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Smile.. I was thinking the exact same thing.

Now if you meant cache, that might explain it.

Jim Oberholtzer
Agile Technology Architects



On May 13, 2021, at 6:32 PM, Leo Burkett <lburkett99@xxxxxxxxx> wrote:

How is a file pulled off hard disk and placed somewhere in single-level
storage? I thought single-level storage referred to a single address space
spanning both RAM and disk.

Rob Berendt, you are a bad influence on me.

Leo Burkett

-----Original Message-----
From: RPG400-L On Behalf Of x y
Sent: Thursday, May 13, 2021 7:26 PM
To: RPG programming on IBM i <rpg400-l@xxxxxxxxxxxxxxxxxx>
Subject: Re: native i/o and RCAC - performance

Lots of reasons performance could be different, not the least of which is
the possibility that the file's been pulled off disk hard disk and is
sitting somewhere in single-level storage. I'd run this test at least 10
times in succession, alternating with/without RCAC, to tamp down system
workload and the other unseen factors that play havoc with performance
measurement. My development partition has 245 jobs running--a handful of
QINTER's, one user daemon, and a handful of

It seems that this feature is extremely useful in some very specific use
cases, primarily to protect financial and employee-confidential data, but
not the most effective for dealing with performance issues. Another approach
is to create a covered index/access path, where all the fields/columns
needed for a given query are included in the "logical".

On Thu, May 13, 2021 at 5:57 AM Jay Vaughn <jeffersonvaughn@xxxxxxxxx>
wrote:

Can anyone explain or even theorize when applying RCAC to a file, how
it boosts the read performance of the file under native i/o?

Example:

file containing 5M rows...
simple RPG pgm in for loop with reads...

without RCAC applied
elapsed time - 23s
processing time - 1.544

with RCAC applied (alter table theTable activate column access
control) elapsed time - 4s processing time - 1.413

drastic change in elapsed time - small change in processing time.

There is also a smaller gain when using SQL but not as much as native i/o.

tia

Jay
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