parameterizing the transformation functions
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parameterizing the transformation functions
Today, i have got a question from a developer who is working in Ab Initio.
Can we parameterize the functions?
e.g:
we are using trim(col).
I need to parameterize the trim and get the function in run time.
e.g
something like TRIM_PAR(col).
It's not possible in datastage .
Any thoughts why this feature is not provided?
Thanks
Can we parameterize the functions?
e.g:
we are using trim(col).
I need to parameterize the trim and get the function in run time.
e.g
something like TRIM_PAR(col).
It's not possible in datastage .
Any thoughts why this feature is not provided?
Thanks
pandeeswaran
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Re: parameterizing the transformation functions
Your proof?pandeesh wrote:It's not possible in datastage.
I believe it is possible, but I'm not sure what you're asking. Could you provide a concrete example?
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Re: parameterizing the transformation functions
I think it's not possible because the syntax editor in the transformer derivation won't accept something that looks like <parameter name>(....), which, I think, is what is being asked - i.e. to have the actual function to be called be a parameter.
Re: parameterizing the transformation functions
I'm withholding comment until I understand what the above is supposed to achieve. Right now I don't see the point, so much like Ray I'm looking for a better, more concrete example.pandeesh wrote:we are using trim(col).
I need to parameterize the trim and get the function in run time.
e.g something like TRIM_PAR(col).
-craig
"You can never have too many knives" -- Logan Nine Fingers
"You can never have too many knives" -- Logan Nine Fingers
If I understand it correctly , you are trying to parameterize a function ...Suppose you have rule table which gets populated & depending on the value , you need to either A + B or A - B or A * B . Here the operand between A , B is parameter . I tried this requirement sometime back but didn't do that ..there are couple of posts related to this requirement ..I guess you need search by rule engine keyword ..
Yes in abinitio , you can do it very easily ..when you deploy a graph in abinitio, it's get converted into simple KSH ...In datastage , things are little complicated as it get converted into OSH & C++ compiled code .
Yes in abinitio , you can do it very easily ..when you deploy a graph in abinitio, it's get converted into simple KSH ...In datastage , things are little complicated as it get converted into OSH & C++ compiled code .
Nag
Not really sure how you drew that conclusion from the 'trim' example posted. So, we wait.nagarjuna wrote:If I understand it correctly , you are trying to parameterize a function ...Suppose you have rule table which gets populated & depending on the value , you need to either A + B or A - B or A * B . Here the operand between A , B is parameter .
-craig
"You can never have too many knives" -- Logan Nine Fingers
"You can never have too many knives" -- Logan Nine Fingers
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I don't believe that will work, but do try it and let us know.
With only one additional level of redirection it would be easily done. The general function would incorporate a dispatcher of some kind based on the first argument value.
With only one additional level of redirection it would be easily done.
Code: Select all
GeneralFunction(<param>,<arg-list>)
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Version 8.7 introduces a Data Rules stage. From the description, you would use Information Analyzer to build the rules based on a variety of functions. Then data can pass all rules to validate, fail on one or more rules, etc. I don't think a rule engine is what this topic is about exactly, although it may be implied somewhat.
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Re: parameterizing the transformation functions
I will take a stab at it... Parallel Transformer code is compiled before run time. Perhaps Ab Initio is interpreted at run time? Back in the day, I was taught that compiled code always performs faster than interpreted code.pandeesh wrote:Any thoughts why this feature is not provided?
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Data Rule Definitions can be created in either DataStage or Information Analyzer. They are compatible - rule definitions published into the common metadata repository by one tool can be used by the other.
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