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make poisson sampling slightly faster #1

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Nov 20, 2014
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make poisson sampling slightly faster #1

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26 changes: 16 additions & 10 deletions python/pyspark/rddsampler.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,7 @@

import sys
import random
import math


class RDDSamplerBase(object):
Expand All @@ -37,16 +38,21 @@ def getUniformSample(self):
return self._random.random()

def getPoissonSample(self, mean):
# here we simulate drawing numbers n_i ~ Poisson(lambda = 1/mean) by
# drawing a sequence of numbers delta_j ~ Exp(mean)
num_arrivals = 0
cur_time = self._random.expovariate(mean)

while cur_time < 1.0:
cur_time += self._random.expovariate(mean)
num_arrivals += 1

return num_arrivals
# Using Knuth's algorithm described in http://en.wikipedia.org/wiki/Poisson_distribution
if mean < 20.0: # one exp and k+1 random calls
l = math.exp(-mean)
p = self._random.random()
k = 0
while p > l:
k += 1
p *= self._random.random()
else: # switch to the log domain, k+1 expovariate (random + log) calls
p = self._random.expovariate(mean)
k = 0
while p < 1.0:
k += 1
p += self._random.expovariate(mean)
return k

def func(self, split, iterator):
raise NotImplementedError
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