I have a webapplicaton on IIS 6.0. It constantly processes huge amount of short-time requests (15-30 ms process time). When there comes some (1-10) long-time requests all short-time requests slow down (up to 2000-6000 ms process time and more than 100000 for some of them).
Should there be like an isolation between requests in IIS? It isn't supposed that one requests should not interrupt another?
In IIS logs it is look like:
[Normal work]
cs-host sc-status sc-substatus sc-win32-status sc-bytes cs-bytes time-taken
192.168.1.7 200 0 0 2394 524 734
192.168.1.7 200 0 0 2394 524 0
192.168.1.7 200 0 0 2394 524 0
192.168.1.7 200 0 0 2394 524 15
192.168.1.7 200 0 0 2394 524 15
192.168.1.7 200 0 0 2394 524 0
192.168.1.7 200 0 0 2394 524 0
192.168.1.7 200 0 0 2394 524 15
192.168.1.7 200 0 0 2394 524 46
[Slowdown]
cs-host sc-status sc-substatus sc-win32-status sc-bytes cs-bytes time-taken
192.168.1.7 200 0 64 0 522 508251
192.168.1.7 200 0 64 0 522 91827
192.168.1.7 200 0 64 0 522 386438
192.168.1.7 200 0 64 0 522 445947
192.168.1.7 200 0 0 178 522 35545
192.168.1.7 200 0 64 0 522 274130
sc-win32-status 64 means "The specified network is no longer available" but there was no disconnections.
I tried to tune IIS up with tools like IISTuner (http://iistuner.codeplex.com/) it causes no effect.
Why such situation happens?
How to troubleshoot that?
Looks like all the troubles were in appltication itself.
We used ASP.NET form with DataGridView on it (pages were formed on server-side). At the time long-running request comes server has to process it and load data into its memory - so that just blocks other activity.
We rewrite application using ASP.NET MVC (client-side pages) and the trouble was gone.
Related
I am trying to plot some numbers of a data frame using gvisLineChart. The data I am feeding is a data.frame but still I am getting the error that Error: data has to be a data.frame.
My data has one single column, I trimmed the zeros & want to plot the remaining numbers.
My data frame is like below;
mydf$figures
[1] 1250 760 2590 7990 2070 6770 4760 4270 2550 6070 4580 2350 1510 4140 2450 3010 1070 1230 850 490 170 1970 0 0
[25] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Then I trimmed the zeros;
mydf2<- subset(mydf,figures != 0)
mydf2$figures
[1] 1250 760 2590 7990 2070 6770 4760 4270 2550 6070 4580 2350 1510 4140 2450 3010 1070 1230 850 490 170 1970
Now I want to plot the numbers;
library(googleVis)
library(googleCharts)
gvisLineChart(mydf2$figures)
Error in gvisCoreChart(data, xvar, yvar, options, chartid, chart.type = "LineChart") :
Error: data has to be a data.frame.
But, when I am checking the class, it is data.frame
class(mydf2)
[1] "data.frame"
Please help me to understand the error properly & guide me how can I plot the numbers using gvisLineChart. TIA
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I am using centos.
