[英]How can I use an implicit function with two parameters (Scala)?
I've tried this two options:我试过这两个选项:
object DSChecker {
implicit def checkImplFunction(dataset: Dataset[Row], config:Config): Checker = new Checker (dataset, config)
}
and和
object DSChecker {
implicit def checkImplFunction(dataset: Dataset[Row])(implicit config:Config): Checker = new Checker (dataset, config)
}
They compile, but the problem is when I need two use them.他们编译,但问题是当我需要两个使用它们时。
I've tried also multiple combinations, but they don't compile... (evalDifferences is a "normal" function inside clas Checker)我也尝试了多种组合,但它们无法编译......(evalDifferences 是 clas Checker 中的“正常” function)
//Whithout implicit args in implicit function
import DSChecker._
(df1, difConfig).evalDifferences(df2)
or或者
// With config as implicit arg in implicit funciton
import DSChecker._
df1.evalDifferences(df2)
The problem is always the same... the compilator doesn't find "evalDifferences" method.问题总是一样的......编译器找不到“evalDifferences”方法。
Can someone help me?有人能帮我吗?
Try with Tuple
:尝试使用Tuple
:
object DSChecker {
implicit def checkImplFunction(data: (Dataset[Row], Config)): Checker = new Checker (data._1, data._2)
}
Then, this should work:然后,这应该工作:
//Whithout implicit args in implicit function
import DSChecker._
(df1, difConfig).evalDifferences(df2)
In your case, I think extension method fits better:在您的情况下,我认为扩展方法更适合:
object DSChecker {
implicit class DfExtension(df: Dataframe) {
def checker(implicit config: Config) = {
new Checker(df, config)
}
}
}
df1.checker.evalDifferences(df2)
You can also expose evalDifferences
directly as extension method.您还可以将evalDifferences
直接公开为扩展方法。
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