Github user tillrohrmann commented on a diff in the pull request:
https://github.com/apache/flink/pull/1704#discussion_r55993625
--- Diff:
flink-scala/src/main/scala/org/apache/flink/api/scala/extensions/acceptPartialFunctions/OnDataSet.scala
---
@@ -0,0 +1,104 @@
+/*
+ * 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.api.scala.extensions.acceptPartialFunctions
+
+import org.apache.flink.api.common.typeinfo.TypeInformation
+import org.apache.flink.api.scala.{GroupedDataSet, DataSet}
+
+import scala.reflect.ClassTag
+
+class OnDataSet[T: TypeInformation](ds: DataSet[T]) {
+
+ /**
+ * Applies a function `fun` to each item of the data set
+ *
+ * @param fun The function to be applied to each item
+ * @tparam R The type of the items in the returned data set
+ * @return A dataset of R
+ */
+ def mapWith[R: TypeInformation: ClassTag](fun: T => R): DataSet[R] =
+ ds.map(fun)
+
+ /**
+ * Applies a function `fun` to a partition as a whole
+ *
+ * @param fun The function to be applied on the whole partition
+ * @tparam R The type of the items in the returned data set
+ * @return A dataset of R
+ */
+ def mapPartitionWith[R: TypeInformation: ClassTag](fun: Seq[T] => R):
DataSet[R] =
+ ds.mapPartition {
+ (it, out) =>
+ out.collect(fun(it.to[Seq]))
+ }
+
+ /**
+ * Applies a function `fun` to each item of the dataset, producing a
collection of items
+ * that will be flattened in the resulting data set
+ *
+ * @param fun The function to be applied to each item
+ * @tparam R The type of the items in the returned data set
+ * @return A dataset of R
+ */
+ def flatMapWith[R: TypeInformation: ClassTag](fun: T =>
TraversableOnce[R]): DataSet[R] =
+ ds.flatMap(fun)
+
+ /**
+ * Applies a predicate `fun` to each item of the data set, 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): DataSet[T] =
+ ds.filter(fun)
+
+ /**
+ * Applies a reducer `fun` to the data set
+ *
+ * @param fun The reducing function to be applied on the whole data set
+ * @tparam R The type of the items in the returned collection
+ * @return A data set of Rs
+ */
+ def reduceWith[R: TypeInformation](fun: (T, T) => T): DataSet[T] =
+ ds.reduce(fun)
+
+ /**
+ * Applies a reducer `fun` to a grouped data set
+ *
+ * @param fun The function to be applied to the whole grouping
+ * @tparam R The type of the items in the returned data set
+ * @return A dataset of Rs
+ */
+ def reduceGroupWith[R: TypeInformation: ClassTag](fun: Seq[T] => R):
DataSet[R] =
+ ds.reduceGroup {
+ (it, out) =>
+ out.collect(fun(it.to[Seq]))
--- End diff --
Same question here with the materialization of the iterator.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
