1 files changed, 109 insertions, 0 deletions
diff --git a/python/pyspark/statcounter.py b/python/pyspark/statcounter.py
new file mode 100644
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+++ b/python/pyspark/statcounter.py
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+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# 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.
+#
+
+# This file is ported from spark/util/StatCounter.scala
+
+import copy
+import math
+
+class StatCounter(object):
+    
+    def __init__(self, values=[]):
+        self.n = 0L    # Running count of our values
+        self.mu = 0.0  # Running mean of our values
+        self.m2 = 0.0  # Running variance numerator (sum of (x - mean)^2)
+
+        for v in values:
+            self.merge(v)
+            
+    # Add a value into this StatCounter, updating the internal statistics.
+    def merge(self, value):
+        delta = value - self.mu
+        self.n += 1
+        self.mu += delta / self.n
+        self.m2 += delta * (value - self.mu)
+        return self
+
+    # Merge another StatCounter into this one, adding up the internal statistics.
+    def mergeStats(self, other):
+        if not isinstance(other, StatCounter):
+            raise Exception("Can only merge Statcounters!")
+
+        if other is self: # reference equality holds
+            self.merge(copy.deepcopy(other))  # Avoid overwriting fields in a weird order
+        else:
+            if self.n == 0:
+                self.mu = other.mu
+                self.m2 = other.m2
+                self.n = other.n       
+            elif other.n != 0:        
+                delta = other.mu - self.mu
+                if other.n * 10 < self.n:
+                    self.mu = self.mu + (delta * other.n) / (self.n + other.n)
+                elif self.n * 10 < other.n:
+                    self.mu = other.mu - (delta * self.n) / (self.n + other.n)
+                else:
+                    self.mu = (self.mu * self.n + other.mu * other.n) / (self.n + other.n)
+        
+                self.m2 += other.m2 + (delta * delta * self.n * other.n) / (self.n + other.n)
+                self.n += other.n
+        return self
+
+    # Clone this StatCounter
+    def copy(self):
+        return copy.deepcopy(self)
+
+    def count(self):
+        return self.n
+
+    def mean(self):
+        return self.mu
+
+    def sum(self):
+        return self.n * self.mu
+
+    # Return the variance of the values.
+    def variance(self):
+        if self.n == 0:
+            return float('nan')
+        else:
+            return self.m2 / self.n
+
+    #
+    # Return the sample variance, which corrects for bias in estimating the variance by dividing
+    # by N-1 instead of N.
+    #
+    def sampleVariance(self):
+        if self.n <= 1:
+            return float('nan')
+        else:
+            return self.m2 / (self.n - 1)
+
+    # Return the standard deviation of the values.
+    def stdev(self):
+        return math.sqrt(self.variance())
+
+    #
+    # Return the sample standard deviation of the values, which corrects for bias in estimating the
+    # variance by dividing by N-1 instead of N.
+    #
+    def sampleStdev(self):
+        return math.sqrt(self.sampleVariance())
+
+    def __repr__(self):
+        return "(count: %s, mean: %s, stdev: %s)" % (self.count(), self.mean(), self.stdev())
+