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http://github.com/valkey-io/valkey
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89 lines
2.6 KiB
Ruby
89 lines
2.6 KiB
Ruby
# hll-err.rb - Copyright (C) 2014 Salvatore Sanfilippo
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# BSD license, See the COPYING file for more information.
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#
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# This program is suited to output average and maximum errors of
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# the Redis HyperLogLog implementation in a format suitable to print
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# graphs using gnuplot.
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require 'rubygems'
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require 'redis'
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require 'digest/sha1'
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# Generate an array of [cardinality,relative_error] pairs
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# in the 0 - max range, with the specified step.
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#
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# 'r' is the Redis object used to perform the queries.
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# 'seed' must be different every time you want a test performed
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# with a different set. The function guarantees that if 'seed' is the
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# same, exactly the same dataset is used, and when it is different,
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# a totally unrelated different data set is used (without any common
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# element in practice).
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def run_experiment(r,seed,max,step)
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r.del('hll')
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i = 0
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samples = []
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step = 1000 if step > 1000
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while i < max do
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elements = []
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step.times {
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ele = Digest::SHA1.hexdigest(i.to_s+seed.to_s)
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elements << ele
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i += 1
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}
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r.pfadd('hll',elements)
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approx = r.pfcount('hll')
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err = approx-i
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rel_err = 100.to_f*err/i
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samples << [i,rel_err]
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end
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samples
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end
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def filter_samples(numsets,max,step,filter)
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r = Redis.new
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dataset = {}
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(0...numsets).each{|i|
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dataset[i] = run_experiment(r,i,max,step)
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STDERR.puts "Set #{i}"
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}
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dataset[0].each_with_index{|ele,index|
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if filter == :max
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card=ele[0]
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err=ele[1].abs
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(1...numsets).each{|i|
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err = dataset[i][index][1] if err < dataset[i][index][1]
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}
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puts "#{card} #{err}"
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elsif filter == :avg
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card=ele[0]
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err = 0
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(0...numsets).each{|i|
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err += dataset[i][index][1]
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}
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err /= numsets
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puts "#{card} #{err}"
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elsif filter == :absavg
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card=ele[0]
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err = 0
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(0...numsets).each{|i|
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err += dataset[i][index][1].abs
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}
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err /= numsets
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puts "#{card} #{err}"
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elsif filter == :all
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(0...numsets).each{|i|
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card,err = dataset[i][index]
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puts "#{card} #{err}"
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}
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else
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raise "Unknown filter #{filter}"
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end
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}
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end
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if ARGV.length != 4
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puts "Usage: hll-gnuplot-graph <samples> <max> <step> (max|avg|absavg|all)"
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exit 1
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end
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filter_samples(ARGV[0].to_i,ARGV[1].to_i,ARGV[2].to_i,ARGV[3].to_sym)
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