Created
March 17, 2015 19:57
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New code for hll present
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| [info] Formatting 1 Scala source {file:/Users/ioconnell/workspace/github/algebird/}algebird-caliper(test) ... | |
| [info] Formatting 1 Scala source {file:/Users/ioconnell/workspace/github/algebird/}algebird-core(compile) ... | |
| [info] Compiling 1 Scala source to /Users/ioconnell/workspace/github/algebird/algebird-core/target/scala-2.10/classes... | |
| [info] Compiling 6 Scala sources to /Users/ioconnell/workspace/github/algebird/algebird-caliper/target/scala-2.10/test-classes... | |
| [info] Running com.google.caliper.Runner com.twitter.algebird.caliper.HLLPresentBenchmark | |
| [info] 0% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=5, max=10, numHLL=10} 1217.34 ns; σ=60.94 ns @ 10 trials | |
| [info] 2% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=10, max=10, numHLL=10} 1065.77 ns; σ=21.95 ns @ 10 trials | |
| [info] 3% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=17, max=10, numHLL=10} 1127.64 ns; σ=7.16 ns @ 3 trials | |
| [info] 5% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=20, max=10, numHLL=10} 1054.39 ns; σ=19.92 ns @ 10 trials | |
| [info] 7% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=5, max=100, numHLL=10} 1127.73 ns; σ=21.47 ns @ 10 trials | |
| [info] 8% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=10, max=100, numHLL=10} 1034.09 ns; σ=9.58 ns @ 3 trials | |
| [info] 10% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=17, max=100, numHLL=10} 1114.01 ns; σ=24.30 ns @ 10 trials | |
| [info] 12% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=20, max=100, numHLL=10} 1067.77 ns; σ=10.08 ns @ 4 trials | |
| [info] 13% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=5, max=500, numHLL=10} 1164.89 ns; σ=19.46 ns @ 10 trials | |
| [info] 15% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=10, max=500, numHLL=10} 1093.87 ns; σ=10.18 ns @ 3 trials | |
| [info] 17% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=17, max=500, numHLL=10} 1167.00 ns; σ=21.14 ns @ 10 trials | |
| [info] 18% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=20, max=500, numHLL=10} 1142.76 ns; σ=111.07 ns @ 10 trials | |
| [info] 20% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=5, max=1000, numHLL=10} 1436.88 ns; σ=330.44 ns @ 10 trials | |
| [info] 22% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=10, max=1000, numHLL=10} 1086.87 ns; σ=29.91 ns @ 10 trials | |
| [info] 23% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=17, max=1000, numHLL=10} 1169.24 ns; σ=36.89 ns @ 10 trials | |
| [info] 25% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=20, max=1000, numHLL=10} 1107.78 ns; σ=65.01 ns @ 10 trials | |
| [info] 27% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=5, max=10000, numHLL=10} 1196.76 ns; σ=38.67 ns @ 10 trials | |
| [info] 28% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=10, max=10000, numHLL=10} 1108.13 ns; σ=22.20 ns @ 10 trials | |
| [info] 30% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=17, max=10000, numHLL=10} 1145.70 ns; σ=69.39 ns @ 10 trials | |
| [info] 32% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=20, max=10000, numHLL=10} 1103.64 ns; σ=17.42 ns @ 10 trials | |
| [info] 33% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=5, max=10, numHLL=20} 2232.58 ns; σ=30.71 ns @ 10 trials | |
| [info] 35% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=10, max=10, numHLL=20} 2099.12 ns; σ=18.70 ns @ 5 trials | |
| [info] 37% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=17, max=10, numHLL=20} 2207.53 ns; σ=34.11 ns @ 10 trials | |
