Understand that with this question, I am trying to understand the logic.
I've worked a lot of hours over the last 4 days so I'm not sure I am
thinking straight anymore. :(
Wouldn't it be more efficient to just run 5 SQL statements like the
following instead of the 6 discussed earlier?
Update file set vendor = '0'||vendor where vendor <> ' '
-----Original Message-----
From: MIDRANGE-L <midrange-l-bounces@xxxxxxxxxxxxxxxxxx> On Behalf Of Kevin
Bucknum
Sent: Thursday, February 25, 2021 9:27 AM
To: midrange-l@xxxxxxxxxxxxxxxxxx
Subject: Re: Need some help with SQL case/when performance
You are correct. I thought about that after I typed the second part. So 6
passes or 5. But each pass should be more of a "set" transaction, and
hopefully will run faster. I've had good luck before when I had multiple
ways to reformat data based on contents with making multiple passes instead
of one all encompassing pass.
On Thu, 2021-02-25 at 09:20 -0500, smith5646midrange@xxxxxxxxx wrote:
I'm not understanding your two passes?
I assume that you mean pass 1 will prefix the 0 on all 5 fields whether it
is blank or not and pass 2 will clean up what have a value of a single 0
only ("0 ") but I can't do that with a single SQL so I have to run 5
SQLs to clean up the single 0 so now I am running 6 passes...
Update to set all fields with the 0 prefix
Update file set vendor = ' ' where vendor = '0 '.
Update file set maxinv = ' ' where maxinv = '0 '.
And 3 more, one for each remaining field.
What did I miss?
-----Original Message-----
From: MIDRANGE-L <
<mailto:midrange-l-bounces@xxxxxxxxxxxxxxxxxx>
midrange-l-bounces@xxxxxxxxxxxxxxxxxx
On Behalf Of Kevin
Bucknum
Sent: Thursday, February 25, 2021 8:54 AM
To:
<mailto:midrange-l@xxxxxxxxxxxxxxxxxx>
midrange-l@xxxxxxxxxxxxxxxxxx
Subject: Re: Need some help with SQL case/when performance
Two pass it? First pass slug the 0. Second pass blank out any with just
zero? Make 5 runs updating one field at a time with a where clause?
On Thu, 2021-02-25 at 08:48 -0500,
<mailto:smith5646midrange@xxxxxxxxx>
smith5646midrange@xxxxxxxxx
wrote:
We are converting files and I have a BIG performance problem.
The files are being converted via CHGPF. Some of the fields contain numeric
values stored in alpha fields. The client does not like to use null capable
fields so I think they did this to identify "no value". I also know this
file is pretty old so null might not have been widely used back when it was
created.
For an example of the data.our 5 digit vendor is stored in a 5A field.
After the CHGPF, it is a 6A field so the vendor is stored as "12345 ". I am
running an SQL that inserts a 0 in front so it will be "012345". However,
not all vendors have a value. Some are blank and we don't want to create
the value "0 ".
I used the logic (forgive the syntax if it is wrong)
Vendor = case when vendor = ' ' then ' ' else '0' || vendor end
The problem that I am having is the performance on this seems horrible. We
have a file of 68M records and it has 5 of these types of fields. Therefore
the case/when exists 5 times in the update. The SQL update ran for about 12
hours. When I created an RPGLE with normal F Specs and reads and writes, it
ran in 20 minutes. I have run this several times on several different
machines and the performance seems similar on all runs.
The dilemma with this is the values in the records vary. Of the 5 fields,
how many of them in each record will be populated and which ones will vary.
So, my options as I saw them were either using the case/when or running 5
different SQL updates each updating a single field where a clause selecting
that field running over 68M rows each time. At the time, the case/when
seemed like the better option.
Does anyone have any thoughts on what might be going on that would cause
such an extreme difference between the SQL case/when and native RPGLE? Does
anyone have a different idea how to approach this using SQL? I can go back
to the RPG logic but it seems "old school".
This request is strictly for ideas on conversion. I can't change the field
types or allow null or change the programs that are using them.
Thanks in advance.
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[
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Senior Programmer Analyst
MEDDATA / MEDTRON
120 Innwood Drive
Covington LA 70433
Local: 985-893-2550
Toll Free: 877-893-2550
https://www.medtronsoftware.com
CONFIDENTIALITY NOTICE
This document and any accompanying this email transmission contain
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