We have a scenario where the desire is to have a different number sequence for replacement orders vs sales orders.
Sales Orders have a strictly numeric number sequence defined, ######.
We've created a number sequence for Replacement orders, REP######.
Since both orders live in the SalesTable, this fails when creating the replacement order saying the REP###### number doesn't match the format ######.
1) Is it possible to use two differently formatted number sequences like this?
2) Assuming it is, is there somewhere I can disable some validation to allow this?
1) Yes, this is possible.
2) Take a look how standard AX does this e.g. for fixed assets. You can set up several asset groups with different number sequences that are then used to create numbers for new assets in the groups. So you do not disable a validation, you will customize the code that generates the number to control which number sequence is used to generate the number or to validate the number.
Some further reading:
generate different number sequence number for domestic and international sales order
how to create two number sequences
Related
I want to clean a list of Titles that have numbers after them.
an excerpt of the list:
A Adaptive Behavior 1059-7123 1741-2633 Adaptive Human Behavior and Physiology 2198-7335 Addiction 0965-2140 1360-0443
So how can I tell R not to create a new row after a specific string of numbers, but after a this generel form of 'number number number number - number number number number'?
Disclaimer: This is not a database administration or design question. I did not design this database and I do not have rights to change it.
I have a database in which many fields are compound. For example, a single column is used for acre usage for a district. Many districts have one primary crop and the value is a single number, such as 14. Some have two primary crops and it has two numbers separated by a comma like "14,8". Some have three, four, or even five primary crops resulting in a compound value like "14,8,7,4,3".
I am pulling data out of this database for analytical research. Right now, I am pulling columns like that into R, splitting them into 5 values (padding nulls if there aren't 5 values), and performing work on the values. I want to do it in the database itself. I want to split the value on the comma, perform an operation on the resulting values, and then concatenate the result of the operation back into the original column format.
Example, I have a column that is in acres. I want it in square meters. So, I want to take "14,8", temporarily turn it into 14 and 8, multiply each of those by 4046.86, and get "56656.04,32374.88" as my result. What I am currently doing is using regexp_replace. I start with all rows where "acres REGEXP '^[0-9.]+,[0-9.]+,[0-9.]+,[0-9.]+$'" for the where clause. That gives me rows with 5 numbers in the field. Then, I can do the first number with "cast(regexp_replace(acres,',.*%','') as float) * 4046.86". I can do each of the 5 using a different regexp_replace. I can concatenate those values back together. Then, I run a query for those with 4 numbers, then 3, then 2, and finally the single number rows.
Is this possible as a single query?
Use a function to parse the string and to convert it to desired result. This will allow for you to use a sigle query for the job.
I connect Tableau to R and execute an R function for recommending products. When R ends, the return value is a string which will have all products details, like below:
ID|Existing_Prod|Recommended_Prod\nC001|NA|PROD008\nC002|PROD003|NA\nF003|NA|PROD_ABC\nF004|NA|PROD_ABC1\nC005|PROD_ABC2|NA\nC005|PRODABC3|PRODABC4
(Each line separated by \n indicating end of line)
On Tableau, I display the calculated field which is as below:
ID|Existing_Prod|Recommended_Prod
C001|NA|PROD008
C002|PROD003|NA
F003|NA|PROD_ABC
F004|NA|PROD_ABC1
C005|PROD_ABC2|NA
C005|PRODABC3|PRODABC4
Above data reaches Tableau through a calculated field as a single string which I want to split based on pipeline ('|'). Now, I need to split this into three columns, separated by the pipeline.
I used Split function on the calculated field :
SPLIT([R_Calculated_Field],'|',1)
SPLIT([R_Calculated_Field],'|',2)
SPLIT([R_Calculated_Field],'|',3)
But the error says "SPLIT function cannot be applied on Table calculations", which is self explanatory. Are there any alternatives to solve this ?? I googled to check for best practices to handle integration between R and Tableau and all I could find was simple kmeans clustering codes.
Make sure you understand how partitioning and addressing work for table calcs. Table calcs pass vectors of arguments to the R script, and receive a single vector in response. The cardinality of those vectors depends on the partitioning of the table calc. You can view that by editing the table calc, clicking specific dimensions. The fields that are not checked determine the partitioning - and thus the cardinality of the arguments you send and receive from R
This means it might be tricky to map your problem onto this infrastructure. Not necessarily impossible. It was designed to send a series of vector arguments with one cell per partitioning dimension, say, Manufacturer and get back one vector with one result per Manufacturer (or whatever combination of fields partition your data for the table calc). Sounds like you are expecting an arbitrary length list of recommendations. It shouldn’t be too hard to have your R script turn the string into a vector before returning, but the size of the vector has to make sense.
As an example of an approach that fits this model more easily, say you had a Tableau view that had one row per Product (and you had N products) - and some other aggregated measure fields in the view per Product. (In Tableau speak, the view’s level of detail is at the Product level.)
It would be straightforward to pass those measures as a series of argument vectors to R - each vector having N values, and then have R return a vector of reals of length N where the value returned at each location was a recommender score for the product at that position. (Which is why the ordering aka addressing of the vectors also matters)
Then you could filter out low scoring products from the view and visually distinguish highly recommended products.
So the first step to understanding R integration is to understand how table calcs operate with partitioning and addressing and to think in terms of vectors of fixed lengths passed in both directions.
If this model doesn’t support your use case well, you might be able to do something useful with URL actions or the JavaScript API.
On page 77 of the Aster Analtyics users guide:
http://www.info.teradata.com/eDownload.cfm?itemid=122580002
it says:
“Note that the predicates for different symbols may overlap, and therefore multiple symbols may match the same row.”
Does anyone have any experience with practical use cases where you actually need multiple symbols per row?
Concern is this could explode pretty quickly: for n symbols per row and m rows in a partition, number of symbol combinations per partition is n^m.
e.g., for n=2 and m=50 this results in ~1e15 symbol combinations which we certainly don't want to traverse.
Thx,
Francis
nPath in Aster will never match multiple symbols per row, but multiple symbols may match the same row and nPath will have to choose one of them when forming its result. There will be many cases when this is possible, for example, when you have general page hit (defined as TRUE) and then special pages like START, FINISH, BASKET, etc. then the matching will depend on how pattern is defined.
Not sure if what I'm trying to do is possible or if I need to change my data model.
I have a dimension containing the different amouts a customer can loan so what I wan't to do is see the share of a certain amount compared to total sales.
Pseudo code:
member [Measures].[Share 5000] as 'count([Amount].[5000])/([Measures].[Total Sales], [Time].CurrentMember)'
I assume you want the 5000 included included in your calculation? So if 10 consumers loaned 5000 and the total sales is 100000 the share is (5000*10) / 100000 = 0,5
First you will need a 'number of customers' measure, I don't know if it exists already in your data model otherwise you will have to add it.
Then you can write your calculation something like this:
member [Measures].[Share 5000] as
'
(([Amount].[Total Amount].[5000],[Measures].[Number of Customers])*5000) /
([Amount].[Total Amount],[Measures].[Total Sales])
'
You don't need to include the Time.CurrentMember in your calculation as it does not make any difference in this case. If you put Time in the rows or columns it will be automatically included.