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188 lines
5.9 KiB
Ruby
188 lines
5.9 KiB
Ruby
require "benchmark"
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require "redis"
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N = (ARGV.first || 1).to_i
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DOC_ID = (ARGV.last || "606072b20bb4d3109fb5b122")
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@r = Redis.new
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def get
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@r.get("doclines:{#{DOC_ID}}")
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@r.get("DocVersion:{#{DOC_ID}}")
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@r.get("DocHash:{#{DOC_ID}}")
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@r.get("ProjectId:{#{DOC_ID}}")
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@r.get("Ranges:{#{DOC_ID}}")
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@r.get("Pathname:{#{DOC_ID}}")
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@r.get("ProjectHistoryId:{#{DOC_ID}}")
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@r.get("UnflushedTime:{#{DOC_ID}}")
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@r.get("lastUpdatedAt:{#{DOC_ID}}")
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@r.get("lastUpdatedBy:{#{DOC_ID}}")
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end
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def mget
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@r.mget(
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"doclines:{#{DOC_ID}}",
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"DocVersion:{#{DOC_ID}}",
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"DocHash:{#{DOC_ID}}",
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"ProjectId:{#{DOC_ID}}",
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"Ranges:{#{DOC_ID}}",
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"Pathname:{#{DOC_ID}}",
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"ProjectHistoryId:{#{DOC_ID}}",
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"UnflushedTime:{#{DOC_ID}}",
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"lastUpdatedAt:{#{DOC_ID}}",
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"lastUpdatedBy:{#{DOC_ID}}",
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)
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end
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def set
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@r.set("doclines:{#{DOC_ID}}", "[\"@book{adams1995hitchhiker,\",\" title={The Hitchhiker's Guide to the Galaxy},\",\" author={Adams, D.},\",\" isbn={9781417642595},\",\" url={http://books.google.com/books?id=W-xMPgAACAAJ},\",\" year={1995},\",\" publisher={San Val}\",\"}\",\"\"]")
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@r.set("DocVersion:{#{DOC_ID}}", "0")
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@r.set("DocHash:{#{DOC_ID}}", "0075bb0629c6c13d0d68918443648bbfe7d98869")
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@r.set("ProjectId:{#{DOC_ID}}", "606072b20bb4d3109fb5b11e")
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@r.set("Ranges:{#{DOC_ID}}", "")
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@r.set("Pathname:{#{DOC_ID}}", "/references.bib")
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@r.set("ProjectHistoryId:{#{DOC_ID}}", "")
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@r.set("UnflushedTime:{#{DOC_ID}}", "")
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@r.set("lastUpdatedAt:{#{DOC_ID}}", "")
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@r.set("lastUpdatedBy:{#{DOC_ID}}", "")
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end
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def mset
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@r.mset(
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"doclines:{#{DOC_ID}}", "[\"@book{adams1995hitchhiker,\",\" title={The Hitchhiker's Guide to the Galaxy},\",\" author={Adams, D.},\",\" isbn={9781417642595},\",\" url={http://books.google.com/books?id=W-xMPgAACAAJ},\",\" year={1995},\",\" publisher={San Val}\",\"}\",\"\"]",
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"DocVersion:{#{DOC_ID}}", "0",
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"DocHash:{#{DOC_ID}}", "0075bb0629c6c13d0d68918443648bbfe7d98869",
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"ProjectId:{#{DOC_ID}}", "606072b20bb4d3109fb5b11e",
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"Ranges:{#{DOC_ID}}", "",
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"Pathname:{#{DOC_ID}}", "/references.bib",
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"ProjectHistoryId:{#{DOC_ID}}", "",
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"UnflushedTime:{#{DOC_ID}}", "",
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"lastUpdatedAt:{#{DOC_ID}}", "",
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"lastUpdatedBy:{#{DOC_ID}}", "",
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)
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end
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def benchmark_multi_get(benchmark, i)
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benchmark.report("#{i}: multi get") do
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N.times do
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@r.multi do
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get
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end
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end
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end
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end
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def benchmark_mget(benchmark, i)
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benchmark.report("#{i}: mget") do
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N.times do
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mget
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end
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end
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end
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def benchmark_multi_set(benchmark, i)
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benchmark.report("#{i}: multi set") do
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N.times do
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@r.multi do
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set
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end
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end
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end
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end
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def benchmark_mset(benchmark, i)
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benchmark.report("#{i}: mset") do
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N.times do
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mset
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end
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end
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end
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# init
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set
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Benchmark.bmbm do |benchmark|
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3.times do |i|
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benchmark_multi_get(benchmark, i)
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benchmark_mget(benchmark, i)
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benchmark_multi_set(benchmark, i)
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benchmark_mset(benchmark, i)
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end
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end
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=begin
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# Results
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I could not max out the redis-server process with this benchmark.
