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https://issues.apache.org/jira/browse/FLINK-8997?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16679798#comment-16679798
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ASF GitHub Bot commented on FLINK-8997:
---------------------------------------
kl0u commented on a change in pull request #7039: [FLINK-8997] Added sliding
window aggregation to datastream test job
URL: https://github.com/apache/flink/pull/7039#discussion_r231897342
##########
File path:
flink-end-to-end-tests/flink-datastream-allround-test/src/main/java/org/apache/flink/streaming/tests/SlidingWindowCheckMapper.java
##########
@@ -0,0 +1,100 @@
+/*
+ * 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.tests;
+
+import org.apache.flink.api.common.functions.RichFlatMapFunction;
+import org.apache.flink.api.common.state.ValueState;
+import org.apache.flink.api.common.state.ValueStateDescriptor;
+import org.apache.flink.api.common.typeinfo.BasicTypeInfo;
+import org.apache.flink.api.common.typeinfo.TypeInformation;
+import org.apache.flink.api.java.tuple.Tuple2;
+import org.apache.flink.api.java.typeutils.ListTypeInfo;
+import org.apache.flink.api.java.typeutils.TupleTypeInfo;
+import org.apache.flink.configuration.Configuration;
+import org.apache.flink.util.Collector;
+
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.List;
+import java.util.Optional;
+import java.util.function.BinaryOperator;
+
+/**
+ * This mapper validates sliding event time window. It checks each event
belongs to appropriate number of consecutive windows.
+ */
+public class SlidingWindowCheckMapper extends
RichFlatMapFunction<Tuple2<Integer, List<Event>>, String> {
+
+ private static final long serialVersionUID = -744070793650644485L;
+
+ /** This value state tracks previously seen events with the number of
windows they appeared in. */
+ private transient ValueState<List<Tuple2<Event, Integer>>>
previousWindow;
+
+ private final int slideFactor;
+
+ SlidingWindowCheckMapper(int slideFactor) {
+ this.slideFactor = slideFactor;
+ }
+
+ @Override
+ public void open(Configuration parameters) throws Exception {
+ ValueStateDescriptor<List<Tuple2<Event, Integer>>>
previousWindowDescriptor =
+ new ValueStateDescriptor<>("previousWindow",
+ new ListTypeInfo<>(new
TupleTypeInfo<>(TypeInformation.of(Event.class), BasicTypeInfo.INT_TYPE_INFO)));
+
+ previousWindow =
getRuntimeContext().getState(previousWindowDescriptor);
+ }
+
+ @Override
+ public void flatMap(Tuple2<Integer, List<Event>> value,
Collector<String> out) throws Exception {
+ List<Tuple2<Event, Integer>> previousWindowValues =
Optional.ofNullable(previousWindow.value()).orElseGet(
+ Collections::emptyList);
+
+ List<Event> newValues = value.f1;
+ newValues.stream().reduce(new BinaryOperator<Event>() {
+ @Override
+ public Event apply(Event event, Event event2) {
+ if (event2.getSequenceNumber() - 1 !=
event.getSequenceNumber()) {
+ out.collect("Alert: events in window
out ouf order!");
+ }
+
+ return event2;
+ }
+ });
+
+ List<Tuple2<Event, Integer>> newWindow = new ArrayList<>();
+ for (Tuple2<Event, Integer> windowValue : previousWindowValues)
{
+ if (!newValues.contains(windowValue.f0)) {
Review comment:
So we assume that we will see the elements at least `slideFactor` times,
right? Shouldn't we also catch the case where we see sth less times? If I
understand the test correctly, then if we see `seqNumber` `x` `N` times, then
all `sequenceNumbers` `y < x` should have also been seen that many times, right?
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> Add sliding window aggregation to the job
> -----------------------------------------
>
> Key: FLINK-8997
> URL: https://issues.apache.org/jira/browse/FLINK-8997
> Project: Flink
> Issue Type: Sub-task
> Components: Tests
> Affects Versions: 1.5.0
> Reporter: Stefan Richter
> Assignee: Dawid Wysakowicz
> Priority: Major
> Labels: pull-request-available
> Fix For: 1.7.0
>
>
> The test job should also test windowing. Sliding windows are probably the
> most demanding form, so this would be a good pick for the test.
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