E         + 1.6900000000000013
2025-06-13 05:42:48.886 E         + 1.629999999999999
2025-06-13 05:42:48.893 E         + 1.6899999999999977
2025-06-13 05:42:48.899 E         + 1.6700000000000017
2025-06-13 05:42:48.905 E         + 1.6999999999999993
2025-06-13 05:42:48.911 E         + 1.6799999999999997
2025-06-13 05:42:48.917 E         + 1.8000000000000007
2025-06-13 05:42:48.922 E         + 1.8100000000000023
2025-06-13 05:42:48.928 E         + 1.6499999999999986
2025-06-13 05:42:48.934 E         + 1.8000000000000043
2025-06-13 05:42:48.939 E         + 1.6100000000000065
2025-06-13 05:42:48.945 E         + 1.8200000000000003
2025-06-13 05:42:48.951
2025-06-13 05:42:48.956 tests/bugs/gh_7989_test.py:152: AssertionError
2025-06-13 05:42:48.962 ---------------------------- Captured stdout setup -----------------------------
2025-06-13 05:42:48.968 Creating db: localhost:/var/tmp/qa_2024/test_11654/test.fdb [page_size=None, sql_dialect=None, charset='ASCII', user=SYSDBA, password=masterkey]
3 #text
act = <firebird.qa.plugin.Action pytest object at [hex]>
capsys = <_pytest.capture.CaptureFixture pytest object at [hex]>

    @pytest.mark.version('>=6.0')
    def test_1(act: Action, capsys):
    
        with act.db.connect() as con:
            cur=con.cursor()
            cur.execute('select mon$server_pid as p from mon$attachments where mon$attachment_id = current_connection')
            fb_pid = int(cur.fetchone()[0])
    
            times_map = {}
            for i in range(0, N_MEASURES):
                fb_info_init = psutil.Process(fb_pid).cpu_times()
                cur.callproc( 'sp_gen_hash', (N_HASH_EVALUATE_COUNT,) )
                fb_info_curr = psutil.Process(fb_pid).cpu_times()
                times_map[ 'hash_eval', i ]  = max(fb_info_curr.user - fb_info_init.user, 0.000001)
    
                fb_info_init = psutil.Process(fb_pid).cpu_times()
                cur.callproc( 'sp_udr_call', (N_UDR_CALLS_COUNT,) )
                fb_info_curr = psutil.Process(fb_pid).cpu_times()
                times_map[ 'udr_call', i ]  = max(fb_info_curr.user - fb_info_init.user, 0.000001)
    
    
        sp_gen_hash_median = median([v for k,v in times_map.items() if k[0] == 'hash_eval'])
        sp_udr_call_median = median([v for k,v in times_map.items() if k[0] == 'udr_call'])
    
        median_ratio = sp_udr_call_median / sp_gen_hash_median
    
        print( 'Medians ratio: ' + ('acceptable' if median_ratio <= MAX_RATIO else '/* perf_issue_tag */ POOR: %s, more than threshold: %s' % ( '{:9g}'.format(median_ratio), '{:9g}'.format(MAX_RATIO) ) ) )
        if median_ratio > MAX_RATIO:
            print(f'CPU times for each of {N_MEASURES} measures:')
            for sp_name in ('hash_eval', 'udr_call', ):
                print(f'{sp_name=}:')
                for p in [v for k,v in times_map.items() if k[0] == sp_name]:
                    print(p)
    
        act.expected_stdout = expected_stdout
        act.stdout = capsys.readouterr().out
>       assert act.clean_stdout == act.clean_expected_stdout
E       AssertionError: assert   
E         - Medians ratio: acceptable
E         + Medians ratio: /* perf_issue_tag */ POOR:   4.63889, more than threshold:       0.4
E         + CPU times for each of 21 measures:
E         + sp_name='hash_eval':
E         + 0.37
E         + 0.3999999999999999
E         + 0.34000000000000075
E         + 0.33999999999999986
E         + 0.35999999999999943
E         + 0.40000000000000036
E         + 0.35999999999999943
E         + 0.3899999999999988
E         + 0.379999999999999
E         + 0.3500000000000014
E         + 0.33999999999999986
E         + 0.46000000000000085
E         + 0.370000000000001
E         + 0.4499999999999993
E         + 0.370000000000001
E         + 0.33999999999999986
E         + 0.35999999999999943
E         + 0.35999999999999943
E         + 0.3399999999999963
E         + 0.37999999999999545
E         + 0.35999999999999943
E         + sp_name='udr_call':
E         + 1.62
E         + 1.6199999999999997
E         + 1.67
E         + 1.67
E         + 1.6500000000000004
E         + 1.6799999999999997
E         + 1.6800000000000015
E         + 1.6100000000000012
E         + 1.6499999999999986
E         + 1.6900000000000013
E         + 1.629999999999999
E         + 1.6899999999999977
E         + 1.6700000000000017
E         + 1.6999999999999993
E         + 1.6799999999999997
E         + 1.8000000000000007
E         + 1.8100000000000023
E         + 1.6499999999999986
E         + 1.8000000000000043
E         + 1.6100000000000065
E         + 1.8200000000000003