When i am running the command free -m then its showing me below:
total used free shared buffers cached
Mem: 2048 373 1674 10 0 147
-/+ buffers/cache: 225 1822
Swap: 0 0 0
I have run the command "Top" and get the below result:
top - 07:08:01 up 16:09, 3 users, load average: 0.00, 0.00, 0.00
Tasks: 39 total, 1 running, 38 sleeping, 0 stopped, 0 zombie
Cpu(s): 0.0%us, 0.0%sy, 0.0%ni,100.0%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st
Mem: 2097152k total, 381024k used, 1716128k free, 0k buffers
Swap: 0k total, 0k used, 0k free, 150200k cached
PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND
1 root 20 0 19236 1452 1212 S 0.0 0.1 0:00.02 init
2 root 20 0 0 0 0 S 0.0 0.0 0:00.00 kthreadd/23354
3 root 20 0 0 0 0 S 0.0 0.0 0:00.00 khelper/23354
147 root 16 -4 10644 668 400 S 0.0 0.0 0:00.00 udevd
453 root 20 0 179m 1512 1056 S 0.0 0.1 0:00.27 rsyslogd
489 root 20 0 66692 1296 536 S 0.0 0.1 0:00.03 sshd
497 root 20 0 22192 972 716 S 0.0 0.0 0:00.00 xinetd
658 root 20 0 66876 1028 312 S 0.0 0.0 0:00.00 saslauthd
659 root 20 0 66876 764 48 S 0.0 0.0 0:00.00 saslauthd
731 root 20 0 114m 1260 620 S 0.0 0.1 0:00.24 crond
835 ossecm 20 0 10512 492 312 S 0.0 0.0 0:00.32 ossec-maild
839 root 20 0 13088 960 712 S 0.0 0.0 0:00.00 ossec-execd
843 ossec 20 0 12780 2380 620 S 0.0 0.1 0:10.15 ossec-analysisd
847 root 20 0 4200 444 304 S 0.0 0.0 0:00.84 ossec-logcollec
858 root 20 0 5004 1484 468 S 0.0 0.1 0:07.06 ossec-syscheckd
862 ossec 20 0 6388 624 372 S 0.0 0.0 0:00.03 ossec-monitord
870 root 20 0 92420 21m 1620 S 0.0 1.0 0:01.21 miniserv.pl
4363 root 20 0 96336 4448 3464 S 0.0 0.2 0:00.10 sshd
4365 root 20 0 105m 2024 1532 S 0.0 0.1 0:00.03 bash
4615 root 20 0 96776 4936 3460 S 0.0 0.2 0:00.61 sshd
4617 root 20 0 105m 2052 1548 S 0.0 0.1 0:00.20 bash
4674 root 20 0 96336 4452 3460 S 0.0 0.2 0:00.22 sshd
4676 root 20 0 105m 2012 1532 S 0.0 0.1 0:00.06 bash
7494 root 20 0 96336 4404 3428 S 0.0 0.2 0:00.03 sshd
7496 root 20 0 57712 2704 2028 S 0.0 0.1 0:00.01 sftp-server
7719 root 20 0 83116 2700 836 S 0.0 0.1 0:00.10 sendmail
7728 smmsp 20 0 78692 2128 636 S 0.0 0.1 0:00.00 sendmail
7742 root 20 0 402m 14m 7772 S 0.0 0.7 0:00.13 httpd
7744 asterisk 20 0 502m 22m 10m S 0.0 1.1 0:00.11 httpd
7938 root 20 0 105m 756 520 S 0.0 0.0 0:00.00 safe_asterisk
7940 asterisk 20 0 3157m 26m 8508 S 0.0 1.3 0:07.14 asterisk
8066 root 20 0 105m 1568 1304 S 0.0 0.1 0:00.01 mysqld_safe
8168 mysql 20 0 499m 21m 6472 S 0.0 1.1 0:01.44 mysqld
8607 asterisk 20 0 402m 8288 1404 S 0.0 0.4 0:00.00 httpd
8608 asterisk 20 0 402m 8288 1404 S 0.0 0.4 0:00.00 httpd
8611 asterisk 20 0 402m 8284 1400 S 0.0 0.4 0:00.00 httpd
8615 asterisk 20 0 402m 8296 1412 S 0.0 0.4 0:00.00 httpd
Even when i am trying see by disabling the services asterisk,httpd,sendmail,mysqld still its showing 100% cpu usage.
Can anybody know how can i check what is the actual thing which is taking this much CPU usages?
