#!/usr/bin/env python # # Public Domain 2014-2015 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 check_scenarios(scenes): """ Make sure all scenarios have unique names """ assert len(scenes) == len(dict(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 scenes: for scenb in result: # 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 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