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Rig up a query-frequency analyzer with the most commonly seen callstack, including Jinja demangling.

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This commit is contained in:
Ben Rog-Wilhelm 2022-11-10 19:17:30 -06:00 • committed by Ben Rog-Wilhelm
parent 6b55cc1f5b
commit 1437bc3092
6 changed files with 69 additions and 7 deletions
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5
thirdparty/sqlalchemy-easy-profile/easy_profile/reporters.py vendored
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@ -86,6 +86,8 @@ class StreamReporter(Reporter):
summary = "Total queries: {0} in {1:.3}s".format(total, duration)
output += self._info_line("\n{0}\n".format(summary), total)
callstacks = stats["callstacks"]
# Display duplicated sql statements.
#
# Get top counters were value greater than 1 and write to
@ -95,11 +97,12 @@ class StreamReporter(Reporter):
for statement, count in most_common:
if count < 1:
continue
callstack = callstacks[statement].most_common(1)
# Wrap SQL statement and returning a list of wrapped lines
statement = sqlparse.format(
statement, reindent=True, keyword_case="upper"
)
text = "\nRepeated {0} times:\n{1}\n".format(count + 1, statement)
text = "\nRepeated {0} times:\n{1}\nMost common callstack {2} times:\n{3}\n".format(count + 1, statement, callstack[0][1], callstack[0][0])
output += self._info_line(text, count)
self._file.write(output)