| [info] 38% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=20, max=10, numHLL=20} 2091.16 ns; σ=28.19 ns @ 10 trials | |
| [info] 40% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=5, max=100, numHLL=20} 2240.91 ns; σ=29.44 ns @ 10 trials | |
| [info] 42% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=10, max=100, numHLL=20} 2068.10 ns; σ=30.98 ns @ 10 trials | |
| [info] 43% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=17, max=100, numHLL=20} 2204.79 ns; σ=15.30 ns @ 3 trials | |
| [info] 45% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=20, max=100, numHLL=20} 2176.11 ns; σ=124.23 ns @ 10 trials | |
| [info] 47% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=5, max=500, numHLL=20} 2322.52 ns; σ=51.81 ns @ 10 trials | |
| [info] 48% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=10, max=500, numHLL=20} 2202.62 ns; σ=148.47 ns @ 10 trials | |
| [info] 50% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=17, max=500, numHLL=20} 2443.16 ns; σ=133.18 ns @ 10 trials | |
| [info] 52% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=20, max=500, numHLL=20} 2343.10 ns; σ=58.96 ns @ 10 trials | |
| [info] 53% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=5, max=1000, numHLL=20} 2349.38 ns; σ=61.97 ns @ 10 trials | |
| [info] 55% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=10, max=1000, numHLL=20} 2193.63 ns; σ=28.03 ns @ 10 trials | |
| [info] 57% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=17, max=1000, numHLL=20} 2373.24 ns; σ=64.09 ns @ 10 trials | |
| [info] 58% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=20, max=1000, numHLL=20} 2299.01 ns; σ=8.62 ns @ 3 trials | |
| [info] 60% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=5, max=10000, numHLL=20} 2323.59 ns; σ=21.10 ns @ 4 trials | |
| [info] 62% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=10, max=10000, numHLL=20} 2187.05 ns; σ=7.20 ns @ 3 trials | |
| [info] 63% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=17, max=10000, numHLL=20} 2298.18 ns; σ=48.78 ns @ 10 trials | |
| [info] 65% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=20, max=10000, numHLL=20} 2243.36 ns; σ=79.80 ns @ 10 trials | |
| [info] 67% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=5, max=10, numHLL=100} 11253.87 ns; σ=81.71 ns @ 3 trials | |
| [info] 68% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=10, max=10, numHLL=100} 10494.53 ns; σ=60.65 ns @ 3 trials | |
| [info] 70% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=17, max=10, numHLL=100} 11335.10 ns; σ=93.74 ns @ 3 trials | |
| [info] 72% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=20, max=10, numHLL=100} 10493.22 ns; σ=202.96 ns @ 10 trials | |
| [info] 73% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=5, max=100, numHLL=100} 12374.14 ns; σ=1337.93 ns @ 10 trials | |
| [info] 75% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=10, max=100, numHLL=100} 10680.26 ns; σ=96.55 ns @ 4 trials | |
| [info] 77% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=17, max=100, numHLL=100} 11897.39 ns; σ=505.13 ns @ 10 trials | |
| [info] 78% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=20, max=100, numHLL=100} 10860.35 ns; σ=102.35 ns @ 8 trials | |
| [info] 80% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=5, max=500, numHLL=100} 11597.87 ns; σ=157.23 ns @ 10 trials | |
| [info] 82% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=10, max=500, numHLL=100} 10978.36 ns; σ=128.85 ns @ 10 trials | |
| [info] 83% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=17, max=500, numHLL=100} 11884.35 ns; σ=1281.00 ns @ 10 trials | |
