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https://issues.apache.org/jira/browse/FLINK-4207?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15392172#comment-15392172
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ASF GitHub Bot commented on FLINK-4207:
---------------------------------------
Github user aljoscha commented on a diff in the pull request:
https://github.com/apache/flink/pull/2277#discussion_r72092981
--- Diff:
flink-core/src/main/java/org/apache/flink/api/common/state/AppendingState.java
---
@@ -46,8 +46,14 @@
* operator instance. If state partitioning is applied, the value
returned
* depends on the current operator input, as the operator maintains an
* independent state for each partition.
- *
- * @return The operator state value corresponding to the current input.
+ *
+ * <p>
+ * <b>NOTE TO IMPLEMENTERS:</b> if the state is empty, then this
method
+ * should return {@code null}.
+ * </p>
+ *
+ * @return The operator state value corresponding to the current input
or {@code null}
+ * is the state is empty.
--- End diff --
Good idea to include this message!
There's a type, though, should be "if the state is empty" 😉
> WindowOperator becomes very slow with allowed lateness
> ------------------------------------------------------
>
> Key: FLINK-4207
> URL: https://issues.apache.org/jira/browse/FLINK-4207
> Project: Flink
> Issue Type: Bug
> Components: Streaming
> Affects Versions: 1.1.0
> Reporter: Aljoscha Krettek
> Assignee: Kostas Kloudas
> Priority: Blocker
>
> In this simple example the throughput (as measured by the count the window
> emits) becomes very low when an allowed lateness is set:
> {code}
> public class WindowWordCount {
> public static void main(String[] args) throws Exception {
> final StreamExecutionEnvironment env =
> StreamExecutionEnvironment.getExecutionEnvironment();
>
> env.setStreamTimeCharacteristic(TimeCharacteristic.IngestionTime);
> env.setParallelism(1);
> env.addSource(new InfiniteTupleSource(100_000))
> .keyBy(0)
> .timeWindow(Time.seconds(3))
> .allowedLateness(Time.seconds(1))
> .reduce(new ReduceFunction<Tuple2<String,
> Integer>>() {
> @Override
> public Tuple2<String, Integer>
> reduce(Tuple2<String, Integer> value1,
> Tuple2<String, Integer>
> value2) throws Exception {
> return Tuple2.of(value1.f0,
> value1.f1 + value2.f1);
> }
> })
> .filter(new FilterFunction<Tuple2<String,
> Integer>>() {
> private static final long
> serialVersionUID = 1L;
> @Override
> public boolean filter(Tuple2<String,
> Integer> value) throws Exception {
> return
> value.f0.startsWith("Tuple 0");
> }
> })
> .print();
> // execute program
> env.execute("WindowWordCount");
> }
> public static class InfiniteTupleSource implements
> ParallelSourceFunction<Tuple2<String, Integer>> {
> private static final long serialVersionUID = 1L;
> private int numGroups;
> public InfiniteTupleSource(int numGroups) {
> this.numGroups = numGroups;
> }
> @Override
> public void run(SourceContext<Tuple2<String, Integer>> out)
> throws Exception {
> long index = 0;
> while (true) {
> Tuple2<String, Integer> tuple = new
> Tuple2<>("Tuple " + (index % numGroups), 1);
> out.collect(tuple);
> index++;
> }
> }
> @Override
> public void cancel() {
> }
> }
> }
> {code}
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