#!/usr/bin/env python
#
# this is a fairly trivial parser of the ftrace function stack trace output
# the idea is to find the most common stack traces that lead to calling
# given function, even those that don't use much CPU time and won't
# show up in other profilers.
#
# It assumes ftrace output looks like this:
#       some text including the function name
# <= func
# <= func2
# <= func3
#       some text including the function name
# <= func4
# <= func5
# <= func6
#
# The traces above would generate two histogram entries, one for
# func,func2,func3 and one for func4,func5,fun6
#

import sys, os, signal

stacks = {}

last = []
printed = False

def summary(arg1, arg2):
    global printed;

    printed = True
    count = {}

    for lines, c in stacks.items():
        count.setdefault(c, []).append(lines + ' ===========\n')

    limit = 50
    keys = count.keys()
    keys.sort()
    for x in keys.__reversed__():
        print "%d hits: \n%s" % (x, "".join(count[x]))
        limit -= 1
        if limit <= 0:
            break
    sys.exit(0)

signal.signal(signal.SIGTERM, summary)
signal.signal(signal.SIGINT, summary)

while True:
    try:
        l = sys.stdin.readline()
    except:
        break

    if not l:
        break

    if l[0] == '#':
        continue
    if not l.startswith(' <='):
        if last:
            lines = ''.join(last)
            val = stacks.get(lines, 0) + 1
            stacks[lines] = val
        # we don't put the header line into the trace because that might
        # have timestamp info in it.
        last = []
    else:
        last.append(l)

if not printed:
    summary(1, 2)