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https://issues.apache.org/jira/browse/FLINK-3290?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Chesnay Schepler updated FLINK-3290:
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Issue Type: Improvement (was: Bug)
> [py] Generalize OperationInfo transfer
> --------------------------------------
>
> Key: FLINK-3290
> URL: https://issues.apache.org/jira/browse/FLINK-3290
> Project: Flink
> Issue Type: Improvement
> Components: Python API
> Affects Versions: 0.10.1
> Reporter: Chesnay Schepler
> Assignee: Chesnay Schepler
> Fix For: 1.00
>
>
> A set number of arguments is transferred whenever a user defines an
> operation. For a CSV Source for example these are delimiters/filepath, for a
> map function only the set ID'S are transferred. As such, for all operators a
> separate routine is defined that governs which arguments are transferred.
> While working on FLINK-3275 I realized that adding a new argument/parameter,
> in this case parallelism, is not as straightforward as it could be. Most
> newly added operators will require a new routine; whereas adding new
> arguments may require the modification of multiple routines. Over times, this
> is bound to become a big mess.
> All arguments are stored in an OperationInfo object, which also contains
> default values for all unused arguments. I want to generalize the whole
> affair by transferring all arguments, used or not.
> This will reduce clutter, make it easier to add new parameters (only 4 new
> lines needed, 2 for defining new fields inside Java/Python OperationInfo
> Classes; 1 each for sending/receiving the new argument) and will make the
> transfer consistent across all operations.
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