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import os | |
import sys | |
import time | |
from timeit import default_timer as timer | |
from datetime import timedelta | |
from os import path | |
base_dir = "data" | |
dummy_dir_small = path.join(base_dir, "small") | |
dummy_dir_large = path.join(base_dir, "large") | |
def create_dummpy_data(dir_path, count): | |
os.makedirs(dir_path) | |
print("create dummy data in {} starting".format(dir_path)) | |
time_start_all = timer() | |
time_start_last = timer() | |
interval = 1000 | |
for i in range(count): | |
if (i + 1) % 1000 == 0: | |
time_curr = timer() | |
print( | |
"[{}:{}] create dummy data elapsed: {}(avg: {}), in total: {}(avg: {})" | |
.format( | |
dir_path, i + 1, | |
timedelta(seconds=(time_curr - time_start_last)), | |
timedelta(seconds=((time_curr - time_start_last) / | |
interval)), | |
timedelta(seconds=(time_curr - time_start_all)), | |
timedelta(seconds=((time_curr - time_start_all) / | |
(i + 1))))) | |
sys.stdout.flush() | |
with open(path.join(dir_path, str(i)), 'w') as f: | |
msg = "{:010d}".format(i) | |
f.write(msg) | |
print("[{}:{}] create dummy elapsed: {} avg: {}, all done".format( | |
dir_path, count, timedelta(seconds=(time_curr - time_start_all)), | |
timedelta(seconds=((time_curr - time_start_all) / count)))) | |
sys.stdout.flush() | |
def is_dir(dir_path): | |
return os.path.exists(dir_path) | |
def ensure_dir(dir_path, amount): | |
if not is_dir(dir_path): | |
create_dummpy_data(dir_path, amount) | |
def test_reading(dir_path, count): | |
print("test reading data in {} starting".format(dir_path)) | |
time_start_all = timer() | |
time_start_last = timer() | |
interval = 1000 | |
for i in range(count): | |
if (i + 1) % interval == 0: | |
time_curr = timer() | |
print("[{}:{}] elapsed: {}(avg: {}), in total: {}(avg: {})".format( | |
dir_path, i + 1, | |
timedelta(seconds=(time_curr - time_start_last)), | |
timedelta(seconds=((time_curr - time_start_last) / interval)), | |
timedelta(seconds=(time_curr - time_start_all)), | |
timedelta(seconds=((time_curr - time_start_all) / (i + 1))))) | |
sys.stdout.flush() | |
time_start_last = time_curr | |
with open(path.join(dir_path, str(i)), 'r') as f: | |
msg = "{:010d}".format(i) | |
assert (f.readline() == msg) | |
time_curr = timer() | |
print("[{}:{}] elapsed: {} avg: {}".format( | |
dir_path, count, timedelta(seconds=(time_curr - time_start_all)), | |
timedelta(seconds=((time_curr - time_start_all) / count)))) | |
sys.stdout.flush() | |
def main(): | |
ensure_dir(dummy_dir_small, 5000) | |
ensure_dir(dummy_dir_large, 500000) | |
test_reading(dummy_dir_small, 5000) | |
test_reading(dummy_dir_large, 5000) | |
if __name__ == "__main__": | |
main() |
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create dummy data in data/small starting | |
[data/small:1000] create dummy data elapsed: 0:00:00.118295(avg: 0:00:00.000118), in total: 0:00:00.118297(avg: 0:00:00.000118) | |
[data/small:2000] create dummy data elapsed: 0:00:00.241233(avg: 0:00:00.000241), in total: 0:00:00.241235(avg: 0:00:00.000121) | |
[data/small:3000] create dummy data elapsed: 0:00:00.357166(avg: 0:00:00.000357), in total: 0:00:00.357168(avg: 0:00:00.000119) | |
[data/small:4000] create dummy data elapsed: 0:00:00.476689(avg: 0:00:00.000477), in total: 0:00:00.476690(avg: 0:00:00.000119) | |
