writes
import time
import pymongo
m = pymongo.MongoClient()
doc = {'a': 1, 'b': 'hat'}
i = 0
while (i < 1000000):
start = time.time()
m.tests.insertTest.insert(doc, manipulate=False, w=1)
end = time.time()
executionTime = (end - start) * 1000 ## Convert to ms
print executionTime
i = i + 1
times.txt
Script with Auth
!/usr/bin/python
import time
import pymongo
import random
import string
import sys
uri = "mongodb://user:pw@localhost:27017/db"
m = pymongo.MongoClient(uri)
x = "e"
for i in xrange(10000):
x = x + random.choice(string.letters)
doc = {'a': 1, 'b': x}
i = 0
while (i < 1000000):
m.Loyalty.insertTest.insert(doc, manipulate=False, w=1)
i = i + 1
Verify the tests
mongos> use devopstest
mongos> db.stats()
{
"raw" : {
"rs0/mongo01:27018,mongo02:27018" : {
"db" : "devopstest",
"collections" : 3,
"objects" : 110053,
"avgObjSize" : 40.00101769147592,
"dataSize" : 4402232,
"storageSize" : 11194368,
"numExtents" : 8,
"indexes" : 2,
"indexSize" : 8380400,
"fileSize" : 201326592,
"nsSizeMB" : 16,
"dataFileVersion" : {
"major" : 4,
"minor" : 5
},
"ok" : 1
},
"rs1/mongo03:27018,mongo04:27018" : {
"db" : "devopstest",
"collections" : 3,
"objects" : 110159,
"avgObjSize" : 40.0010167122069,
"dataSize" : 4406472,
"storageSize" : 11194368,
"numExtents" : 8,
"indexes" : 2,
"indexSize" : 8519392,
"fileSize" : 201326592,
"nsSizeMB" : 16,
"dataFileVersion" : {
"major" : 4,
"minor" : 5
},
"ok" : 1
}
},
"objects" : 220212,
"avgObjSize" : 40,
"dataSize" : 8808704,
"storageSize" : 22388736,
"numExtents" : 16,
"indexes" : 4,
"indexSize" : 16899792,
"fileSize" : 402653184,
"ok" : 1
}
Overview 1 Mio Queries from 1 Machine
Auswertung mit R
> x <- read.csv("C:/cygwin64/home/noqqe/single.txt", as.is=T, header=F)
> head(x)
V1
1 1.1410713
2 0.6830692
3 0.7622242
4 0.6301403
5 0.6930828
6 0.6759167
> hist(x)
> mean(x)
> mean(x[,1])
[1] 0.5329964
>
> summary(x[,1])
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.3819 0.4399 0.4652 0.5330 0.5040 1054.0000
> x <- x[,1]
> sort(x[x>=100])
[1] 102.5641 106.1161 114.6011 139.0510 144.7840 192.0590 193.9261 195.7710 203.4011 204.2670 209.1570 209.5540 210.3591 211.7610 212.6400 486.0430 555.4299
[18] 599.1330 1053.8390
hist(x[x>=100&x<1000],main="Distribution of big queries")
> summary(y)
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.325 0.598 0.786 1.773 1.186 23870.000