Is there some way like a script we can run n times in a loop to benchmark classic ASP CPU computation time and disk I/O from server to server? That is, run on a local workstation, then a local Pentium dev server with rotational disk, then a entry level production server with RAID 01, then a virtualized cloud production server, then a quad-core xeon server with SSDs, etc. So we can see "how much faster" the servers are from one to the next. The only tricky part is testing SQL and I/O testing. Perhaps the script could compute at random and then write a 10gb file to disk or a series of 1gb files and then time how long it takes to create them, write them, copy/move them, read them in and calculate and MD5 on them and spit out the results to the client, say, in a loop of n times. What we're trying to do is prove with a control set of code and tasks server performance from one machine to the next.
-- EDIT --
Of course, as pointed out by jbwebtech below, VBS does indeed have its own Timer() function, which I had completely forgotten about. And so...
Well you can just get the time before you run each process, run the process and then deduct it from the current time...
<%
Dim start
start = Timer()
'Run my process...
...
...
Response.Write(Timer()-start))
%>
It's perhaps not perfect, but it will give you back a fairly useful reading. The
result is a Double precision number; the first part of the result is the number of days that have passed since you started, and the fractional part, obviously fractions of days. You can work this out into time if you wish by dividing by the appropriate amounts (i.e. 24 hours in a day, 60 minutes in an hour, 1440 minutes in a day, 60 seconds in an hour, 86400 seconds in a day etc.). The Timer() function gives you the time in seconds and milliseconds taken to execute the code block.
Related
We have a batch process that executes every day. This week, a job that usually does not past 18 minutes of execution time (real time, as you can see), now is taking more than 45 minutes to finish.
Fullstimmer option is already active, but we don't know why only the real time was increased.
In old documentation there are Fullstimmer stats that could help identify the problem but they do not appear in batch log. (The stats are those down below: Page Faults, Context Switches, Block Operation and so on, as you can see)
It might be an I/O issue. Does anyone know how we can identify if it is really an I/O problem or if it could be some other issue (network, for example)?
To be more specific, this is one of the queries that have increased in time dramatically. As you can see, it is reading from a data base (SQL Server, VAULT schema) and work and writing in work directory.
Number of observations its almost the same:
We asked customer about any change in network traffic, and they said still the same.
Thanks in advance.
For a process to complete, much more needs to be done than the actual calculations on the CPU.
Your data has te be read and your results have to be written.
You might have to wait for other processes to finish first, and if your process includes multiple steps, writing to and reading from disk each time, you will have to wait for the CPU each time too.
In our situation, if real time is much larger than cpu time, we usually see much trafic to our Network File System (nfs).
As a programmer, you might notice that storing intermediate results in WORK is more efficient then on remote libraries.
You might safe much time by creating intermediate results as views instead of tables, IF you only use them once. That is not only possible in SQL, but also in data steps like this
data MY_RESULT / view=MY_RESULT;
set MY_DATA;
where transaction_date between '1jan2022'd and 30jun2022'd;
run;
while using nagios with multiple hosts spread over the network,hosts status shows a recognizable lag and takes a long time to reflect on nagios server cgi.Thus what is the optimal nrpe/nagios configration to speed up the status process for a distributed host environment.
In my case I use nagios core 4.1
nrpe 1.5
server/clients: Amazon ec2
The GUI is usually only updated once each minute (automatically), though clicking refresh can provide you with 'nearly' the latest information. I say nearly because there is a distinct processing loop inside of the Nagios core that causes it to never be real time. NRPE is going to run at the speed of your network connection - it does little else besides sending and receiving tiny amounts of data. About the only delay here is the time it takes to actually perform the check and send back the response - which, of course, has way to many factors to mention. Try looking at the output of
[nagioshome]/bin/nagiostats
There are several entries that tell you:
'Latency' - the time between when the check was scheduled to start, and the actual start time.
'Execution Time' - the amount of time checks are actually taking to run.