[data/small:5000] create dummy data elapsed: 0:00:00.592847(avg: 0:00:00.000593), in total: 0:00:00.592848(avg: 0:00:00.000119) | |
[data/small:5000] create dummy elapsed: 0:00:00.592848 avg: 0:00:00.000119, all done | |
create dummy data in data/large starting | |
[data/large:1000] create dummy data elapsed: 0:00:00.119876(avg: 0:00:00.000120), in total: 0:00:00.119876(avg: 0:00:00.000120) | |
[data/large:2000] create dummy data elapsed: 0:00:00.257207(avg: 0:00:00.000257), in total: 0:00:00.257207(avg: 0:00:00.000129) | |
[data/large:3000] create dummy data elapsed: 0:00:00.405286(avg: 0:00:00.000405), in total: 0:00:00.405287(avg: 0:00:00.000135) | |
[data/large:4000] create dummy data elapsed: 0:00:00.536713(avg: 0:00:00.000537), in total: 0:00:00.536713(avg: 0:00:00.000134) | |
[data/large:5000] create dummy data elapsed: 0:00:00.700402(avg: 0:00:00.000700), in total: 0:00:00.700402(avg: 0:00:00.000140) | |
[data/large:6000] create dummy data elapsed: 0:00:00.851999(avg: 0:00:00.000852), in total: 0:00:00.851999(avg: 0:00:00.000142) | |
[data/large:7000] create dummy data elapsed: 0:00:00.981476(avg: 0:00:00.000981), in total: 0:00:00.981476(avg: 0:00:00.000140) | |
[data/large:8000] create dummy data elapsed: 0:00:01.096823(avg: 0:00:00.001097), in total: 0:00:01.096824(avg: 0:00:00.000137) | |
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[data/large:10000] create dummy data elapsed: 0:00:01.329219(avg: 0:00:00.001329), in total: 0:00:01.329219(avg: 0:00:00.000133) | |
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[data/large:498000] create dummy data elapsed: 0:01:19.085928(avg: 0:00:00.079086), in total: 0:01:19.085928(avg: 0:00:00.000159) | |
[data/large:499000] create dummy data elapsed: 0:01:19.251707(avg: 0:00:00.079252), in total: 0:01:19.251707(avg: 0:00:00.000159) | |
[data/large:500000] create dummy data elapsed: 0:01:19.416390(avg: 0:00:00.079416), in total: 0:01:19.416390(avg: 0:00:00.000159) | |
[data/large:500000] create dummy elapsed: 0:01:19.416390 avg: 0:00:00.000159, all done | |
test reading data in data/small starting | |
[data/small:1000] elapsed: 0:00:00.153062(avg: 0:00:00.000153), in total: 0:00:00.153062(avg: 0:00:00.000153) | |
[data/small:2000] elapsed: 0:00:00.130151(avg: 0:00:00.000130), in total: 0:00:00.283214(avg: 0:00:00.000142) | |
[data/small:3000] elapsed: 0:00:00.121274(avg: 0:00:00.000121), in total: 0:00:00.404488(avg: 0:00:00.000135) | |
[data/small:4000] elapsed: 0:00:00.117216(avg: 0:00:00.000117), in total: 0:00:00.521704(avg: 0:00:00.000130) | |
[data/small:5000] elapsed: 0:00:00.122165(avg: 0:00:00.000122), in total: 0:00:00.643869(avg: 0:00:00.000129) | |
[data/small:5000] elapsed: 0:00:00.644100 avg: 0:00:00.000129 | |
test reading data in data/large starting | |
[data/large:1000] elapsed: 0:00:00.165082(avg: 0:00:00.000165), in total: 0:00:00.165082(avg: 0:00:00.000165) | |
[data/large:2000] elapsed: 0:00:00.140481(avg: 0:00:00.000140), in total: 0:00:00.305562(avg: 0:00:00.000153) | |
[data/large:3000] elapsed: 0:00:00.141707(avg: 0:00:00.000142), in total: 0:00:00.447269(avg: 0:00:00.000149) | |
[data/large:4000] elapsed: 0:00:00.194968(avg: 0:00:00.000195), in total: 0:00:00.642237(avg: 0:00:00.000161) | |
[data/large:5000] elapsed: 0:00:00.128898(avg: 0:00:00.000129), in total: 0:00:00.771135(avg: 0:00:00.000154) | |
[data/large:5000] elapsed: 0:00:00.771358 avg: 0:00:00.000154 |
