Bursty Batch – Small Reprise

In Bursty Batch I talked about how some customers have large amounts of batch work coming in all at once, and how a new WLM function in z/OS 3.1 might be handy in catering for it. And it subsequently occurred to me there is a cheap-to-collect and therefore almost universal method of assessing how bursty batch is. This post is about that method.

One section in SMF 70-1 is the ASID Data Area Section. It has system-level statistics for such things as the number of Started Tasks or TSO userids.

To take a relevant example, you can calculate the average number of batch address spaces by dividing field SMF70BTT by SMF70SAM.

So SMF70SAM is the number of RMF SMF 70 samples in an interval. Which makes SMF70BTT the total of all the sampled batch address spaces in the system. Hence the average. Samples in this context are one per second. So a typical 15-minute interval has 900 samples. We’ll come back to samples in a moment.

An average over 15 minutes is not a great determinant of burstiness. A lot can happen in that time. While one might drop the RMF interval to 5 minutes or even 1, most customers don’t run that way; The volume of RMF SMF records goes way up the shorter the interval. So this sort of interval length is good for benchmarks or Proofs Of Concept (POC’s) – of which I have data from one at the moment.

If an average is not good, it would be nice to compute a maximum. And this is where the neighbouring field to SMF70BTT comes in: SMF70BMM. This field is described in the SMF manual as the maximum number of batch address spaces. Actually, as happens occasionally, this description doesn’t entirely cover the ground. Let me explain why.

I said I’d return to samples, and here we are: The number of batch address spaces is sampled, once for each sample point. It is the maximum of these sampled values that SMF70BMM contains. But why do I make this point? It’s because the sampling process doesn’t rule out there being times – between the sample points – where the value was higher. So SMF70BMM isn’t a perfect measure. If you want perfect measurements you have to spend a lot more resources getting them.

But is SMF70BMM good enough? Take a look at the following graph.

Here I’ve plotted the maximum number of batch address spaces in the interval, and the average. This is real customer data, in case you wondered.

• During the day the average number of batch jobs remains pretty constant, while the maximum varies wildly. You might discern an hourly pattern, with minor peaks on the half hour. This is interesting as it suggests work is thrown in on a timer pop of some sort. You’d have to examine SMF 30 to learn more about this.
• At night there is more variation in the average, and much more in the maximum. The system peaks at over 60 jobs – according to SMF70BMM. Of course, this is a lower bound, but the picture is pretty clear.

From this pair of metrics we can learn a lot about the nature of batch in this system.

One thing we can’t learn that much about is balance between systems. The averages won’t show the fluctuations and the maxima can’t really be compared – as they might not coincide. In this case the average is the better of the two.

So, I think the SMF70BMM approach is valuable. It’s possible the other maxima – for, say, TSO or Started Tasks – is valuable. But I’d think rather less so.

The Making Of

Again I’m writing this on an aeroplane. It’s an Airbus A380 – in British Airways Economy. I make that point because, surprisingly to me, the seat pitch is adequate for a 12.9” iPad Pro.

And, if you were wondering about the title, in my head I misattributed it to Jimi Hendrix. In fact Queen and Paul Rodgers had a song called “Small”. And at the end of the”Cosmos Rocks” they had a song called “Small Reprise’. (You might prefer, though, Roger Taylor’s own “Small”.

I thought originally this post would indeed be a small reprise. In fact it’s quite lengthy. Oh well.

And the smudge on the graph is, of course, obfuscation.