tests/bugs/gh_7989_test.py:152: AssertionError
Full history of outcomes and elapsed time, ms:
NN SNAP_INFO CS_outcome SS_outcome CS_run_time SS_run_time CS_run_beg CS_run_end SS_run_beg SS_run_end
1 6.0.0.892 2025.07.02 10f7d F F 43382 71837 2025.07.03 01:44:13.646 2025.07.03 01:44:57.028 2025.07.02 23:08:46.558 2025.07.02 23:09:58.395
2 6.0.0.889 2025.07.01 969ac F F 44883 69557 2025.07.02 02:12:09.130 2025.07.02 02:12:54.013 2025.07.01 23:22:06.242 2025.07.01 23:23:15.799
3 6.0.0.884 2025.06.30 f7e5f F F 43751 71832 2025.07.01 02:12:28.116 2025.07.01 02:13:11.867 2025.06.30 23:30:41.486 2025.06.30 23:31:53.318
4 6.0.0.881 2025.06.27 7035d F F 45814 71314 2025.06.30 02:02:38.833 2025.06.30 02:03:24.647 2025.06.29 23:17:47.961 2025.06.29 23:18:59.275
5 6.0.0.877 2025.06.26 8e38f F F 43660 71977 2025.06.27 01:41:44.664 2025.06.27 01:42:28.324 2025.06.26 23:08:49.005 2025.06.26 23:10:00.982
6 6.0.0.876 2025.06.25 b1bec F F 43711 71334 2025.06.26 01:45:34.639 2025.06.26 01:46:18.350 2025.06.25 23:10:44.100 2025.06.25 23:11:55.434
7 6.0.0.863 2025.06.24 c3c20 F F 43676 72162 2025.06.25 01:45:52.900 2025.06.25 01:46:36.576 2025.06.24 23:10:28.039 2025.06.24 23:11:40.201
8 6.0.0.858 2025.06.23 8d6f7 F F 43322 71268 2025.06.24 01:46:14.604 2025.06.24 01:46:57.926 2025.06.23 23:10:37.716 2025.06.23 23:11:48.984
9 6.0.0.849 2025.06.20 7b79c F F 44099 74560 2025.06.21 01:57:46.613 2025.06.21 01:58:30.712 2025.06.20 23:19:45.054 2025.06.20 23:20:59.614
10 6.0.0.848 2025.06.19 c483c F F 44101 74992 2025.06.20 01:54:07.334 2025.06.20 01:54:51.435 2025.06.19 23:16:33.089 2025.06.19 23:17:48.081
11 6.0.0.845 2025.06.18 22b12 F F 44567 75830 2025.06.19 02:02:46.191 2025.06.19 02:03:30.758 2025.06.18 23:19:38.338 2025.06.18 23:20:54.168
12 6.0.0.843 2025.06.16 995f4 F F 45113 65901 2025.06.18 02:01:00.606 2025.06.18 02:01:45.719 2025.06.17 23:22:10.514 2025.06.17 23:23:16.415
13 6.0.0.840 2025.06.14 29bca F F 44087 74125 2025.06.16 01:52:49.635 2025.06.16 01:53:33.722 2025.06.15 23:13:59.417 2025.06.15 23:15:13.542
14 6.0.0.838 2025.06.13 0e28a F F 44852 73947 2025.06.14 02:05:51.294 2025.06.14 02:06:36.146 2025.06.13 23:21:36.802 2025.06.13 23:22:50.749
15 6.0.0.835 2025.06.12 2cf29 F F 44171 53393 2025.06.13 02:05:51.089 2025.06.13 02:06:35.260 2025.06.12 23:26:05.609 2025.06.12 23:26:59.002
16 6.0.0.834 2025.06.11 e889f F F 44731 62345 2025.06.12 02:01:01.832 2025.06.12 02:01:46.563 2025.06.11 23:22:03.011 2025.06.11 23:23:05.356
17 6.0.0.800 2025.06.10 1f226 P P 18838 17502 2025.06.11 00:28:03.820 2025.06.11 00:28:22.658 2025.06.10 22:20:49.071 2025.06.10 22:21:06.573
18 6.0.0.799 2025.06.07 be644 P P 10911 17546 2025.06.10 00:29:59.535 2025.06.10 00:30:10.446 2025.06.09 22:20:24.118 2025.06.09 22:20:41.664
19 6.0.0.797 2025.06.06 303e8 P P 17599 20083 2025.06.07 00:33:35.559 2025.06.07 00:33:53.158 2025.06.06 22:19:51.915 2025.06.06 22:20:11.998
20 6.0.0.795 2025.05.29 7a71a P P 11527 17832 2025.06.06 00:28:33.911 2025.06.06 00:28:45.438 2025.06.05 22:19:05.843 2025.06.05 22:19:23.675
21 6.0.0.792 2025.05.28 b4327 P P 18904 22202 2025.05.29 00:42:07.794 2025.05.29 00:42:26.698 2025.05.28 22:21:51.132 2025.05.28 22:22:13.334
22 6.0.0.791 2025.05.27 02db8 P P 12334 17373 2025.05.28 00:39:39.530 2025.05.28 00:39:51.864 2025.05.27 22:21:05.661 2025.05.27 22:21:23.034
23 6.0.0.789 2025.05.21 64051 P P 14321 18803 2025.05.25 00:32:20.551 2025.05.25 00:32:34.872 2025.05.24 22:20:17.295 2025.05.24 22:20:36.098
24 6.0.0.787 2025.05.20 230ad P P 11777 18421 2025.05.21 00:29:31.165 2025.05.21 00:29:42.942 2025.05.20 22:18:41.638 2025.05.20 22:19:00.059
25 6.0.0.783 2025.05.12 37320 P P 12264 12381 2025.05.19 12:02:51.633 2025.05.19 12:03:03.897 2025.05.19 10:07:38.231 2025.05.19 10:07:50.612

Elapsed time, ms. Chart for last 25 runs:

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