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From Koert Kuipers <>
Subject frustration with field names in Dataset
Date Thu, 02 Feb 2017 15:39:26 GMT
since a dataset is a typed object you ideally don't have to think about
field names.

however there are operations on Dataset that require you to provide a
Column, like for example joinWith (and joinWith returns a strongly typed
Dataset, not DataFrame). once you have to provide a Column you are back to
thinking in field names, and worrying about duplicate field names, which is
something that can easily happen in a Dataset without you realizing it.

so under the hood Dataset has unique identifiers for every column, as in
dataset.queryExecution.logical.output, but these are expressions
(attributes) that i cannot turn back into columns since the constructors
for this are private in spark.

so.... how about having Dataset.apply(i: Int): Column to allow me to pick
columns by position without having to worry about (duplicate) field names?
then i could do something like:

dataset.joinWith(otherDataset, dataset(0) === otherDataset(0), joinType)

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