def test_holistic(self):
n = int(1e4)
N = int(2e4)
T = 3
print "ScalingTimingBloom with capacity %e and expiration time %ds" % (n, T)
with TimingBlock("Initialization"):
stbf = ScalingTimingBloomFilter(n, decay_time=T, ioloop=self.io_loop)
orig_decay = stbf.decay
def new_decay(*args, **kwargs):
with TimingBlock("Decaying"):
val = orig_decay(*args, **kwargs)
return val
setattr(stbf, "decay", new_decay)
stbf._setup_decay()
stbf.start()
print "State of blooms: %d blooms with expected error %.2f%%" % (len(stbf.blooms), stbf.expected_error()*100.)
with TimingBlock("Adding %d values" % N, N):
for i in xrange(N):
stbf.add(str(i))
last_insert = time.time()
print "State of blooms: %d blooms with expected error %.2f%%" % (len(stbf.blooms), stbf.expected_error()*100.)
with TimingBlock("Testing %d positive values" % N, N):
for i in xrange(N):
assert str(i) in stbf
with TimingBlock("Testing %d negative values" % N, N):
err = 0
for i in xrange(N, 2*N):
if str(i) in stbf:
err += 1
tot_err = err / float(N)
assert tot_err <= stbf.error, "Error is too high: %f > %f" % (tot_err, stbf.error)
try:
t = T - (time.time() - last_insert) + 1
if t > 0:
self.wait(timeout = t)
except:
pass
print "State of blooms: %d blooms with expected error %.2f%%" % (len(stbf.blooms), stbf.expected_error()*100.)
with TimingBlock("Testing %d expired values" % N, N):
err = 0
for i in xrange(N):
if str(i) in stbf:
err += 1
tot_err = err / float(N)
assert tot_err <= stbf.error, "Error is too high: %f > %f" % (tot_err, stbf.error)
assert len(stbf.blooms) == 1, "Decay should have pruned all but one bloom filters: %d blooms left" % len(stbf.blooms)
