content: /*
   * 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.beam.runners.spark.structuredstreaming.translation.batch;
  
  import java.io.Serializable;
  import java.util.ArrayList;
  import java.util.List;
  import org.apache.beam.runners.spark.structuredstreaming.SparkSessionRule;
  import org.apache.beam.sdk.testing.PAssert;
  import org.apache.beam.sdk.testing.TestPipeline;
  import org.apache.beam.sdk.transforms.CombineFnBase;
  import org.apache.beam.sdk.transforms.Count;
  import org.apache.beam.sdk.transforms.Create;
  import org.apache.beam.sdk.transforms.Distinct;
  import org.apache.beam.sdk.transforms.Sum;
  import org.apache.beam.sdk.transforms.windowing.FixedWindows;
  import org.apache.beam.sdk.transforms.windowing.Sessions;
  import org.apache.beam.sdk.transforms.windowing.SlidingWindows;
  import org.apache.beam.sdk.transforms.windowing.Window;
  import org.apache.beam.sdk.values.KV;
  import org.apache.beam.sdk.values.PCollection;
  import org.apache.beam.sdk.values.TimestampedValue;
  import org.apache.beam.vendor.guava.v32_1_2_jre.com.google.common.collect.Lists;
  import org.joda.time.Duration;
  import org.joda.time.Instant;
  import org.junit.ClassRule;
  import org.junit.Rule;
  import org.junit.Test;
  import org.junit.runner.RunWith;
  import org.junit.runners.JUnit4;
  
  /**
   * Test class for beam to spark {@link
   * org.apache.beam.sdk.transforms.Combine#perKey(CombineFnBase.GlobalCombineFn)} translation.
   */
  @RunWith(JUnit4.class)
  public class CombinePerKeyTest implements Serializable {
    @ClassRule public static final SparkSessionRule SESSION = new SparkSessionRule();
  
    @Rule
    public transient TestPipeline pipeline =
        TestPipeline.fromOptions(SESSION.createPipelineOptions());
  
    @Test
    public void testCombinePerKey() {
      List<KV<Integer, Integer>> elems = new ArrayList<>();
      elems.add(KV.of(1, 1));
      elems.add(KV.of(1, 3));
      elems.add(KV.of(1, 5));
      elems.add(KV.of(2, 2));
      elems.add(KV.of(2, 4));
      elems.add(KV.of(2, 6));
  
      PCollection<KV<Integer, Integer>> input =
          pipeline.apply(Create.of(elems)).apply(Sum.integersPerKey());
      PAssert.that(input).containsInAnyOrder(KV.of(1, 9), KV.of(2, 12));
      pipeline.run();
    }
  
    @Test
    public void testDistinctViaCombinePerKey() {
      List<Integer> elems = Lists.newArrayList(1, 2, 3, 3, 4, 4, 4, 4, 5, 5);
  
      // Distinct is implemented in terms of CombinePerKey
      PCollection<Integer> result = pipeline.apply(Create.of(elems)).apply(Distinct.create());
  
      PAssert.that(result).containsInAnyOrder(1, 2, 3, 4, 5);
      pipeline.run();
    }
  
    @Test
    public void testCombinePerKeyPreservesWindowing() {
      PCollection<KV<Integer, Integer>> input =
          pipeline
              .apply(
                  Create.timestamped(
                      TimestampedValue.of(KV.of(1, 1), new Instant(1)),
                      TimestampedValue.of(KV.of(1, 3), new Instant(2)),
                      TimestampedValue.of(KV.of(1, 5), new Instant(11)),
                      TimestampedValue.of(KV.of(2, 2), new Instant(3)),
                      TimestampedValue.of(KV.of(2, 4), new Instant(11)),
                      TimestampedValue.of(KV.of(2, 6), new Instant(12))))
              .apply(Window.into(FixedWindows.of(Duration.millis(10))))
              .apply(Sum.integersPerKey());
      PAssert.that(input).containsInAnyOrder(KV.of(1, 4), KV.of(1, 5), KV.of(2, 2), KV.of(2, 10));
      pipeline.run();
    }
  
    @Test
    public void testCombinePerKeyWithSlidingWindows() {
      PCollection<KV<Integer, Integer>> input =
          pipeline
              .apply(
                  Create.timestamped(
                      TimestampedValue.of(KV.of(1, 1), new Instant(1)),
                      TimestampedValue.of(KV.of(1, 3), new Instant(2)),
                      TimestampedValue.of(KV.of(1, 5), new Instant(3)),
                      TimestampedValue.of(KV.of(1, 2), new Instant(1)),
                      TimestampedValue.of(KV.of(1, 4), new Instant(2)),
                      TimestampedValue.of(KV.of(1, 6), new Instant(3))))
              .apply(Window.into(SlidingWindows.of(Duration.millis(3)).every(Duration.millis(1))))
              .apply(Sum.integersPerKey());
      PAssert.that(input)
          .containsInAnyOrder(
              KV.of(1, 1 + 2),
              KV.of(1, 1 + 2 + 3 + 4),
              KV.of(1, 1 + 3 + 5 + 2 + 4 + 6),
              KV.of(1, 3 + 4 + 5 + 6),
              KV.of(1, 5 + 6));
      pipeline.run();
    }
  
    @Test
    public void testCombineByKeyWithMergingWindows() {
      PCollection<KV<Integer, Integer>> input =
          pipeline
              .apply(
                  Create.timestamped(
                      TimestampedValue.of(KV.of(1, 1), new Instant(5)),
                      TimestampedValue.of(KV.of(1, 3), new Instant(7)),
                      TimestampedValue.of(KV.of(1, 5), new Instant(11)),
                      TimestampedValue.of(KV.of(2, 2), new Instant(5)),
                      TimestampedValue.of(KV.of(2, 4), new Instant(11)),
                      TimestampedValue.of(KV.of(2, 6), new Instant(12))))
              .apply(Window.into(Sessions.withGapDuration(Duration.millis(5))))
              .apply(Sum.integersPerKey());
  
      PAssert.that(input)
          .containsInAnyOrder(
              KV.of(1, 9), // window [5-16)
              KV.of(2, 2), // window [5-10)
              KV.of(2, 10) // window [11-17)
              );
      pipeline.run();
    }
  
    @Test
    public void testCountPerElementWithSlidingWindows() {
      PCollection<String> input =
          pipeline
              .apply(
                  Create.timestamped(
                      TimestampedValue.of("a", new Instant(1)),
                      TimestampedValue.of("a", new Instant(2)),
                      TimestampedValue.of("b", new Instant(3)),
                      TimestampedValue.of("b", new Instant(4))))
              .apply(Window.into(SlidingWindows.of(Duration.millis(2)).every(Duration.millis(1))));
      PCollection<KV<String, Long>> output = input.apply(Count.perElement());
      PAssert.that(output)
          .containsInAnyOrder(
              KV.of("a", 1L),
              KV.of("a", 2L),
              KV.of("a", 1L),
              KV.of("b", 1L),
              KV.of("b", 2L),
              KV.of("b", 1L));
      pipeline.run();
    }
  }
  