Hello,
Consider the following function:
def check_s3_refcounts():
"""Check s3 object reference counts"""
global found_errors
log.info('Checking S3 object reference counts...')
for (key, refcount) in conn.query("SELECT id, refcount FROM s3_objects"):
refcount2 = conn.get_val("SELECT COUNT(inode) FROM blocks WHERE
s3key=?",
(key,))
if refcount != refcount2:
log_error("S3 object %s has invalid refcount, setting from %d to
%d",
key, refcount, refcount2)
found_errors = True
if refcount2 != 0:
conn.execute("UPDATE s3_objects SET refcount=? WHERE id=?",
(refcount2, key))
else:
# Orphaned object will be picked up by check_keylist
conn.execute('DELETE FROM s3_objects WHERE id=?', (key,))
When I ran cProfile.Profile().runcall() on it, I got the following
result:
ncalls tottime percall cumtime percall filename:lineno(function)
1 7639.962 7639.962 7640.269 7640.269 fsck.py:270(check_s3_refcounts)
So according to the profiler, the entire 7639 seconds where spent
executing the function itself.
How is this possible? I really don't see how the above function can
consume any CPU time without spending it in one of the called
sub-functions.
Puzzled,
-Nikolaus
--
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