Github user tillrohrmann commented on a diff in the pull request:
https://github.com/apache/flink/pull/1704#discussion_r53947144
--- Diff:
flink-streaming-scala/src/main/scala/org/apache/flink/streaming/api/scala/extensions/acceptPartialFunctions/package.scala
---
@@ -0,0 +1,133 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.flink.streaming.api.scala.extensions
+
+import org.apache.flink.api.common.typeinfo.TypeInformation
+import org.apache.flink.streaming.api.scala.{JoinedStreams,
CoGroupedStreams, KeyedStream, DataStream}
+import org.apache.flink.streaming.api.windowing.windows.Window
+
+import scala.reflect.ClassTag
+
+/**
+ * acceptPartialFunctions extends the original DataStream with methods
with unique names
+ * that delegate to core higher-order functions (e.g. `map`) so that we
can work around
+ * the fact that overloaded methods taking functions as parameters can't
accept partial
+ * functions as well. This enables the possibility to directly apply
pattern matching
+ * to decompose inputs such as tuples, case classes and collections.
+ *
+ * e.g.
+ * {{{
+ * object Main {
+ * import org.apache.flink.api.scala.extensions._
+ * case class Point(x: Double, y: Double)
+ * def main(args: Array[String]): Unit = {
+ * val env = StreamExecutionEnvironment.getExecutionEnvironment
+ * val ds = env.fromElements(Point(1, 2), Point(3, 4), Point(5, 6))
+ * ds.filterWith {
+ * case Point(x, _) => x > 1
+ * }.reduceWith {
+ * case (Point(x1, y1), (Point(x2, y2))) => Point(x1 + y1, x2 +
y2)
+ * }.mapWith {
+ * case Point(x, y) => (x, y)
+ * }.flatMapWith {
+ * case (x, y) => Seq('x' -> x, 'y' -> y)
+ * }.groupingBy {
+ * case (id, value) => id
+ * }
+ * }
+ * }
+ * }}}
+ *
+ */
+package object acceptPartialFunctions {
+
+ implicit class OnDataStream[T: TypeInformation](stream: DataStream[T]) {
+
+ /**
+ * Applies a function `fun` to each item of the stream
+ *
+ * @param fun The function to be applied to each item
+ * @tparam R The type of the items in the returned stream
+ * @return A dataset of R
+ */
+ def mapWith[R: TypeInformation: ClassTag](fun: T => R): DataStream[R] =
+ stream.map(fun)
+
+ /**
+ * Applies a function `fun` to each item of the stream, producing a
collection of items
+ * that will be flattened in the resulting stream
+ *
+ * @param fun The function to be applied to each item
+ * @tparam R The type of the items in the returned stream
+ * @return A dataset of R
+ */
+ def flatMapWith[R: TypeInformation: ClassTag](fun: T =>
TraversableOnce[R]): DataStream[R] =
+ stream.flatMap(fun)
+
+ /**
+ * Applies a predicate `fun` to each item of the stream, keeping only
those for which
+ * the predicate holds
+ *
+ * @param fun The predicate to be tested on each item
+ * @return A dataset of R
+ */
+ def filterWith(fun: T => Boolean): DataStream[T] =
+ stream.filter(fun)
+
+ /**
+ * Keys the items according to a keying function `fun`
+ *
+ * @param fun The keying function
+ * @tparam K The type of the key, for which type information must be
known
+ * @return A stream of Ts keyed by Ks
+ */
+ def keyingBy[K: TypeInformation: ClassTag](fun: T => K):
KeyedStream[T, K] =
+ stream.keyBy(fun)
+
+ }
+
+ implicit class OnKeyedStream[T: TypeInformation, K](stream:
KeyedStream[T, K]) {
--- End diff --
What is with the `fold` operation?
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