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#!/usr/bin/env python
#
# Public Domain 2014-2016 MongoDB, Inc.
# Public Domain 2008-2014 WiredTiger, Inc.
#
# This is free and unencumbered software released into the public domain.
#
# Anyone is free to copy, modify, publish, use, compile, sell, or
# distribute this software, either in source code form or as a compiled
# binary, for any purpose, commercial or non-commercial, and by any
# means.
#
# In jurisdictions that recognize copyright laws, the author or authors
# of this software dedicate any and all copyright interest in the
# software to the public domain. We make this dedication for the benefit
# of the public at large and to the detriment of our heirs and
# successors. We intend this dedication to be an overt act of
# relinquishment in perpetuity of all present and future rights to this
# software under copyright law.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
# MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
# IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR
# OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,
# ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
# OTHER DEALINGS IN THE SOFTWARE.
import testscenarios
import suite_random
# wtscenarios.py
# Support scenarios based testing
def powerrange(start, stop, mult):
"""
Like xrange, generates a range from start to stop.
Unlike xrange, the range is inclusive of stop,
each step is multiplicative, and as a special case,
the stop value is returned as the last item.
"""
val = start
while val <= stop:
yield val
newval = val * mult
if val < stop and newval > stop:
val = stop
else:
val = newval
def log2chr(val):
"""
For the log-base 2 of val, return the numeral or letter
corresponding to val (which is < 36). Hence, 1 return '0',
2 return '1', 2*15 returns 'f', 2*16 returns 'g', etc.
"""
p = 0
while val >= 2:
p += 1
val /= 2
if p < 10:
return chr(ord('0') + p)
else:
return chr(ord('a') + p - 10)
megabyte = 1024 * 1024
def make_scenarios(*args, **kwargs):
"""
The standard way to create scenarios for WT tests.
Scenarios can be combined by listing them all as arguments.
A final prune= and/or prunelong= argument may be given that
forces the list of entries in the scenario to be pruned.
The result is a (combined) scenario that has been checked
for name duplicates and has been given names and numbers.
"""
scenes = multiply_scenarios('.', *args)
pruneval = None
prunelong = None
for key in kwargs:
if key == 'prune':
pruneval = kwargs[key]
elif key == 'prunelong':
prunelong = kwargs[key]
else:
raise AssertionError(
'make_scenarios: unexpected named arg: ' + key)
if pruneval != None or prunelong != None:
pruneval = pruneval if pruneval != None else -1
prunelong = prunelong if prunelong != None else -1
scenes = prune_scenarios(scenes, pruneval, prunelong)
return number_scenarios(scenes)
def check_scenarios(scenes):
"""
Make sure all scenarios have unique case insensitive names
"""
assert len(scenes) == len(dict((k.lower(), v) for k, v in scenes))
return scenes
def multiply_scenarios(sep, *args):
"""
Create the cross product of two lists of scenarios
"""
result = None
for scenes in args:
if result == None:
result = scenes
else:
total = []
for scena in result:
for scenb in scenes:
# Create a merged scenario with a concatenated name
name = scena[0] + sep + scenb[0]
tdict = {}
tdict.update(scena[1])
tdict.update(scenb[1])
# If there is a 'P' value, it represents the
# probability that we want to use this scenario
# If both scenarios list a probability, multiply them.
if 'P' in scena[1] and 'P' in scenb[1]:
P = scena[1]['P'] * scenb[1]['P']
tdict['P'] = P
total.append((name, tdict))
result = total
return check_scenarios(result)
def prune_sorter_key(scene):
"""
Used by prune_scenerios to extract key for sorting.
The key is the saved random value multiplied by
the probability of choosing.
"""
p = 1.0
if 'P' in scene[1]:
p = scene[1]['P']
return p * scene[1]['_rand']
def prune_resort_key(scene):
"""
Used by prune_scenerios to extract the original ordering key for sorting.
"""
return scene[1]['_order']
def set_long_run(islong):
global _is_long_run
_is_long_run = islong
def prune_scenarios(scenes, default_count = -1, long_count = -1):
"""
Use listed probabilities for pruning the list of scenarios.