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create dummy data in data/small starting | |
[data/small:1000] create dummy data elapsed: 0:00:00.036681(avg: 0:00:00.000037), in total: 0:00:00.036681(avg: 0:00:00.000037) | |
[data/small:2000] create dummy data elapsed: 0:00:00.184024(avg: 0:00:00.000184), in total: 0:00:00.184024(avg: 0:00:00.000092) | |
[data/small:3000] create dummy data elapsed: 0:00:00.233445(avg: 0:00:00.000233), in total: 0:00:00.233445(avg: 0:00:00.000078) | |
[data/small:4000] create dummy data elapsed: 0:00:00.314359(avg: 0:00:00.000314), in total: 0:00:00.314359(avg: 0:00:00.000079) | |
[data/small:5000] create dummy data elapsed: 0:00:00.351601(avg: 0:00:00.000352), in total: 0:00:00.351601(avg: 0:00:00.000070) | |
[data/small:5000] create dummy elapsed: 0:00:00.351601 avg: 0:00:00.000070, all done | |
create dummy data in data/large starting | |
[data/large:1000] create dummy data elapsed: 0:00:00.034126(avg: 0:00:00.000034), in total: 0:00:00.034126(avg: 0:00:00.000034) | |
[data/large:2000] create dummy data elapsed: 0:00:00.072506(avg: 0:00:00.000073), in total: 0:00:00.072506(avg: 0:00:00.000036) | |
[data/large:3000] create dummy data elapsed: 0:00:00.111110(avg: 0:00:00.000111), in total: 0:00:00.111110(avg: 0:00:00.000037) | |
[data/large:4000] create dummy data elapsed: 0:00:00.149772(avg: 0:00:00.000150), in total: 0:00:00.149772(avg: 0:00:00.000037) | |
[data/large:5000] create dummy data elapsed: 0:00:00.188803(avg: 0:00:00.000189), in total: 0:00:00.188803(avg: 0:00:00.000038) | |
[data/large:6000] create dummy data elapsed: 0:00:00.227672(avg: 0:00:00.000228), in total: 0:00:00.227672(avg: 0:00:00.000038) | |
[data/large:7000] create dummy data elapsed: 0:00:00.266520(avg: 0:00:00.000267), in total: 0:00:00.266520(avg: 0:00:00.000038) | |
[data/large:8000] create dummy data elapsed: 0:00:00.305397(avg: 0:00:00.000305), in total: 0:00:00.305398(avg: 0:00:00.000038) | |
[data/large:9000] create dummy data elapsed: 0:00:00.342445(avg: 0:00:00.000342), in total: 0:00:00.342445(avg: 0:00:00.000038) | |
[data/large:10000] create dummy data elapsed: 0:00:00.380018(avg: 0:00:00.000380), in total: 0:00:00.380018(avg: 0:00:00.000038) | |
[data/large:11000] create dummy data elapsed: 0:00:00.417818(avg: 0:00:00.000418), in total: 0:00:00.417818(avg: 0:00:00.000038) | |
[data/large:12000] create dummy data elapsed: 0:00:00.455580(avg: 0:00:00.000456), in total: 0:00:00.455580(avg: 0:00:00.000038) | |
[data/large:13000] create dummy data elapsed: 0:00:00.493272(avg: 0:00:00.000493), in total: 0:00:00.493273(avg: 0:00:00.000038) | |
[data/large:14000] create dummy data elapsed: 0:00:00.531164(avg: 0:00:00.000531), in total: 0:00:00.531164(avg: 0:00:00.000038) | |
[data/large:15000] create dummy data elapsed: 0:00:00.569206(avg: 0:00:00.000569), in total: 0:00:00.569206(avg: 0:00:00.000038) | |
[data/large:16000] create dummy data elapsed: 0:00:00.607333(avg: 0:00:00.000607), in total: 0:00:00.607333(avg: 0:00:00.000038) | |
[data/large:17000] create dummy data elapsed: 0:00:00.647495(avg: 0:00:00.000647), in total: 0:00:00.647495(avg: 0:00:00.000038) | |
[data/large:18000] create dummy data elapsed: 0:00:00.685814(avg: 0:00:00.000686), in total: 0:00:00.685814(avg: 0:00:00.000038) | |
[data/large:19000] create dummy data elapsed: 0:00:00.724375(avg: 0:00:00.000724), in total: 0:00:00.724375(avg: 0:00:00.000038) | |
