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authorantirez <antirez@gmail.com>2014-03-31 10:01:42 +0200
committerantirez <antirez@gmail.com>2014-03-31 10:09:43 +0200
commit7f9d289e100725a8eab67ec1a0d069e8d1a6221e (patch)
treeb0579cb4af42613b8b03c937ed0364574a4a0027
parent307a189900c06bb4f76638277275f70f2e480558 (diff)
downloadredis-7f9d289e100725a8eab67ec1a0d069e8d1a6221e.tar.gz
hll-gnuplot-graph.rb added to plot HyperLogLog error graphs.
-rw-r--r--utils/hyperloglog/hll-gnuplot-graph.rb68
1 files changed, 68 insertions, 0 deletions
diff --git a/utils/hyperloglog/hll-gnuplot-graph.rb b/utils/hyperloglog/hll-gnuplot-graph.rb
new file mode 100644
index 000000000..1cccbf4be
--- /dev/null
+++ b/utils/hyperloglog/hll-gnuplot-graph.rb
@@ -0,0 +1,68 @@
+# hll-err.rb - Copyright (C) 2014 Salvatore Sanfilippo
+# BSD license, See the COPYING file for more information.
+#
+# This program is suited to output average and maximum errors of
+# the Redis HyperLogLog implementation in a format suitable to print
+# graphs using gnuplot.
+
+require 'rubygems'
+require 'redis'
+require 'digest/sha1'
+
+# Generate an array of [cardinality,relative_error] pairs
+# in the 0 - max range with step of 1000*step.
+#
+# 'r' is the Redis object used to perform the queries.
+# 'seed' must be different every time you want a test performed
+# with a different set. The function guarantees that if 'seed' is the
+# same, exactly the same dataset is used, and when it is different,
+# a totally unrelated different data set is used (without any common
+# element in practice).
+def run_experiment(r,seed,max,step)
+ r.del('hll')
+ i = 0
+ samples = []
+ while i < max do
+ step.times {
+ elements = []
+ 1000.times {
+ ele = Digest::SHA1.hexdigest(i.to_s+seed.to_s)
+ elements << ele
+ i += 1
+ }
+ r.hlladd('hll',*elements)
+ }
+ approx = r.hllcount('hll')
+ err = approx-i
+ rel_err = 100.to_f*err/i
+ samples << [i,rel_err]
+ end
+ samples
+end
+
+def filter_samples(numsets,filter)
+ r = Redis.new
+ dataset = {}
+ (0...numsets).each{|i|
+ dataset[i] = run_experiment(r,i,100000,1)
+ }
+ dataset[0].each_with_index{|ele,index|
+ card,err=ele
+ if filter == :max
+ (1...numsets).each{|i|
+ err = dataset[i][index][1] if err < dataset[i][index][1]
+ }
+ elsif filter == :avg
+ (1...numsets).each{|i|
+ err += dataset[i][index][1]
+ }
+ err /= numsets
+ else
+ raise "Unknown filter #{filter}"
+ end
+ puts "#{card} #{err}"
+ }
+end
+
+filter_samples(100,:max)
+#filter_samples(100,:avg)