def pyblume_test_fpp(N):
print ' a. Creating filter'
bloom = pyblume.Filter(1024 * 1024 * 10, 0.000001, "/tmp/pyblume_fpp_test.bf")
print ' b. Loading filter'
start = time.time()
for k in xrange(0, N, 10):
bloom.add(str(k))
end = time.time()
print ' bloom.add: %d/s' % ((N / 10) / (end - start))
print ' c. Computing false positive rate'
fn_count = 0
fp_count = 0
start = time.time()
for k in xrange(0, N):
hit = str(k) in bloom
if hit and k % 10 != 0:
fp_count += 1
elif not hit and k % 10 == 0:
fn_count += 1
end = time.time()
print ' bloom.check: %d/s' % (N / (end - start))
print ' d. %d false positives out of %d trials (p = %0.4f)' % (fp_count, N, float(fp_count) / N)
def pyblume_test_full(N):
print ' a. Creating filter'
bloom = pyblume.Filter(1024 * 512, 0.000001, "/tmp/pyblume_full_test.bf")
print ' b. Loading filter'
start = time.time()
for k in xrange(0, N, 10):
bloom.add(str(k))
end = time.time()
print ' bloom.add: %d/s' % ((N / 10) / (end - start))
def create_filter():
print ' a. Creating filter at "%s"' % (filepath,)
bloom = pyblume.Filter(1024 * 1024 * 10, 0.000001, filepath)
print ' b. Loading filter'
start = time.time()
for k in xrange(0, N, 10):
bloom.add(str(k))
end = time.time()
print ' bloom.add: %d/s' % ((N / 10) / (end - start))
bloom.close()
def pyblume_test_locking(N):
print ' a. Creating filter'
bloom = pyblume.Filter(1024 * 512, 0.000001, "/tmp/pyblume_locking_test.bf")
bloom2 = pyblume.open("/tmp/pyblume_locking_test.bf", for_write=1)
print ' b. Loading filter'
start = time.time()
for k in xrange(0, N, 10):
bloom.add(str(k))
end = time.time()
print ' bloom.add: %d/s' % ((N / 10) / (end - start))
__author__ = 'rakesh'
import pyblume
BLOOM_FILTER_MAX_FILESIZE = 1024 * 1024 * 500
BLOOM_ERROR_RATE = 0.000001
fileloc = "/tmp/test.blume"
bf = pyblume.Filter(BLOOM_FILTER_MAX_FILESIZE, BLOOM_ERROR_RATE, fileloc)
for i in range(313):
bf.add(str(i))
bf.close()
check = [str(j) for j in range(300, 400)]
print check
bf = pyblume.open(fileloc, for_write=False)
for x in check:
if x in bf:
print "Found"
bf.close()
'''
NOTES:
Bloom Filters Description - https://www.pinterest.com/pin/429953095654194981/