These entries will have three numbers, which are; Min / Max / Avg
High latency numbers (in my book that means Avg is greater than 1 second) usually means your Nagios server is over worked. There are a few things you can do to improve latency times, and these are outlined in the 'nagios.cfg' file. This latency has nothing to do with network speed or the speed of NRPE - it is primarily hardware speed. If you're already using the optimal values specified in nagios.cfg, then its time to find some faster hardware.
High execution times (for me an Avg greater than 5 seconds) can be blamed on just about everything except your Nagios system. This can be caused by faulty networks (improper packet routing), over loaded networks, faulty and/or poorly designed checks, slow target systems, ... the list is endless. Nothing you do with the Nagios and/or NRPE configs will help lower these values. Well, you could disable NRPE's encryption to improve wire time; but if you have encryption enabled in the first place, then its not likely you'd want it disabled.
I'm using a virtual server in U.S.A/Texas and its time is synchronized with "Time.windows.com". I too have in Canada/Quebec 3 PCs with a time synchronized with the same internet time. Unfortunately, my server in Texas is 40 seconds less than my 3 others PCs in Canada.
All PCs use the same time zone (UTC-5). The only difference is the country set in "Region and Language/Location"
Can someone explain how is this possible.
Thanks
See the following article it explains the (not) working of time synchronize:
http://www.pretentiousname.com/timesync/
In short:
The time synchronize job only runs once a week, and because the interal clocks of computers are unreliable you get a time difference..
Solution is to create a special sync Task that runs more often to keep the time up to date.. (al explained in the article)
I am analyzing a web application and want to predict the maximum users that application can support. Now i have the below numbers out of my load test execution
1. Response Time
2. Throughput
3. CPU
I have the application use case SLA
Response Time - 4 Secs
CPU - 65%
When i execute load test of 10 concurrent users (without Think Time) for a particular use case the average response time reaches 3.5 Seconds and CPU touches 50%. Next I execute load test of 20 concurrent users and response time reaches 6 seconds and CPU 70% thus surpassing the SLA.
The application server configuration is 4 core 7 GB RAM.
Going by the data does this suggests that the web application can support only 10 user at a time? Is there any formula or procedure which can suggest what is the maximum users the application can support.
TIA
"Concurrent users" is not a meaningful measurement, unless you also model "think time" and a couple of other things.
Think about the case of people reading books on a Kindle. An average reader will turn the page every 60 seconds, sending a little ping to a central server. If the system can support 10,000 of those pings per second, how many "concurrent users" is that? About 10,000 * 60, or 600,000. Now imagine that people read faster, turning pages every 30 seconds. The same system will only be able to support half as many "concurrent users". Now imagine a game like Halo online. Each user will be emitting multiple transactions / requests per second. In other words, user behavior matters a lot, and you can't control it. You can only model it.
So, for your application, you have to make a reasonable guess at the "think time" between requests, and add that to your benchmark. Only then will you start to approach a reasonable simulation. Other things to think about are session time, variability, time of day, etc.
Chapter 4 of the "Mature Optimization Handbook" discusses a lot of these issues: http://carlos.bueno.org/optimization/mature-optimization.pdf
I have driver program that runs a set of 5 experiments - basically the driver program just tells the program which dataset to use (of which there are 5 and they're very similar).
The first iteration takes 3.5 minutes, the second 6 minutes, the third 30 minutes and the fourth has been running for over 30 minutes.
After each run the SparkContext object is stopped, it is then re-started for the next run - I thought this method would prevent slow down, as when sc.stop is called I was under the impression that the instances were cleared of all their RDD data - this is at least how it works in local mode. The dataset is quite small and according to Spark UI only 20Mb of data on 2 nodes is used.
Does sc.stop not remove all data from a node? What would cause such a slow down?
call sc.stop after all iterations are complete. Whenever we stop SparkContenxt and invoke new, it require time to load spark configurations,jars and free driver port to execute the next job.
and
using config --executor-memory you can speed up the process, depending on how much memory you have in each node.
Stupidly, I had used T2 instances. Their burstable performance means they only work on full power for a small amount of time. Read the documentation thoroughly - lesson learnt!