[data/large:20000] create dummy data elapsed: 0:00:00.762961(avg: 0:00:00.000763), in total: 0:00:00.762961(avg: 0:00:00.000038) | |
[data/large:21000] create dummy data elapsed: 0:00:00.801665(avg: 0:00:00.000802), in total: 0:00:00.801665(avg: 0:00:00.000038) | |
[data/large:22000] create dummy data elapsed: 0:00:00.842664(avg: 0:00:00.000843), in total: 0:00:00.842664(avg: 0:00:00.000038) | |
[data/large:23000] create dummy data elapsed: 0:00:00.883977(avg: 0:00:00.000884), in total: 0:00:00.883977(avg: 0:00:00.000038) | |
[data/large:24000] create dummy data elapsed: 0:00:00.923601(avg: 0:00:00.000924), in total: 0:00:00.923601(avg: 0:00:00.000038) | |
[data/large:25000] create dummy data elapsed: 0:00:00.977085(avg: 0:00:00.000977), in total: 0:00:00.977085(avg: 0:00:00.000039) | |
[data/large:26000] create dummy data elapsed: 0:00:01.016285(avg: 0:00:00.001016), in total: 0:00:01.016285(avg: 0:00:00.000039) | |
[data/large:27000] create dummy data elapsed: 0:00:01.057920(avg: 0:00:00.001058), in total: 0:00:01.057920(avg: 0:00:00.000039) | |
[data/large:28000] create dummy data elapsed: 0:00:01.097676(avg: 0:00:00.001098), in total: 0:00:01.097676(avg: 0:00:00.000039) | |
[data/large:29000] create dummy data elapsed: 0:00:01.139397(avg: 0:00:00.001139), in total: 0:00:01.139397(avg: 0:00:00.000039) | |
[data/large:30000] create dummy data elapsed: 0:00:01.181281(avg: 0:00:00.001181), in total: 0:00:01.181281(avg: 0:00:00.000039) | |
[data/large:31000] create dummy data elapsed: 0:00:01.221279(avg: 0:00:00.001221), in total: 0:00:01.221279(avg: 0:00:00.000039) | |
[data/large:32000] create dummy data elapsed: 0:00:01.261309(avg: 0:00:00.001261), in total: 0:00:01.261309(avg: 0:00:00.000039) | |
[data/large:33000] create dummy data elapsed: 0:00:01.301618(avg: 0:00:00.001302), in total: 0:00:01.301618(avg: 0:00:00.000039) | |
[data/large:34000] create dummy data elapsed: 0:00:01.341923(avg: 0:00:00.001342), in total: 0:00:01.341923(avg: 0:00:00.000039) | |
[data/large:35000] create dummy data elapsed: 0:00:01.382648(avg: 0:00:00.001383), in total: 0:00:01.382649(avg: 0:00:00.000040) | |
[data/large:36000] create dummy data elapsed: 0:00:01.423952(avg: 0:00:00.001424), in total: 0:00:01.423952(avg: 0:00:00.000040) | |
[data/large:37000] create dummy data elapsed: 0:00:01.464982(avg: 0:00:00.001465), in total: 0:00:01.464982(avg: 0:00:00.000040) | |
[data/large:38000] create dummy data elapsed: 0:00:01.506219(avg: 0:00:00.001506), in total: 0:00:01.506219(avg: 0:00:00.000040) | |
[data/large:39000] create dummy data elapsed: 0:00:01.547856(avg: 0:00:00.001548), in total: 0:00:01.547856(avg: 0:00:00.000040) | |
[data/large:40000] create dummy data elapsed: 0:00:01.589355(avg: 0:00:00.001589), in total: 0:00:01.589355(avg: 0:00:00.000040) | |
[data/large:41000] create dummy data elapsed: 0:00:01.630784(avg: 0:00:00.001631), in total: 0:00:01.630784(avg: 0:00:00.000040) | |
[data/large:42000] create dummy data elapsed: 0:00:01.672212(avg: 0:00:00.001672), in total: 0:00:01.672212(avg: 0:00:00.000040) | |
[data/large:43000] create dummy data elapsed: 0:00:01.714179(avg: 0:00:00.001714), in total: 0:00:01.714179(avg: 0:00:00.000040) | |
[data/large:44000] create dummy data elapsed: 0:00:01.756260(avg: 0:00:00.001756), in total: 0:00:01.756260(avg: 0:00:00.000040) | |
