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gitguto
Contributor III
Contributor III

Creating new Fields from existing ones.

Hello everyone,

I have a table like this:

Material Component level position qty
Car Car 0 1 1
Car Engine 0.1 1 1
Car Seats 0.1 2 4
Car Structure 0.1 3 1
Car Piston 0.1.1 1 1
Car Alternator 0.1.1 2 1
Car Valves 0.1.1 3 8
Car Seat Structure 0.1.2 1 1
Car Cushion 0.1.2 2 500
Car Cottom 0.1.2.2 1 400
Car Plastic 0.1.2.2 2 100

 

Explanation: This table shows all the parts I need to make 1 car and the components that I need to make these parts. And further, the material I need to make these components.

To make 1 car, I need: 1 Engine, 4 Seats and 1 Structure. 

To make 1 Engine, I need: 1 Piston,  1 Alternator, and 8 valves.

To make 1 Seat, I need: 1 Seat Structure and 500g of Cushion.

To make 1 Cushion, I need: 400g of Cottom and 100g of Plastic.

P.S. I left the table 'incomplete' to better reflect my real data. I have different level steps for different Materials, in this case, the further we go is 4 levels down: Car - Seat - Cushion - Cottom/Plastic. But mind that for other materials I can go up to 14 levels down with multiple steps down the way.

 

The "level" field is a pathway to understanding at which level we are, and to understanding what material is composed by that component. 

 

What I need to do is to be able to navigate through this levels, in a drop-down dimension. I need a bar chart in which the user can select "Car" among other materials and the chart would filter down to the first level, that is: Engine, Seats, Structure. Than the user could select one of the parts, if the user select Seat, it would filter down to Cushion and Seat Structure, and so on. The Measure would be the qty field.

My problem is that I can't use the same field in multiple levels of the drop-down master dimension, as any filter applied to it would be referencing itself.

Any solution for this problem would be appreciated it, either on the load script, maybe exploding each level in a new field, or by set analysis. My dataset is very large, so maybe a set analysis approach would be more efficient.

I've tried using the len(level) as the dropdown rule, but couldnt get the result I need.

 

Labels (2)
1 Solution

Accepted Solutions
oskartoivonen
Partner - Contributor III
Partner - Contributor III

This appears to be a typical hierarchy scenario. You need to transform your data into child-parent relationships and run it through a Hierarchy-LOAD.

Example data:

Component ChildID ParentID
Car 1  
Engine 11 1
Seats 12 1
Structure 13 1
Piston 111 11
Alternator 112 11
Valves 113 11
Seat Structure 121 12
Cushion 122 12
Cottom 1221 122
Plastic 1222 122

View solution in original post

5 Replies
Digvijay_Singh

In your data how do you identify that Piston(0.1.1) is a child of Engine(0.1) and not a child of  Seats(0.1) because both Engine and Seat has got level 0.1?

gitguto
Contributor III
Contributor III
Author

The level field is composed by the last level&position

So the last '1'  refers to the position inside the level 0.1.

So:
0 = Car (only item in the level, position = 1)

0.1 = refers to all materials that are part of the level 0, position 1

0.1.1 = refers to all materials that are part of level 0.1, position 1.


Piston(0.1.1)

Component Level Position
Engine 0.1 1
Seats 0.1 2
Structure 0.1 3
gitguto
Contributor III
Contributor III
Author

I was able to create new columns with the levels with something like this in the load script:

if(len(level) = 1, matnr_act, '') as First,
if(len(level) = 3, matnr_act, '') as Second,
if(len(level) = 5, matnr_act, '') as Third,
if(len(level) = 7, matnr_act, '') as Forth

This generated the following table, but WITHOUT THE VALUES IN RED. Because the script is not able to find the relationship between level and position.

Material Component level position qty len(level) First Second Third Forth
Car Car 0 1 1 1 Car      
Car Engine 0.1 1 1 3 Car Engine    
Car Seats 0.1 2 4 3 Car Seats    
Car Structure 0.1 3 1 3 Car Structure    
Car Piston 0.1.1 1 1 5 Car Engine Piston  
Car Alternator 0.1.1 2 1 5 Car Engine Alternator  
Car Valves 0.1.1 3 8 5 Car Engine Valves  
Car Seat Structure 0.1.2 1 1 5 Car Seats Seat Structure  
Car Cushion 0.1.2 2 500 5 Car Seats Cushion  
Car Cottom 0.1.2.2 1 400 7 Car Seats Cushion Cottom
Car Plastic 0.1.2.2 2 100 7 Car Seats Cushion Plastic

 

If I could complete the table with the values in red, this would solve my problem.

oskartoivonen
Partner - Contributor III
Partner - Contributor III

This appears to be a typical hierarchy scenario. You need to transform your data into child-parent relationships and run it through a Hierarchy-LOAD.

Example data:

Component ChildID ParentID
Car 1  
Engine 11 1
Seats 12 1
Structure 13 1
Piston 111 11
Alternator 112 11
Valves 113 11
Seat Structure 121 12
Cushion 122 12
Cottom 1221 122
Plastic 1222 122
gitguto
Contributor III
Contributor III
Author

Thank you very much! Hierarchy load was exactly what I needed. I didn't know it existed.

https://help.qlik.com/en-US/sense/May2022/Subsystems/Hub/Content/Sense_Hub/DataSource/hierarchies.ht...