zhipeng93 commented on code in PR #90:
URL: https://github.com/apache/flink-ml/pull/90#discussion_r860683058
##########
flink-ml-core/src/main/java/org/apache/flink/ml/common/datastream/DataStreamUtils.java:
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@@ -67,6 +72,28 @@ public static <IN, OUT> DataStream<OUT> mapPartition(
.setParallelism(input.getParallelism());
}
+ /**
+ * Applies a {@link ReduceFunction} on a bounded data stream. The output
stream contains at most
+ * one stream record and its parallelism is one.
+ *
+ * @param input The input data stream.
+ * @param func The user defined reduce function.
+ * @param <T> The class type of the input.
+ * @return The result data stream.
+ */
+ public static <T> DataStream<T> reduce(DataStream<T> input,
ReduceFunction<T> func) {
+ DataStream<T> partialReducedStream =
+ input.transform("partialReduce", input.getType(), new
ReduceOperator<>(func))
+ .setParallelism(input.getParallelism());
Review Comment:
Yeah, you are right and it is not chained. But from the job graph, I could
see that the edge is already `FORWARD` and there is no network shuffle.
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