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# Scala Extensions and Partial Functions
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Scala-specific extensions that enable partial function support for more idiomatic Scala programming with automatic conversion between partial and total functions.
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## Extension Import
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```scala
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import org.apache.flink.streaming.api.scala.extensions._
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```
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## Partial Function Support
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```scala { .api }
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class OnDataStream[T] {
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  def mapWith[R: TypeInformation](fun: PartialFunction[T, R]): DataStream[R]
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  def flatMapWith[R: TypeInformation](fun: PartialFunction[T, TraversableOnce[R]]): DataStream[R]
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  def filterWith(fun: PartialFunction[T, Boolean]): DataStream[T]
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  def keyingBy[K: TypeInformation](fun: PartialFunction[T, K]): KeyedStream[T, K]
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}
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class OnKeyedStream[T, K] {
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  def mapWith[R: TypeInformation](fun: PartialFunction[T, R]): DataStream[R]
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  def flatMapWith[R: TypeInformation](fun: PartialFunction[T, TraversableOnce[R]]): DataStream[R]
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  def filterWith(fun: PartialFunction[T, Boolean]): DataStream[T]
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  def reduceWith(fun: PartialFunction[(T, T), T]): DataStream[T]
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}
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```
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## Usage Examples
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```scala
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import org.apache.flink.streaming.api.scala._
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import org.apache.flink.streaming.api.scala.extensions._
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val env = StreamExecutionEnvironment.getExecutionEnvironment
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val events = env.fromElements("start", "data", "end", "error")
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// Partial function mapping
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val mapped = events.mapWith {
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  case "start" => "BEGIN"
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  case "end" => "FINISH"
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  case data => s"PROCESS: $data"
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}
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// Partial function filtering
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val filtered = events.filterWith {
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  case "error" => false
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  case _ => true
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}
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```
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Scala extensions provide idiomatic Scala programming patterns while maintaining Flink's type safety and performance characteristics.