redis_study/utils/hyperloglog/hll-gnuplot-graph.rb
2020-09-05 12:01:22 +08:00

89 lines
2.6 KiB
Ruby

# 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 the specified 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 = []
step = 1000 if step > 1000
while i < max do
elements = []
step.times {
ele = Digest::SHA1.hexdigest(i.to_s+seed.to_s)
elements << ele
i += 1
}
r.pfadd('hll',elements)
approx = r.pfcount('hll')
err = approx-i
rel_err = 100.to_f*err/i
samples << [i,rel_err]
end
samples
end
def filter_samples(numsets,max,step,filter)
r = Redis.new
dataset = {}
(0...numsets).each{|i|
dataset[i] = run_experiment(r,i,max,step)
STDERR.puts "Set #{i}"
}
dataset[0].each_with_index{|ele,index|
if filter == :max
card=ele[0]
err=ele[1].abs
(1...numsets).each{|i|
err = dataset[i][index][1] if err < dataset[i][index][1]
}
puts "#{card} #{err}"
elsif filter == :avg
card=ele[0]
err = 0
(0...numsets).each{|i|
err += dataset[i][index][1]
}
err /= numsets
puts "#{card} #{err}"
elsif filter == :absavg
card=ele[0]
err = 0
(0...numsets).each{|i|
err += dataset[i][index][1].abs
}
err /= numsets
puts "#{card} #{err}"
elsif filter == :all
(0...numsets).each{|i|
card,err = dataset[i][index]
puts "#{card} #{err}"
}
else
raise "Unknown filter #{filter}"
end
}
end
if ARGV.length != 4
puts "Usage: hll-gnuplot-graph <samples> <max> <step> (max|avg|absavg|all)"
exit 1
end
filter_samples(ARGV[0].to_i,ARGV[1].to_i,ARGV[2].to_i,ARGV[3].to_sym)