Virgil Dupras <[EMAIL PROTECTED]> added the comment:
I had a 54 mb hotshot profile lying around, and it is indeed very long to load,
so I ran a profiling session of
hotshot.stats.load(MY_BIG_FILE) with python and stdlib of r61515, and here are
the results (the resulting prof file
is 27 mb):
96541166 function calls in 299.936 CPU seconds
Ordered by: cumulative time
List reduced from 30 to 15 due to restriction <15>
ncalls tottime percall cumtime percall filename:lineno(function)
1 0.000 0.000 299.936 299.936 stats.py:11(load)
1 95.089 95.089 299.936 299.936 stats.py:22(load)
27583167 51.183 0.000 61.815 0.000 log.py:95(next)
13791583 59.314 0.000 59.314 0.000
profile.py:328(trace_dispatch_return)
13791583 35.014 0.000 42.910 0.000 stats.py:54(new_frame)
13791584 40.807 0.000 40.807 0.000
profile.py:295(trace_dispatch_call)
13791583 10.632 0.000 10.632 0.000 log.py:138(_decode_location)
13791583 7.897 0.000 7.897 0.000 stats.py:87(__init__)
1 0.000 0.000 0.000 0.000 pstats.py:73(__init__)
1 0.000 0.000 0.000 0.000 pstats.py:95(init)
1 0.000 0.000 0.000 0.000 pstats.py:138(get_top_level_stats)
1 0.000 0.000 0.000 0.000 log.py:24(__init__)
1 0.000 0.000 0.000 0.000 pstats.py:117(load_stats)
1 0.000 0.000 0.000 0.000 profile.py:436(create_stats)
1 0.000 0.000 0.000 0.000 profile.py:440(snapshot_stats)
96541166 function calls in 299.936 CPU seconds
Ordered by: internal time
List reduced from 30 to 20 due to restriction <20>
ncalls tottime percall cumtime percall filename:lineno(function)
1 95.089 95.089 299.936 299.936 stats.py:22(load)
13791583 59.314 0.000 59.314 0.000
profile.py:328(trace_dispatch_return)
27583167 51.183 0.000 61.815 0.000 log.py:95(next)
13791584 40.807 0.000 40.807 0.000
profile.py:295(trace_dispatch_call)
13791583 35.014 0.000 42.910 0.000 stats.py:54(new_frame)
13791583 10.632 0.000 10.632 0.000 log.py:138(_decode_location)
13791583 7.897 0.000 7.897 0.000 stats.py:87(__init__)
1 0.000 0.000 0.000 0.000 log.py:24(__init__)
1 0.000 0.000 0.000 0.000 profile.py:440(snapshot_stats)
1 0.000 0.000 0.000 0.000 pstats.py:138(get_top_level_stats)
30 0.000 0.000 0.000 0.000 pstats.py:484(func_std_string)
5 0.000 0.000 0.000 0.000 posixpath.py:306(normpath)
1 0.000 0.000 299.936 299.936 stats.py:11(load)
24 0.000 0.000 0.000 0.000 stats.py:80(__init__)
1 0.000 0.000 0.000 0.000 pstats.py:117(load_stats)
1 0.000 0.000 0.000 0.000 profile.py:402(simulate_call)
1 0.000 0.000 0.000 0.000 profile.py:118(_get_time_resource)
1 0.000 0.000 0.000 0.000 pstats.py:73(__init__)
1 0.000 0.000 0.000 0.000 pstats.py:95(init)
1 0.000 0.000 0.000 0.000 profile.py:166(__init__)
So the bulk of the time seems to be taken by the sheer number of
trace_dispatch_return and trace_dispatch_call
calls. I took a quick look, but I'm not sure I can do anything to make it
faster. If no one else has any idea, I
suggest just closing the ticket.
----------
nosy: +vdupras
____________________________________
Tracker <[EMAIL PROTECTED]>
<http://bugs.python.org/issue984219>
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