The CPU Usage in top says:
Cpu(s): 0.0%us, 0.0%sy, 0.0%ni,100.0%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st
Your CPU is 100% idle. This is the explanation:
us: user cpu time (or) % CPU time spent in user space
sy: system cpu time (or) % CPU time spent in kernel space
ni: user nice cpu time (or) % CPU time spent on low priority processes
id: idle cpu time (or) % CPU time spent idle
wa: io wait cpu time (or) % CPU time spent in wait (on disk)
hi: hardware irq (or) % CPU time spent servicing/handling hardware interrupts
si: software irq (or) % CPU time spent servicing/handling software interrupts
st: steal time - - % CPU time in involuntary wait by virtual cpu while hypervisor is servicing another processor (or) % CPU time stolen from a virtual machine
I am experimenting pca with R. I have the following data:
V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
2454 0 168 290 45 1715 61 551 245 30 91
222 188 94 105 60 3374 615 7 294 0 169
552 0 0 465 0 3040 0 0 771 0 0
2872 0 0 0 0 3380 0 289 0 0 0
2938 0 56 56 0 2039 538 311 113 0 254
2849 0 0 332 0 2548 0 332 0 0 221
3102 0 0 0 0 2690 0 0 0 807 807
3134 0 0 0 0 2897 289 144 144 144 0
558 0 0 0 0 3453 0 0 0 0 0
2893 0 262 175 0 2452 350 1138 262 87 175
552 0 0 351 0 3114 0 0 678 0 0
2874 0 109 54 0 2565 272 1037 109 0 0
1396 0 0 407 0 1730 0 0 305 0 0
2866 0 71 179 0 2403 358 753 35 107 143
449 0 0 0 0 2825 0 0 0 0 0
2888 0 0 523 0 2615 104 627 209 0 0
2537 0 57 0 0 1854 0 0 463 0 0
2873 0 0 342 0 3196 0 114 0 0 114
720 0 0 365 4 2704 0 4 643 4 0
218 125 31 94 219 2479 722 0 219 0 94
to which I apply the following code:
fit <- prcomp(data)
ev <- fit$rotation # pc loadings
In order to make some tests, I tried to see the data matrix I retrieve when I do keep all the components I can keep:
numberComponentsKept = 10
featureVector = ev[,1:numberComponentsKept]
newData <- as.matrix(data)%*%as.matrix(featureVector)
The newData matrix should be the same as the original one, but instead, I get a very different result:
PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10
2454 1424.447 867.5986 514.0592 -155.4783720 -574.7425 85.38724 -86.71887 90.872507 4.305168 92.08284
222 3139.681 1020.4150 376.3165 471.8718398 -796.9549 142.14301 -119.86945 32.919950 -31.269467 32.55846
552 2851.544 539.6075 883.3969 -93.3579153 -908.6689 68.34030 -40.97052 -13.856931 23.133566 89.00851
2872 3111.317 1210.0187 433.0382 -144.4065362 -381.2305 -20.08927 -49.03447 9.569258 44.201571 70.13113
2938 1788.334 945.8162 189.6526 308.7703509 -593.5577 124.88484 -109.67276 -115.127348 14.170615 99.19492
2849 2291.839 978.1819 374.7567 -243.6739292 -496.8707 287.01065 -126.22501 -18.747873 54.080763 62.80605
3102 2530.989 814.7548 -510.5978 -410.6295894 -1015.3228 46.85727 -21.20662 14.696831 23.687923 72.37691
3134 2679.430 970.1323 311.8627 124.2884480 -536.4490 -26.23858 83.86768 -17.808390 -28.802387 92.09583
558 3268.599 988.2515 353.6538 -82.9155988 -342.5729 12.96219 -60.94886 18.537087 7.291126 96.14917
2893 1921.761 1664.0084 631.0800 -55.6321469 -864.9628 -28.11045 -104.78931 37.797727 -12.078535 104.88374
552 2927.108 607.6489 799.9602 -79.5494412 -827.6994 14.14625 -50.12209 -14.020936 29.996639 86.72887
2874 2084.285 1636.7999 621.6383 -49.2934502 -577.4815 -67.27198 -11.06071 -7.167577 47.395309 51.02962
1396 1618.171 337.4320 488.2717 -100.1663625 -469.8857 212.37199 -1.19409 13.531485 -23.332701 64.58806
2866 2007.261 1387.6890 395.1586 0.8640971 -636.1243 133.41074 12.34794 -26.969634 5.506828 74.13767
449 2674.136 808.5174 289.3345 -67.8356695 -280.2689 10.60475 -49.86404 15.165731 5.965083 78.66244
2888 2254.171 1162.4988 749.7230 -206.0215007 -652.2364 302.36320 40.76341 -1.079259 17.635956 57.86999
2537 1747.098 371.8884 429.1309 9.3761544 -480.7130 -196.25019 -81.31580 2.819608 24.089379 56.91885
2873 2973.872 974.3854 433.7282 -197.0601947 -478.3647 301.96576 -81.81105 14.516646 -1.191972 100.79057
720 2537.535 504.4124 744.5909 -78.1162036 -771.1396 38.17725 -36.61446 -9.079443 25.488688 78.21597
218 2292.718 800.5257 260.6641 603.3295960 -641.9296 187.38913 11.71382 70.011487 78.047216 96.10967
What did I do wrong?