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The ruby process hit 100% of a modern i7 CPU thread and the redis-server process
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barely hit 50% of a CPU thread.
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Based on the timings below, mget is about 3 times faster and mset about 4 times
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faster than multiple get/set commands in a multi.
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=end
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=begin
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$ redis-server --version
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Redis server v=5.0.7 sha=00000000:0 malloc=jemalloc-5.2.1 bits=64 build=636cde3b5c7a3923
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$ ruby multi_vs_mget_mset.rb 100000
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Rehearsal ------------------------------------------------
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0: multi get 12.132423 4.246689 16.379112 ( 16.420069)
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0: mget 4.499457 0.947556 5.447013 ( 6.274883)
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0: multi set 12.685936 4.495241 17.181177 ( 17.225984)
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0: mset 2.543401 0.913448 3.456849 ( 4.554799)
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1: multi get 13.397207 4.581881 17.979088 ( 18.027755)
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1: mget 4.551287 1.160531 5.711818 ( 6.579168)
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1: multi set 13.018957 4.927175 17.946132 ( 17.987502)
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1: mset 2.561096 1.048416 3.609512 ( 4.780087)
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2: multi get 13.224422 5.014475 18.238897 ( 18.284152)
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2: mget 4.664434 1.051083 5.715517 ( 6.592088)
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2: multi set 12.972284 4.600422 17.572706 ( 17.613185)
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2: mset 2.621344 0.984123 3.605467 ( 4.766855)
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------------------------------------- total: 132.843288sec
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user system total real
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0: multi get 13.341552 4.900892 18.242444 ( 18.289912)
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0: mget 5.056534 0.960954 6.017488 ( 6.971189)
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0: multi set 12.989880 4.823793 17.813673 ( 17.858393)
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0: mset 2.543434 1.025352 3.568786 ( 4.723040)
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1: multi get 13.059379 4.674345 17.733724 ( 17.777859)
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1: mget 4.698754 0.915637 5.614391 ( 6.489614)
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1: multi set 12.608293 4.729163 17.337456 ( 17.372993)
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1: mset 2.645290 0.940584 3.585874 ( 4.744134)
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2: multi get 13.678224 4.732373 18.410597 ( 18.457525)
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2: mget 4.716749 1.072064 5.788813 ( 6.697683)
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2: multi set 13.058710 4.889801 17.948511 ( 17.988742)
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2: mset 2.311854 0.989166 3.301020 ( 4.346467)
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=end
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=begin
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# multi get/set run at about O(65'000) operations per second
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$ redis-cli info | grep 'instantaneous_ops_per_sec'
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instantaneous_ops_per_sec:65557
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# mget runs at about O(15'000) operations per second
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$ redis-cli info | grep 'instantaneous_ops_per_sec'
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instantaneous_ops_per_sec:14580
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# mset runs at about O(20'000) operations per second
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$ redis-cli info | grep 'instantaneous_ops_per_sec'
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instantaneous_ops_per_sec:20792
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These numbers are pretty reasonable:
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multi: 100'000 * 12 ops / 18s = 66'666 ops/s
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mget : 100'000 * 1 ops / 7s = 14'285 ops/s
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mset : 100'000 * 1 ops / 5s = 20'000 ops/s
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Bonus: Running three benchmarks in parallel on different keys.
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multi get: O(125'000) ops/s and 80% CPU load of redis-server
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multi set: O(130'000) ops/s and 90% CPU load of redis-server
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mget : O( 30'000) ops/s and 70% CPU load of redis-server
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mset : O( 40'000) ops/s and 90% CPU load of redis-server
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=end
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