Multi-Line is only way to go when you have a potentially huge dimension only a tiny bit of which should be available to end-user at a time. Like employee planning, whole dimension of 10k people, strictly less than a 100 in department. So you create a fake dimension of 1..100 and add an Employee name column, decreasing cube volume by 100. Access tables + cut-down might help, but it’s sometimes better to allow people pick up any employee,client, product given up that there won’t be more than fixed number of rows.

Main problem with this modeling technique arises when it’s time to import data in such cube. That data usually doesn’t have an 1..100 running count attached, so it’s your task to add it.

In this post I’ll sum up the ideas of how to calculate running count split by elist (that’s usual, ain’t it?).

As a example, I’ll use this simple table

And you have departments as an elist, so you have to number rows so that numbering will restart for each dept. Numbering requires an order so let’s alphabetical order of employee names.

So this is what we want to get:

Source code for table:

WITH data_t AS
(
SELECT 'Finance' DEPT,'Pete' EMP, 100 SALARY FROM sys.dual
UNION ALL
SELECT 'Finance','Ann', 200  FROM sys.dual
UNION ALL
SELECT 'Finance','Jo', 300  FROM sys.dual
UNION ALL
SELECT 'HR','Nick', 100  FROM sys.dual
UNION ALL
SELECT 'HR','Sam', 200  FROM sys.dual
)
SELECT * FROM data_t

So what are our choices?

0 Use a framework package as source and a running-count calculation in query subject

Only since Cognos 8.2, slower than some variants, but definitely most cognos-style.

Create a query subject and add an expression of running-count like

running-count ( [SALARY] for [DEPT] )

1 Add sub query to count this rows position within elist slice.

That’s “works everywhere, but terribly slow” solution. Easy to do, use it if you’re about to import a 100-1000 rows table and really don’t care about time it takes.

Sample code:

SELECT DEPT,EMP,SALARY,
(
SELECT COUNT(*)
FROM data_t T2
WHERE T2.DEPT = T.DEPT
AND T2.EMP <= T.EMP
) AS running_count
 FROM data_t T
 ORDER BY dept,running_count

2 Use SQL’99 standard rownum() function

Way much better optimized (in Oracle ) ) than subquerying variant above. Problem is: works only on Oracle, Ms SQL 2005+ and DB2. Ms SQL 2000 import — sorry, no SQL’99 there. See original syntax

Sample code:

SELECT DEPT,EMP,SALARY, ROW_NUMBER()
OVER (partition BY dept ORDER BY emp) FROM data_t

3 Use cursors to calculate rownumber

Brute-force solution, non portable, as fast as possible. Only way to do serious lifting in MS SQL 2000.

I’ll place sample code for Ms SQL 2000 if somebody needs it

PS You’re on Oracle 10g+? Lucky you, you can also try to do running_counts it via oracle model by clause.

Just a sketch, of course.

I’ve just put Russian Translation of Confluence on Atlassian, hopefully it will help someone.

That was a rather pathetic preambula. Let’s get straight to business.

Problem.
On recent project I was doing some technical support (dllhost problems, if you recall, and more). It is a rather mature installation (about 8 months of production) with quite a number of servers, so logs contained around 100 Mb of data. And common question was — ok, this error, did it appear before? When? Accompanied by what errors? What’s the overall trend? Common patterns? Charts?
All that analytical questions posed up on EP error logs.

As we all know, Cognos Contributor errors are recorded into PlanningErrorLog.csv files. And those log files contain rather detailed information, including ep version, module, time and, of course, error description.

I’ve tried to find some complete solution, but as usual on Microsoft platform, there are only paid tools, yet not solving the task completely.

Solution.
Having a whole Cognos 8 BI at finger-tips, I thought it would be nice to have all that errors in PowerPlay cube. I’m an OLAP-guy, after all.

So, technically the task was divided into 3 parts:

1. Gathering the logs
2. Forming a datasource for Transformer
3. Creating a Transformer model and cube

Step 1 is solved by .bat file — I’ll post it in separate as “Backing up with timestamping”
Step 3 is quite straight-forward, if you have a single file, containing errors from multiple ones, except for time dimension as usual.
More details on forming a datasource. Got no time? Skip to this scheme for overall picture.
Merging the logs.
At first I thought it was a rather simple task since the source files are csv (comma separated) and they just need to merged n to 1 with some additional transformations (adding top level error categories based on error desc, for example).
It’s never easy, I must admit.
Well, csv is comma-separated for all but Cognos, PlanningErrorLogs are tab-separated. That’s not a problem, let’s get n tab files to csv.
Planning logs contain some wonderful pack of unprintable chars(meant for Excel easy opening I hope, because there is no reason otherwise). In those chars there are some kind “EOF” chars, for example (I can see only their hex codes anyway), so VBScript cannot parse those files line by line correctly. There is a variant to open the file in Excel and save it to “normal csv”, but that’s impossible with 60 Mb log file I’ve got here.
For sake of my nerves and Internet space I won’t describe all other problems like parsing returned sql statements in error descriptions (those contain tabs and “;” in the same line).

Since I like Python much the final script is .py. It takes a directorу containing logs, merges them into 1 file, adds timesort values and error categories.

So that’s the final scheme.

We add client servers to this sending net and plan to use 8 BI Event Notifier as technical support catalyst.

—–
I’m eager to give out the scripts for the same reasons as I do this blog (also a dim hope that overall Cognos support will get better), so if you’re interested – mail bark-bark ykud.com. A rather good error categorization can be created with some joined effort, imho.

Recent versions of IETab addon allow to open tabs, using IE as renderer, and, moreover, start contrib apps in FireFox tabs.

So I don’t have to switch browser anymore. Hoooray?

Adaptive Planning – first open-source planning application? (just a less-featured version, but that’s a start).

Compiere + some OS BI (including planning) can be a solution in future.