[data/large:45000] create dummy data elapsed: 0:00:01.798232(avg: 0:00:00.001798), in total: 0:00:01.798232(avg: 0:00:00.000040) | |
[data/large:46000] create dummy data elapsed: 0:00:01.840652(avg: 0:00:00.001841), in total: 0:00:01.840652(avg: 0:00:00.000040) | |
[data/large:47000] create dummy data elapsed: 0:00:01.883404(avg: 0:00:00.001883), in total: 0:00:01.883404(avg: 0:00:00.000040) | |
[data/large:48000] create dummy data elapsed: 0:00:01.925891(avg: 0:00:00.001926), in total: 0:00:01.925891(avg: 0:00:00.000040) | |
[data/large:49000] create dummy data elapsed: 0:00:01.968480(avg: 0:00:00.001968), in total: 0:00:01.968480(avg: 0:00:00.000040) | |
[data/large:50000] create dummy data elapsed: 0:00:02.011070(avg: 0:00:00.002011), in total: 0:00:02.011070(avg: 0:00:00.000040) | |
[data/large:51000] create dummy data elapsed: 0:00:02.054066(avg: 0:00:00.002054), in total: 0:00:02.054066(avg: 0:00:00.000040) | |
[data/large:52000] create dummy data elapsed: 0:00:02.097275(avg: 0:00:00.002097), in total: 0:00:02.097276(avg: 0:00:00.000040) | |
[data/large:53000] create dummy data elapsed: 0:00:02.140582(avg: 0:00:00.002141), in total: 0:00:02.140582(avg: 0:00:00.000040) | |
[data/large:54000] create dummy data elapsed: 0:00:02.184368(avg: 0:00:00.002184), in total: 0:00:02.184368(avg: 0:00:00.000040) | |
[data/large:55000] create dummy data elapsed: 0:00:02.228159(avg: 0:00:00.002228), in total: 0:00:02.228159(avg: 0:00:00.000041) | |
[data/large:56000] create dummy data elapsed: 0:00:02.271801(avg: 0:00:00.002272), in total: 0:00:02.271801(avg: 0:00:00.000041) | |
[data/large:57000] create dummy data elapsed: 0:00:02.315911(avg: 0:00:00.002316), in total: 0:00:02.315911(avg: 0:00:00.000041) | |
[data/large:58000] create dummy data elapsed: 0:00:02.359983(avg: 0:00:00.002360), in total: 0:00:02.359984(avg: 0:00:00.000041) | |
[data/large:59000] create dummy data elapsed: 0:00:02.404768(avg: 0:00:00.002405), in total: 0:00:02.404768(avg: 0:00:00.000041) | |
[data/large:60000] create dummy data elapsed: 0:00:02.449079(avg: 0:00:00.002449), in total: 0:00:02.449080(avg: 0:00:00.000041) | |
[data/large:61000] create dummy data elapsed: 0:00:02.493609(avg: 0:00:00.002494), in total: 0:00:02.493609(avg: 0:00:00.000041) | |
[data/large:62000] create dummy data elapsed: 0:00:02.538415(avg: 0:00:00.002538), in total: 0:00:02.538415(avg: 0:00:00.000041) | |
[data/large:63000] create dummy data elapsed: 0:00:02.585549(avg: 0:00:00.002586), in total: 0:00:02.585549(avg: 0:00:00.000041) | |
[data/large:64000] create dummy data elapsed: 0:00:02.630129(avg: 0:00:00.002630), in total: 0:00:02.630129(avg: 0:00:00.000041) | |
[data/large:65000] create dummy data elapsed: 0:00:02.677784(avg: 0:00:00.002678), in total: 0:00:02.677784(avg: 0:00:00.000041) | |
[data/large:66000] create dummy data elapsed: 0:00:02.722904(avg: 0:00:00.002723), in total: 0:00:02.722904(avg: 0:00:00.000041) | |
[data/large:67000] create dummy data elapsed: 0:00:02.770480(avg: 0:00:00.002770), in total: 0:00:02.770480(avg: 0:00:00.000041) | |
[data/large:68000] create dummy data elapsed: 0:00:02.815922(avg: 0:00:00.002816), in total: 0:00:02.815922(avg: 0:00:00.000041) | |
[data/large:69000] create dummy data elapsed: 0:00:02.861454(avg: 0:00:00.002861), in total: 0:00:02.861454(avg: 0:00:00.000041) | |
[data/large:70000] create dummy data elapsed: 0:00:02.907187(avg: 0:00:00.002907), in total: 0:00:02.907187(avg: 0:00:00.000042) | |