I think the problem is rather a PCA problem than an R problem. You multiply the original data with the rotation matrix and you wonder then why newData!=data. This would be only the case if the rotation matrix would be the identity matrix.
What you probably were planning to do is the following:
# Run PCA:
fit <- prcomp(USArrests)
ev <- fit$rotation # pc loadings
# Reversed PCA:
head(fit$x%*% t(as.matrix(ev)))
# Centered Original data:
head(t(apply(USArrests,1,'-',colMeans(USArrests))))
In the last step you have to center the data, because the function prcomp centers them by default.
Suppose I start a TCP session and close it after some times, now how can I know how much or the size of packets that have been used in the overall session?
Adding to above : Tshark is a tool to sniff packets on the linux machine:
Here is an example :
cmd : tshark -n -T fields -e ip.src -e tcp.seq -e tcp.len -i
ip.src = source ip |
tcp-seq = sequence |
**tcp.len = lenght of tcl packets**
Here is the snapshot: third column is the length of tcp packets
198.252.206.140 14766 117
192.168.1.2 2583 0
192.168.1.2 2583 632
190.93.245.58 1 679
192.168.1.2 522 0
198.252.206.140 0 0
192.168.1.2 1 0
198.252.206.140 1 1440
192.168.1.2 580 0
198.252.206.140 1441 1283
192.168.1.2 580 0
198.252.206.140 14883 145
192.168.1.2 1 556
192.168.1.2 3215 0
192.168.1.2 522 564
190.93.245.58 680 0
190.93.245.58 680 1440
192.168.1.2 1086 0
190.93.245.58 2120 1095
192.168.1.2 1086 0
198.252.206.17 1 1440
^C192.168.1.2 557 0
198.252.206.17 1441 208
192.168.1.2 557 0
192.168.1.2 557 585
192.168.1.2 1086 607
190.93.245.58 3215 343
192.168.1.2 1693 0
198.252.206.17 1649 270
You'll have to use a packet sniffer like WireShark. Even if you have very structured data that sends out at sufficiently delayed intervals it's not really possible to pre-compute how that data will be sent. There's too many variables over which you have minimal, or no, control.
There are 6 NGINX processes in the server. Ever since NGINX is started, the RES/VIRT values kept growing until it is out of memory. Is it indicating there is a memory leak?
PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND
1941 root 20 0 621m 17m 4144 S 290.4 0.1 8415:03 mongod
16383 nobody 20 0 1675m 1.6g 724 S 21.0 5.2 13:19.30 nginx
16382 nobody 20 0 1671m 1.6g 724 S 17.2 5.1 13:21.39 nginx
16381 nobody 20 0 1674m 1.6g 724 S 15.3 5.1 13:28.45 nginx
16380 nobody 20 0 1683m 1.6g 724 S 13.4 5.2 13:24.77 nginx
16384 nobody 20 0 1674m 1.6g 724 S 13.4 5.1 13:19.83 nginx
16385 nobody 20 0 1685m 1.6g 724 S 13.4 5.2 13:25.00 nginx
Try look on this ngx_http_limit_conn_module nginx module.
Also take a look to client_max_body_size