That is, the highest probability (value of P in the scendario)
are chosen more often. With just one argument, only scenarios
with P > .5 are returned half the time, etc. A second argument
limits the number of scenarios. When a third argument is present,
it is a separate limit for a long run.
"""
global _is_long_run
r = suite_random.suite_random()
result = []
if default_count == -1:
# Missing second arg - return those with P == .3 at
# 30% probability, for example.
for scene in scenes:
if 'P' in scene[1]:
p = scene[1]['P']
if p < r.rand_float():
continue
result.append(scene)
return result
else:
# With at least a second arg present, we'll want a specific count
# of items returned. So we'll sort them all and choose
# the top number. Not the most efficient solution,
# but it's easy.
if _is_long_run and long_count != -1:
count = long_count
else:
count = default_count
l = len(scenes)
if l <= count:
return scenes
if count == 0:
return []
order = 0
for scene in scenes:
scene[1]['_rand'] = r.rand_float()
scene[1]['_order'] = order
order += 1
scenes = sorted(scenes, key=prune_sorter_key) # random sort driven by P
scenes = scenes[l-count:l] # truncate to get best
scenes = sorted(scenes, key=prune_resort_key) # original order
for scene in scenes:
del scene[1]['_rand']
del scene[1]['_order']
return check_scenarios(scenes)
def number_scenarios(scenes):
"""
Add a 'scenario_number' and 'scenario_name' variable to each scenario.
The hash table for each scenario is altered!
"""
count = 0
for scene in scenes:
scene[1]['scenario_name'] = scene[0]
scene[1]['scenario_number'] = count
count += 1
return check_scenarios(scenes)
def quick_scenarios(fieldname, values, probabilities):
"""
Quickly build common scenarios, like:
[('foo', dict(somefieldname='foo')),
('bar', dict(somefieldname='bar')),
('boo', dict(somefieldname='boo'))]
via a call to:
quick_scenario('somefieldname', ['foo', 'bar', 'boo'])
"""
result = []
if probabilities == None:
plen = 0
else:
plen = len(probabilities)
ppos = 0
for value in values:
if ppos >= plen:
d = dict([[fieldname, value]])
else:
p = probabilities[ppos]
ppos += 1
d = dict([[fieldname, value],['P', p]])
result.append((str(value), d))
return result
class wtscenario:
"""
A set of generators for different test scenarios
"""
@staticmethod
def session_create_scenario():
"""
Return a set of scenarios with the name of this method
'session_create_scenario' as the name of instance
variable containing a wtscenario object. The wtscenario
object can be queried to get a config string.
Each scenario is named according to the shortName() method.
"""
s = [
('default', dict(session_create_scenario=wtscenario())) ]
for imin in powerrange(512, 512*megabyte, 1024):
for imax in powerrange(imin, 512*megabyte, 1024):
for lmin in powerrange(512, 512*megabyte, 1024):
for lmax in powerrange(lmin, 512*megabyte, 1024):
for cache in [megabyte, 32*megabyte, 1000*megabyte]:
scen = wtscenario()
scen.ioverflow = max(imin / 40, 40)
scen.imax = imax
scen.loverflow = max(lmin / 40, 40)
scen.lmax = lmax
scen.cache_size = cache
s.append((scen.shortName(), dict(session_create_scenario=scen)))
return make_scenarios(s)
def shortName(self):
"""
Return a name of a scenario, based on the 'log2chr-ed numerals'
representing the four values for {internal,leaf} {minimum, maximum}
page size.
"""
return 'scen_' + log2chr(self.ioverflow) + log2chr(self.imax) + log2chr(self.loverflow) + log2chr(self.lmax) + log2chr(self.cache_size)
def configString(self):
"""
Return the associated configuration string
"""
res = ''
if hasattr(self, 'ioverflow'):
res += ',internal_item_max=' + str(self.ioverflow)
if hasattr(self, 'imax'):
res += ',internal_page_max=' + str(self.imax)
if self.imax < 4*1024:
res += ',allocation_size=512'
if hasattr(self, 'loverflow'):
res += ',leaf_item_max=' + str(self.loverflow)
if hasattr(self, 'lmax'):
res += ',leaf_page_max=' + str(self.lmax)
if self.lmax < 4*1024:
res += ',allocation_size=512'
return res
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