I've got a bunch of rrds being updated every 5min
step = 300
ds[ExeTime].minimal_heartbeat = 600
I need to change this to every 15min.
rrdtool tune allows me to change the heartbeat but not the steps. Can I simply change the heartbeat to 1800? (900 = 15min .. then x2 for heartbeat) ??
Will this leave a bunch of holes making avg/max/etc off?
to change the step of your rrd file it has to be rewritten ... check out https://github.com/oetiker/rrdtool-rrdjig
Related
I am following the tutorial here.
Q1: Why in the final application do we clear all states and delete timer whenever flagState = true regardless of the current transaction amount? I refer to this part of the code:
// Check if the flag is set
if (lastTransactionWasSmall != null) {
if (transaction.getAmount() > LARGE_AMOUNT) {
//Output an alert downstream
Alert alert = new Alert();
alert.setId(transaction.getAccountId());
collector.collect(alert);
}
// Clean up our state [WHY HERE?]
cleanUp(context);
}
If the datastream for a transaction was 0.5, 10, 600, then flagState would be set for 0.5 then cleared for 10. So for 600, we skip the code block above and don't check for large amount. But if 0.5 and 600 transactions occurred within a minute, we should have sent an alert but we didn't.
Q2: Why do we use processing time to determine whether two transactions are 1 minute apart? The transaction class has a timeStamp field so isn't it better to use event time? Since processing time will be affected by the speed of the application, so two transactions with event times within 1 minute of each other could be processed > 1 minute apart due to lag.
A1: The fraud model being used in this example is explained by this figure:
In your example, the transaction 600 must immediately follow the transaction for 0.5 to be considered fraud. Because of the intervening transaction for 10, it is not fraud, even if all three transactions occur within a minute. It's just a matter of how the use case was framed.
A2: Doing this with event time would be a very valid choice, but would make the example much more complex. Not only would watermarks be required, but we would also have to sort the stream by event time, since a realistic example would have to consider that the events might be out-of-order.
At that point, implementing this with a process function would no longer be the best choice. Using the temporal pattern matching capabilities of either Flink's CEP library or Flink SQL with MATCH_RECOGNIZE would be the way to go.
how can I check my requirement of 100 requests are processed in less than 1 second in my gatling3 report. I ran this using jenkins.
my simulation looks like as below
rampConcurrentUsers(1) to (100) during (161 second),
constantConcurrentUsers(100) during (1 minute)
Below is my response time percentile graph of two executions for an interval of one second.
enter image []1 here
What does the min,max here will tell us, i am assuming the percentages 25%-99% are the completion of the request.
Those graph sections are not what you're after - they show the distribution of response times and the number of active users.
So min is the fastest response time
max is the longest
95% is the response time for which 95% of your requests were under
and so on...
So what you could do is look at the section of your graph corresponding to the 100 constant concurrent users injection stage. In this part you would require that the max response time always be under 1 second
(Note: there's something odd with your 2nd report - I assume it didn't come from running the stated injection profile as it has more than 100 concurrent users active)
We would like the updates in our stores tables to be pushed instantly to the corp table, or as fast as possible. Currently it takes 10 - 25 seconds.
Can we increase the push/pull job frequencies in SymmetricDS
Thanks
Here are the referenced properties. They can be adjusted in the engine properties file or in sym_parameter:
job.push.period.time.ms (default 60 secs)
job.pull.period.time.ms (default 60 secs)
job.routing.period.time.ms (default 10 secs)
Yes, it's possible. You'll have to increase the frequency of the router job before doing the same for the push and/or pull job(s):
http://www.symmetricds.org/doc/3.9/html/user-guide.html#_jobs_2
To have data to push or pull it has to be routed and ready for syncing. Change the values of job frequencies in the symmetric-ds.properties file which will take presedence over default properties.
In Task Queues code is executed to connect to the server side
through URL Fetch.
My file queue.yaml.
queue:
- Name: default
rate: 10 / m
bucket_size: 1
In such settings, Tusk performed all at once, simultaneously.
Specificity is that between the requests should be delayed at least 5
sec. Task must perform on stage with a difference> 5 sec. (but
does not parallel).
What are the values set in queue.yaml?
You can't specify minimum delays between tasks in queue.yaml, currently; you should do it (partly) in your own code. For example, if you specify a bucket size of 1 (so that more than one task should never be executing at once) and make sure the tasks runs for at least 5 seconds (get a start=time.time() at the start, time.sleep(time.time()-(5+start)) at the end) this should work. If it doesn't, have each task record in the store the timestamp it finished, and when it start check if the last task ended less than 5 seconds ago, and in that case terminate immediately.
The other way could be store the task data in table. In your task-queue add a id parameter. Fetch 1st task from table and pass its id to task queue processing servlet. In servlet at the end delay for 5 second and feth next task, pass its id and.... so on.
We recently got some data back on a benchmarking test from a software vendor, and I think I'm missing something obvious.
If there were 17 transactions (I assume they mean successfully completed requests) per second, and 1500 of these requests could be served in 5 minutes, then how do I get the response time for a single user? Is this sort of thing even possible with benchmarking? I have a lot of other data from them, including apache config settings, but I'm not sure how to do all the math.
Given the server setup they sent, I want to know how I can deduce the user response time. I have looked at other similar benchmarking tests, but I'm having trouble measuring requests to response time. What other data do I need to provide here to get that?
If only 1500 of these can be served per 5 minutes then:
1500 / 5 = 300 transactions per min can be served
300 / 60 = 5 transactions per second can be served
so how are they getting 17 completed transactions per second? Last time I checked 5 < 17 !
This doesn't seem to fit. Or am I looking at it wrongly?
I presume be user response time, you mean the time it takes to serve a single transaction:
If they can serve 5 per second than it takes 200ms (1/5) per transaction
If they can serve 17 per second than it takes 59ms (1/17) per transaction
That is all we can tell from the given data. Perhaps clarify how many transactions are being done per second.