| [info] 85% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=20, max=500, numHLL=100} 11594.74 ns; σ=402.79 ns @ 10 trials | |
| [info] 87% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=5, max=1000, numHLL=100} 11660.51 ns; σ=91.65 ns @ 3 trials | |
| [info] 88% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=10, max=1000, numHLL=100} 11331.58 ns; σ=307.59 ns @ 10 trials | |
| [info] 90% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=17, max=1000, numHLL=100} 12105.41 ns; σ=301.05 ns @ 10 trials | |
| [info] 92% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=20, max=1000, numHLL=100} 11348.44 ns; σ=128.30 ns @ 10 trials | |
| [info] 93% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=5, max=10000, numHLL=100} 11476.68 ns; σ=104.26 ns @ 3 trials | |
| [info] 95% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=10, max=10000, numHLL=100} 11050.63 ns; σ=192.04 ns @ 10 trials | |
| [info] 97% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=17, max=10000, numHLL=100} 11702.95 ns; σ=138.73 ns @ 10 trials | |
| [info] 98% Scenario{vm=java, trial=0, benchmark=BatchCreate, bits=20, max=10000, numHLL=100} 15615.03 ns; σ=3786.64 ns @ 10 trials | |
| [info] | |
| [info] numHLL bits max us linear runtime | |
| [info] 10 5 10 1.22 == | |
| [info] 10 5 100 1.13 == | |
| [info] 10 5 500 1.16 == | |
| [info] 10 5 1000 1.44 == | |
| [info] 10 5 10000 1.20 == | |
| [info] 10 10 10 1.07 == | |
| [info] 10 10 100 1.03 = | |
| [info] 10 10 500 1.09 == | |
| [info] 10 10 1000 1.09 == | |
| [info] 10 10 10000 1.11 == | |
| [info] 10 17 10 1.13 == | |
| [info] 10 17 100 1.11 == | |
| [info] 10 17 500 1.17 == | |
| [info] 10 17 1000 1.17 == | |
| [info] 10 17 10000 1.15 == | |
| [info] 10 20 10 1.05 == | |
| [info] 10 20 100 1.07 == | |
| [info] 10 20 500 1.14 == | |
| [info] 10 20 1000 1.11 == | |
| [info] 10 20 10000 1.10 == | |
| [info] 20 5 10 2.23 ==== | |
| [info] 20 5 100 2.24 ==== | |
| [info] 20 5 500 2.32 ==== | |
| [info] 20 5 1000 2.35 ==== | |
| [info] 20 5 10000 2.32 ==== | |
| [info] 20 10 10 2.10 ==== | |
| [info] 20 10 100 2.07 === | |
| [info] 20 10 500 2.20 ==== | |
| [info] 20 10 1000 2.19 ==== | |
| [info] 20 10 10000 2.19 ==== | |
| [info] 20 17 10 2.21 ==== | |
| [info] 20 17 100 2.20 ==== | |
| [info] 20 17 500 2.44 ==== | |
| [info] 20 17 1000 2.37 ==== | |
| [info] 20 17 10000 2.30 ==== | |
| [info] 20 20 10 2.09 ==== | |
| [info] 20 20 100 2.18 ==== | |
| [info] 20 20 500 2.34 ==== | |
| [info] 20 20 1000 2.30 ==== | |
| [info] 20 20 10000 2.24 ==== | |
| [info] 100 5 10 11.25 ===================== | |
| [info] 100 5 100 12.37 ======================= | |
| [info] 100 5 500 11.60 ====================== | |
| [info] 100 5 1000 11.66 ====================== | |
| [info] 100 5 10000 11.48 ====================== | |
| [info] 100 10 10 10.49 ==================== | |
| [info] 100 10 100 10.68 ==================== | |
| [info] 100 10 500 10.98 ===================== | |
| [info] 100 10 1000 11.33 ===================== | |
| [info] 100 10 10000 11.05 ===================== | |
| [info] 100 17 10 11.34 ===================== | |
| [info] 100 17 100 11.90 ====================== | |
| [info] 100 17 500 11.88 ====================== | |
| [info] 100 17 1000 12.11 ======================= | |
| [info] 100 17 10000 11.70 ====================== | |
| [info] 100 20 10 10.49 ==================== | |
| [info] 100 20 100 10.86 ==================== | |
| [info] 100 20 500 11.59 ====================== | |
| [info] 100 20 1000 11.35 ===================== | |
| [info] 100 20 10000 15.62 ============================== |
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