def main():
if True:
os.chdir(constants.BENCH_BASE_DIR)
for i in range(30):
try:
runCommand('hg pull -u > hgupdate.log')
except RuntimeError:
message(' retry...')
time.sleep(60.0)
else:
s = open('hgupdate.log', 'r').read()
if s.find('not updating') != -1:
raise RuntimeError('hg did not update: %s' % s)
else:
break
else:
raise RuntimeError('failed to run hg pull -u')
os.chdir('%s/%s' % (constants.BASE_DIR, NIGHTLY_DIR))
runCommand('svn cleanup')
open('update.log',
'ab').write('\n\n[%s]: update' % datetime.datetime.now())
for i in range(30):
try:
runCommand('svn update > update.log 2>&1')
except RuntimeError:
message(' retry...')
time.sleep(60.0)
else:
svnRev = int(
reSVNRev.search(open('update.log', 'rb').read()).group(1))
print 'SVN rev is %s' % svnRev
break
else:
raise RuntimeError('svn update failed')
runCommand('%s clean > clean.log 2>&1' % constants.ANT_EXE)
runCommand('%s compile > compile.log 2>&1' % constants.ANT_EXE)
MEDIUM_LINE_FILE = constants.NIGHTLY_MEDIUM_LINE_FILE
MEDIUM_INDEX_NUM_DOCS = constants.NIGHTLY_MEDIUM_INDEX_NUM_DOCS
mediumSource = competition.Data('wikimedium', MEDIUM_LINE_FILE,
MEDIUM_INDEX_NUM_DOCS,
constants.WIKI_MEDIUM_TASKS_FILE)
comp = competition.Competition()
index = comp.newIndex(NIGHTLY_DIR, mediumSource)
c = comp.competitor(id, NIGHTLY_DIR, index=index)
r = benchUtil.RunAlgs(constants.JAVA_COMMAND, True)
r.compile(c)
self.stddevReopenTime,
self.qtCount,
self.totalDocs,
self.totalReopens,
self.totalSearches,
self.totalUpdateTime)
if __name__ == '__main__':
sourceData = competition.sourceData()
sourceData.tasksFile = benchUtil.getArg('-tasks', None, True)
if sourceData.tasksFile is None:
raise RuntimeError('No tasks file defined: -tasks [file]')
comp = competition.Competition(randomSeed=0)
index = comp.newIndex(
constants.TRUNK_CHECKOUT,
sourceData,
postingsFormat='Lucene90',
idFieldPostingsFormat='Memory',
grouping=False,
doDeletions=False,
addDVFields=True,
)
c = competition.Competitor('base', constants.TRUNK_CHECKOUT)
r = benchUtil.RunAlgs(constants.JAVA_COMMAND, False, False)
r.compile(c)
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import competition
# simple example that runs benchmark with WIKI_MEDIUM source and taks files
# Baseline here is ../lucene-solr versus ../patch
if __name__ == '__main__':
sourceData = competition.sourceData()
comp = competition.Competition(
randomSeed=0xdeadbeef,
jvmCount=5, # num of iter
taskRepeatCount=32) # repeat task in every iter
#index = comp.newIndex('lucene-solr-6.6.5', sourceData)
index = comp.newIndex('lucene-solr-6.6.5',
sourceData,
facets=(('taxonomy:Date', 'Date'), ('taxonomy:Month',
'Month'),
('taxonomy:DayOfYear',
'DayOfYear'), ('sortedset:Month', 'Month'),
('sortedset:DayOfYear', 'DayOfYear'))) #,
# Added by Wenbin
#directory="MMapDirectory", # default: MMapDirectory
#maxConcurrentMerges=3, # use 1 for spinning-magnets and 3 for fast SSD
#optimize=True)
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import competition
# simple example that runs benchmark with WIKI_MEDIUM source and taks files
# Baseline here is ../trunk versus ../patch
if __name__ == '__main__':
sourceData = competition.sourceData()
comp = competition.Competition()
index = comp.newIndex('lucene_baseline', sourceData)
# create a competitor named baseline with sources in the ../trunk folder
comp.competitor('baseline', 'lucene_baseline', index=index)
# use the same index here
# create a competitor named my_modified_version with sources in the ../patch folder
# note that we haven't specified an index here, luceneutil will automatically use the index from the base competitor for searching
# while the codec that is used for running this competitor is taken from this competitor.
comp.competitor('my_modified_version', 'lucene_candidate', index=index)
# start the benchmark - this can take long depending on your index and machines
comp.benchmark("trunk_vs_patch")
p = player.StatisticPlayer([50, 50, 20, 20])
p1 = player.StatisticPlayer([60, 30, 5, 5])
p2 = player.StatisticPlayer([33, 33, 10, 33])
p3 = player.StatisticPlayer([33, 33, 20, 5])
p4 = player.Player("random")
data = pd.HDFStore('Statistic.h5')
data['results'] = pd.DataFrame()
i = 0
for x in [70]:
for y in [70]:
for z in [70]:
for a in [10, 25, 40, 60, 70]:
start = time.time()
p = player.StatisticPlayer([x, y, z, a])
c = competition.Competition(game_size=4,
games_number=30,
players=[p],
game_type=game.NO_SCREEN)
c.play()
c.show_results(dont_show=True)
data['results'] = data['results'].append(c.results,
ignore_index=True)
print(max(c.results['max_score']))
i = i + 1
print("finished " + str(i) + ' out of 625 in ' +
str(time.time() - start))
data.close()
print("tiral")
team_stats = {}
for i, name in enumerate(raw_teams.keys()):
teams.append(team.Team(i, name))
teams[i].set_scores(raw_teams[name])
if name not in team_stats:
team_stats[name] = {}
team_stats[name]["wins"] = np.zeros((nschedules), dtype=np.int32)
team_stats[name]["ranks"] = np.zeros((nschedules), dtype=np.int32)
for team in teams:
print(team)
nteams = len(teams)
scheds = schedules.Schedules(nteams, nweeks, nschedules)
for j, sched in enumerate(scheds.schedules):
comp = competition.Competition(sched, teams)
for i, team in enumerate(comp.teams):
team_stats[team.name]["wins"][j] = team.wins
team_stats[team.name]["ranks"][j] = i
# print(comp)
for team, stats in team_stats.items():
team_stats[team]["pdf"] = np.bincount(stats['ranks'],
minlength=nteams) / nschedules
team_stats[team]["cdf"] = np.cumsum(team_stats[team]["pdf"])
# print("{:20}".format(team), team_stats[team]["pdf"] )
# team_stats = sorted(team_stats.items(), key = lambda kv: kv[1]["wins"].mean(), reverse=True)
team_stats = sorted(team_stats.items(),
key=lambda kv: kv[1]["cdf"][3],
reverse=True)
