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Versions: 7
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Stored size: 1.52 KB
Contents
# Runs a mild benchmark and prints out the average time a call to 'throttle!' takes.
require 'prorate'
require 'benchmark'
require 'redis'
require 'securerandom'
def average_ms(ary)
ary.map { |x| x * 1000 }.inject(0, &:+) / ary.length
end
r = Redis.new
# 4000000.times do
# random1 = SecureRandom.hex(10)
# random2 = SecureRandom.hex(10)
# r.set(random1,random2)
# end
logz = Logger.new(STDERR)
logz.level = Logger::FATAL # block out most stuff
times = []
15.times do
id = SecureRandom.hex(10)
times << Benchmark.realtime {
r.evalsha('c95c5f1197cef04ec4afd7d64760f9175933e55a', [], [id, 120, 50, 10]) # values beyond 120 chosen more or less at random
}
end
puts average_ms times
def key_for_ts(ts)
"th:%s:%d" % [@id, ts]
end
times = []
15.times do
sec, _ = r.time # Use Redis time instead of the system timestamp, so that all the nodes are consistent
ts = sec.to_i # All Redis results are strings
k = key_for_ts(ts)
times << Benchmark.realtime {
r.multi do |txn|
# Increment the counter
txn.incr(k)
txn.expire(k, 120)
span_start = ts - 120
span_end = ts + 1
possible_keys = (span_start..span_end).map { |prev_time| key_for_ts(prev_time) }
# Fetch all the counter values within the time window. Despite the fact that this
# will return thousands of elements for large sliding window sizes, the values are
# small and an MGET in Redis is pretty cheap, so perf should stay well within limits.
txn.mget(*possible_keys)
end
}
end
puts average_ms times
Version data entries
7 entries across 7 versions & 1 rubygems