def display_status(self):
"""
Display current status
"""
self.switch_to_old()
delta = self.state['end_time'] - self.state['start_time']
self.state['cumulated'] += delta
# Every estimate-every chunk, we revise our progress indicator
cur = int(self.state['done'] / self.options['step'])
last = int(
(self.state['done'] - self.state['nb']) / self.options['step'])
cur /= self.options['estimate-every']
last /= self.options['estimate-every']
self.state['remaining'] -= self.state['nb']
if cur != last:
old = self.state['remaining']
self.state['remaining'] = self.count(self.state['since'])
self.state['drift'] = self.state['remaining'] - old
self.state['cumulated_drift'] += self.state['drift']
remaining = self.state['remaining']
drift = self.state['cumulated_drift']
if not drift:
total = self.state['initial']
else:
drift_rate = float(drift) / self.state['done']
if drift_rate > 1.0:
print "!!WARNING!! Drift rate is >1.0. Operation will never finish."
return
# We need to compute a sum of a serie, since everytime
# we'll index n items, we'll get drift_rate * n additional
# items
# So we need : sum_n=0^+oo (drift_rate^k) * remaining
# Which is ... 1/(1-drift_rate) * remaining, as we all know
cumulated_drift_rate = 1 / (1 - drift_rate)
total = self.state['initial'] * cumulated_drift_rate
drift_estimated = remaining * cumulated_drift_rate
done = self.state['done']
percent = total and (done * 100.0 / total) or 100.0
cumulated = self.state['cumulated']
utils.print_eta(percent, cumulated)
if drift:
print " -> %d done, drift rate : %.2f, estimated total: %d, actual remaining: %d, estimated remaining: %d" % (
done, drift_rate, total, remaining, drift_estimated)
def display_status(self):
"""
Display current status
"""
self.switch_to_old()
delta = self.state['end_time'] - self.state['start_time']
self.state['cumulated'] += delta
# Every estimate-every chunk, we revise our progress indicator
cur = int(self.state['done'] / self.options['step'])
last = int((self.state['done'] - self.state['nb']) / self.options['step'])
cur /= self.options['estimate-every']
last /= self.options['estimate-every']
self.state['remaining'] -= self.state['nb']
if cur != last:
old = self.state['remaining']
self.state['remaining'] = self.count(self.state['since'])
self.state['drift'] = self.state['remaining'] - old
self.state['cumulated_drift'] += self.state['drift']
remaining = self.state['remaining']
drift = self.state['cumulated_drift']
if not drift:
total = self.state['initial']
else:
drift_rate = float(drift) / self.state['done']
if drift_rate > 1.0:
print "!!WARNING!! Drift rate is >1.0. Operation will never finish."
return
# We need to compute a sum of a serie, since everytime
# we'll index n items, we'll get drift_rate * n additional
# items
# So we need : sum_n=0^+oo (drift_rate^k) * remaining
# Which is ... 1/(1-drift_rate) * remaining, as we all know
cumulated_drift_rate = 1/(1-drift_rate)
total = self.state['initial'] * cumulated_drift_rate
drift_estimated = remaining * cumulated_drift_rate
done = self.state['done']
percent = total and (done * 100.0 / total) or 100.0
cumulated = self.state['cumulated']
utils.print_eta(percent, cumulated)
if drift:
print " -> %d done, drift rate : %.2f, estimated total: %d, actual remaining: %d, estimated remaining: %d" % (done, drift_rate, total, remaining, drift_estimated)
def process_table(self, table):
"""
Process on given table
"""
cursor = config.orm.cursor()
query = 'SELECT min(id), max(id) FROM %s WHERE %s IS NULL' % (table,
self.target)
cursor.execute(query)
start_time = time.time()
idmin, idmax = cursor.fetchone()
if idmin and idmax:
print "Processing table %s from id %d to %d" % (table, idmin, idmax)
start = idmin
while start <= idmax:
end = min(start + self.options['step'], idmax) + 1
self.iteration(table, start, end)
start = end
time.sleep(self.options['delay'])
timedelta = time.time() - start_time
percent = float(start - idmin - 1) / float(idmax - idmin) * 100.0
print_eta(percent, timedelta)
else:
print "Table %s is good, nothing to do" % table