[data/large:71000] create dummy data elapsed: 0:00:02.952859(avg: 0:00:00.002953), in total: 0:00:02.952859(avg: 0:00:00.000042) | |
[data/large:72000] create dummy data elapsed: 0:00:02.998943(avg: 0:00:00.002999), in total: 0:00:02.998943(avg: 0:00:00.000042) | |
[data/large:73000] create dummy data elapsed: 0:00:03.045245(avg: 0:00:00.003045), in total: 0:00:03.045245(avg: 0:00:00.000042) | |
[data/large:74000] create dummy data elapsed: 0:00:03.091605(avg: 0:00:00.003092), in total: 0:00:03.091605(avg: 0:00:00.000042) | |
[data/large:75000] create dummy data elapsed: 0:00:03.140496(avg: 0:00:00.003140), in total: 0:00:03.140496(avg: 0:00:00.000042) | |
[data/large:76000] create dummy data elapsed: 0:00:03.187107(avg: 0:00:00.003187), in total: 0:00:03.187107(avg: 0:00:00.000042) | |
[data/large:77000] create dummy data elapsed: 0:00:03.233772(avg: 0:00:00.003234), in total: 0:00:03.233772(avg: 0:00:00.000042) | |
[data/large:78000] create dummy data elapsed: 0:00:03.280485(avg: 0:00:00.003280), in total: 0:00:03.280485(avg: 0:00:00.000042) | |
[data/large:79000] create dummy data elapsed: 0:00:03.327402(avg: 0:00:00.003327), in total: 0:00:03.327402(avg: 0:00:00.000042) | |
[data/large:80000] create dummy data elapsed: 0:00:03.374655(avg: 0:00:00.003375), in total: 0:00:03.374655(avg: 0:00:00.000042) | |
[data/large:81000] create dummy data elapsed: 0:00:03.422078(avg: 0:00:00.003422), in total: 0:00:03.422078(avg: 0:00:00.000042) | |
[data/large:82000] create dummy data elapsed: 0:00:03.469495(avg: 0:00:00.003469), in total: 0:00:03.469495(avg: 0:00:00.000042) | |
[data/large:83000] create dummy data elapsed: 0:00:03.516902(avg: 0:00:00.003517), in total: 0:00:03.516902(avg: 0:00:00.000042) | |
[data/large:84000] create dummy data elapsed: 0:00:03.564579(avg: 0:00:00.003565), in total: 0:00:03.564579(avg: 0:00:00.000042) | |
[data/large:85000] create dummy data elapsed: 0:00:03.612177(avg: 0:00:00.003612), in total: 0:00:03.612177(avg: 0:00:00.000042) | |
[data/large:86000] create dummy data elapsed: 0:00:03.660073(avg: 0:00:00.003660), in total: 0:00:03.660073(avg: 0:00:00.000043) | |
[data/large:87000] create dummy data elapsed: 0:00:03.710805(avg: 0:00:00.003711), in total: 0:00:03.710805(avg: 0:00:00.000043) | |
[data/large:88000] create dummy data elapsed: 0:00:03.759253(avg: 0:00:00.003759), in total: 0:00:03.759254(avg: 0:00:00.000043) | |
[data/large:89000] create dummy data elapsed: 0:00:03.807693(avg: 0:00:00.003808), in total: 0:00:03.807693(avg: 0:00:00.000043) | |
[data/large:90000] create dummy data elapsed: 0:00:03.856336(avg: 0:00:00.003856), in total: 0:00:03.856337(avg: 0:00:00.000043) | |
[data/large:91000] create dummy data elapsed: 0:00:03.907718(avg: 0:00:00.003908), in total: 0:00:03.907719(avg: 0:00:00.000043) | |
[data/large:92000] create dummy data elapsed: 0:00:03.956934(avg: 0:00:00.003957), in total: 0:00:03.956934(avg: 0:00:00.000043) | |
[data/large:93000] create dummy data elapsed: 0:00:04.008749(avg: 0:00:00.004009), in total: 0:00:04.008749(avg: 0:00:00.000043) | |
[data/large:94000] create dummy data elapsed: 0:00:04.058155(avg: 0:00:00.004058), in total: 0:00:04.058156(avg: 0:00:00.000043) | |
[data/large:95000] create dummy data elapsed: 0:00:04.109992(avg: 0:00:00.004110), in total: 0:00:04.109992(avg: 0:00:00.000043) | |
