jiexray commented on code in PR #25996:
URL: https://github.com/apache/flink/pull/25996#discussion_r1920130658
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flink-examples/flink-examples-streaming/src/main/java/org/apache/flink/streaming/examples/windowing/WindowWordCount.java:
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@@ -118,15 +129,33 @@ public static void main(String[] args) throws Exception {
// Using a keyBy allows performing aggregations and
other
// stateful transformations over data on a per-key
basis.
// This is similar to a GROUP BY clause in a SQL query.
- .keyBy(value -> value.f0)
- // create windows of windowSize records slided every
slideSize records
- .countWindow(windowSize, slideSize)
- // For each key, we perform a simple sum of the "1"
field, the count.
- // If the input data set is bounded, sum will output a
final count for
- // each word. If it is unbounded, it will continuously
output updates
- // each time it sees a new instance of each word in
the stream.
- .sum(1)
- .name("counter");
+ .keyBy(value -> value.f0);
+
+ DataStream<Tuple2<String, Integer>> counts;
+ if (params.isAsyncState()) {
+ counts =
+ keyedStream
+ .enableAsyncState()
+ // create windows of windowSize records slided
every slideSize records
+ .asyncCountWindow(windowSize, slideSize)
Review Comment:
Resolved, I have removed this API. countWindow() + enableAsyncState() will
trigger DataStream using AsyncWindowOperator.
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