you can do an operation on all fields along the lines of:
import cascading.tuple.{ Tuple => CTuple }
pipe.map(Fields.ALL -> Fields.ARGS){ (ctuple: CTuple) => ... }
however this does not give you access to the field names
On Fri, Jun 30, 2017 at 5:13 PM, <[email protected]> wrote:
> Here is the question:
>
> Assume I have a pipe and I want to rename all the fields in the pipe
> programmatically, meaning that I don't want to hard code the field names in
> my code. Any idea how I can do this?
>
> As a concrete example, assume I have a pipe with two fields: "name" and
> "age" and I want to rename these fields to "employee_name" and
> "employee_age". Obviously the natural solution is to write a piece of code
> as below:
>
> pipe.rename(('name, 'age) -> ('employee_name, 'employee_age))
>
> or
>
> pipe.rename(new Fields("name", "age") -> new Fields("employee_name",
> "employee_age"))
>
> However, what I need is to be able to iterate through all fields in the
> pipe without knowing their names.
>
> There are a couple of methods (resolveIncomingOperationArgumentFields and
> resolveIncomingOperationPassThroughFields) callable on a pipe which look
> promising but the issue is that they both take and input argument of type
> cascading.flow.planner.Scope which I don't know where can I get it from in
> a scalding job.
>
> Another solution that comes to my mind is using "each" method on the pipe
> and implementing a cascading function and pass it to the each statement.
> But I was now able to find any sample code for that either.
>
> Thanks!
>
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