[data/large:96000] create dummy data elapsed: 0:00:04.159951(avg: 0:00:00.004160), in total: 0:00:04.159951(avg: 0:00:00.000043) | |
[data/large:97000] create dummy data elapsed: 0:00:04.209488(avg: 0:00:00.004209), in total: 0:00:04.209489(avg: 0:00:00.000043) | |
[data/large:98000] create dummy data elapsed: 0:00:04.265755(avg: 0:00:00.004266), in total: 0:00:04.265756(avg: 0:00:00.000044) | |
[data/large:99000] create dummy data elapsed: 0:00:04.316291(avg: 0:00:00.004316), in total: 0:00:04.316291(avg: 0:00:00.000044) | |
[data/large:100000] create dummy data elapsed: 0:00:04.366538(avg: 0:00:00.004367), in total: 0:00:04.366538(avg: 0:00:00.000044) | |
[data/large:101000] create dummy data elapsed: 0:00:04.417521(avg: 0:00:00.004418), in total: 0:00:04.417522(avg: 0:00:00.000044) | |
[data/large:102000] create dummy data elapsed: 0:00:04.468519(avg: 0:00:00.004469), in total: 0:00:04.468519(avg: 0:00:00.000044) | |
[data/large:103000] create dummy data elapsed: 0:00:04.519381(avg: 0:00:00.004519), in total: 0:00:04.519381(avg: 0:00:00.000044) | |
[data/large:104000] create dummy data elapsed: 0:00:04.578163(avg: 0:00:00.004578), in total: 0:00:04.578163(avg: 0:00:00.000044) | |
[data/large:105000] create dummy data elapsed: 0:00:04.633645(avg: 0:00:00.004634), in total: 0:00:04.633645(avg: 0:00:00.000044) | |
[data/large:106000] create dummy data elapsed: 0:00:04.684715(avg: 0:00:00.004685), in total: 0:00:04.684715(avg: 0:00:00.000044) | |
[data/large:107000] create dummy data elapsed: 0:00:04.738515(avg: 0:00:00.004739), in total: 0:00:04.738516(avg: 0:00:00.000044) | |
[data/large:108000] create dummy data elapsed: 0:00:04.789694(avg: 0:00:00.004790), in total: 0:00:04.789694(avg: 0:00:00.000044) | |
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[data/large:500000] create dummy data elapsed: 0:02:25.737173(avg: 0:00:00.145737), in total: 0:02:25.737173(avg: 0:00:00.000291) | |
[data/large:500000] create dummy elapsed: 0:02:25.737173 avg: 0:00:00.000291, all done | |
test reading data in data/small starting | |
[data/small:1000] elapsed: 0:00:00.019693(avg: 0:00:00.000020), in total: 0:00:00.019693(avg: 0:00:00.000020) | |
[data/small:2000] elapsed: 0:00:00.019776(avg: 0:00:00.000020), in total: 0:00:00.039470(avg: 0:00:00.000020) | |
[data/small:3000] elapsed: 0:00:00.019675(avg: 0:00:00.000020), in total: 0:00:00.059145(avg: 0:00:00.000020) | |
[data/small:4000] elapsed: 0:00:00.019751(avg: 0:00:00.000020), in total: 0:00:00.078895(avg: 0:00:00.000020) | |
[data/small:5000] elapsed: 0:00:00.019847(avg: 0:00:00.000020), in total: 0:00:00.098742(avg: 0:00:00.000020) | |
[data/small:5000] elapsed: 0:00:00.098801 avg: 0:00:00.000020 | |
test reading data in data/large starting | |
[data/large:1000] elapsed: 0:00:00.020725(avg: 0:00:00.000021), in total: 0:00:00.020725(avg: 0:00:00.000021) | |
[data/large:2000] elapsed: 0:00:00.020510(avg: 0:00:00.000021), in total: 0:00:00.041234(avg: 0:00:00.000021) | |
[data/large:3000] elapsed: 0:00:00.020382(avg: 0:00:00.000020), in total: 0:00:00.061616(avg: 0:00:00.000021) | |
[data/large:4000] elapsed: 0:00:00.019515(avg: 0:00:00.000020), in total: 0:00:00.081131(avg: 0:00:00.000020) | |
[data/large:5000] elapsed: 0:00:00.019756(avg: 0:00:00.000020), in total: 0:00:00.100886(avg: 0:00:00.000020) | |
[data/large:5000] elapsed: 0:00:00.100943 avg: 0:00:00.000020 |
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