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 static org.junit.Assert.assertTrue;
  
  import java.io.Serializable;
  import java.util.List;
  import java.util.Map;
  import org.apache.beam.runners.spark.SparkCommonPipelineOptions;
  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.Create;
  import org.apache.beam.sdk.transforms.DoFn;
  import org.apache.beam.sdk.transforms.ParDo;
  import org.apache.beam.sdk.transforms.View;
  import org.apache.beam.sdk.values.KV;
  import org.apache.beam.sdk.values.PCollection;
  import org.apache.beam.sdk.values.PCollectionTuple;
  import org.apache.beam.sdk.values.PCollectionView;
  import org.apache.beam.sdk.values.TupleTag;
  import org.apache.beam.sdk.values.TupleTagList;
  import org.junit.ClassRule;
  import org.junit.Rule;
  import org.junit.Test;
  import org.junit.rules.TestRule;
  import org.junit.runner.RunWith;
  import org.junit.runners.JUnit4;
  
  /** Test class for beam to spark {@link ParDo} translation. */
  @RunWith(JUnit4.class)
  public class ParDoTest implements Serializable {
    @ClassRule public static final SparkSessionRule SESSION = new SparkSessionRule();
  
    @Rule
    public transient TestPipeline pipeline =
        TestPipeline.fromOptions(SESSION.createPipelineOptions());
  
    @Rule public transient TestRule clearCache = SESSION.clearCache();
  
    @Test
    public void testPardo() {
      PCollection<Integer> input =
          pipeline.apply(Create.of(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)).apply(ParDo.of(PLUS_ONE_DOFN));
      PAssert.that(input).containsInAnyOrder(2, 3, 4, 5, 6, 7, 8, 9, 10, 11);
      pipeline.run();
  
      assertTrue("No usage of cache expected", !SESSION.hasCachedData());
    }
  
    @Test
    public void testPardoWithOutputTagsCachedRDD() {
      pardoWithOutputTags("MEMORY_ONLY", true);
      assertTrue("Expected cached data", SESSION.hasCachedData());
    }
  
    @Test
    public void testPardoWithOutputTagsCachedDataset() {
      pardoWithOutputTags("MEMORY_AND_DISK", true);
      assertTrue("Expected cached data", SESSION.hasCachedData());
    }
  
    @Test
    public void testPardoWithUnusedOutputTags() {
      pardoWithOutputTags("MEMORY_AND_DISK", false);
      assertTrue("No usage of cache expected", !SESSION.hasCachedData());
    }
  
    private void pardoWithOutputTags(String storageLevel, boolean evaluateAdditionalOutputs) {
      pipeline.getOptions().as(SparkCommonPipelineOptions.class).setStorageLevel(storageLevel);
  
      TupleTag<Integer> mainTag = new TupleTag<Integer>() {};
      TupleTag<String> additionalUnevenTag = new TupleTag<String>() {};
  
      DoFn<Integer, Integer> doFn =
          new DoFn<Integer, Integer>() {
            @ProcessElement
            public void processElement(@Element Integer i, MultiOutputReceiver out) {
              if (i % 2 == 0) {
                out.get(mainTag).output(i);
              } else {
                out.get(additionalUnevenTag).output(i.toString());
              }
            }
          };
  
      PCollectionTuple outputs =
          pipeline
              .apply(Create.of(1, 2, 3, 4, 5, 6, 7, 8, 9, 10))
              .apply(ParDo.of(doFn).withOutputTags(mainTag, TupleTagList.of(additionalUnevenTag)));
  
      PAssert.that(outputs.get(mainTag)).containsInAnyOrder(2, 4, 6, 8, 10);
      if (evaluateAdditionalOutputs) {
        PAssert.that(outputs.get(additionalUnevenTag)).containsInAnyOrder("1", "3", "5", "7", "9");
      }
      pipeline.run();
    }
  
    @Test
    public void testTwoPardoInRow() {
      PCollection<Integer> input =
          pipeline
              .apply(Create.of(1, 2, 3, 4, 5, 6, 7, 8, 9, 10))
              .apply("Plus 1 (1st)", ParDo.of(PLUS_ONE_DOFN))
              .apply("Plus 1 (2nd)", ParDo.of(PLUS_ONE_DOFN));
      PAssert.that(input).containsInAnyOrder(3, 4, 5, 6, 7, 8, 9, 10, 11, 12);
      pipeline.run();
  
      assertTrue("No usage of cache expected", !SESSION.hasCachedData());
    }
  
    @Test
    public void testSideInputAsList() {
      PCollectionView<List<Integer>> sideInputView =
          pipeline.apply("Create sideInput", Create.of(1, 2, 3)).apply(View.asList());
      PCollection<Integer> input =
          pipeline
              .apply("Create input", Create.of(1, 2, 3, 4, 5, 6, 7, 8, 9, 10))
              .apply(
                  ParDo.of(
                          new DoFn<Integer, Integer>() {
                            @ProcessElement
                            public void processElement(ProcessContext c) {
                              List<Integer> sideInputValue = c.sideInput(sideInputView);
                              if (!sideInputValue.contains(c.element())) {
                                c.output(c.element());
                              }
                            }
                          })
                      .withSideInputs(sideInputView));
      PAssert.that(input).containsInAnyOrder(4, 5, 6, 7, 8, 9, 10);
      pipeline.run();
  
      assertTrue("No usage of cache expected", !SESSION.hasCachedData());
    }
  
    @Test
    public void testSideInputAsSingleton() {
      PCollectionView<Integer> sideInputView =
          pipeline.apply("Create sideInput", Create.of(1)).apply(View.asSingleton());
  
      PCollection<Integer> input =
          pipeline
              .apply("Create input", Create.of(1, 2, 3, 4, 5, 6, 7, 8, 9, 10))
              .apply(
                  ParDo.of(
                          new DoFn<Integer, Integer>() {
                            @ProcessElement
                            public void processElement(ProcessContext c) {
                              Integer sideInputValue = c.sideInput(sideInputView);
                              if (!sideInputValue.equals(c.element())) {
                                c.output(c.element());
                              }
                            }
                          })
                      .withSideInputs(sideInputView));
  
      PAssert.that(input).containsInAnyOrder(2, 3, 4, 5, 6, 7, 8, 9, 10);
      pipeline.run();
  
      assertTrue("No usage of cache expected", !SESSION.hasCachedData());
    }
  
    @Test
    public void testSideInputAsMap() {
      PCollectionView<Map<String, Integer>> sideInputView =
          pipeline
              .apply("Create sideInput", Create.of(KV.of("key1", 1), KV.of("key2", 2)))
              .apply(View.asMap());
      PCollection<Integer> input =
          pipeline
              .apply("Create input", Create.of(1, 2, 3, 4, 5, 6, 7, 8, 9, 10))
              .apply(
                  ParDo.of(
                          new DoFn<Integer, Integer>() {
                            @ProcessElement
                            public void processElement(ProcessContext c) {
                              Map<String, Integer> sideInputValue = c.sideInput(sideInputView);
                              if (!sideInputValue.containsKey("key" + c.element())) {
                                c.output(c.element());
                              }
                            }
                          })
                      .withSideInputs(sideInputView));
      PAssert.that(input).containsInAnyOrder(3, 4, 5, 6, 7, 8, 9, 10);
      pipeline.run();
  
      assertTrue("No usage of cache expected", !SESSION.hasCachedData());
    }
  
    private static final DoFn<Integer, Integer> PLUS_ONE_DOFN =
        new DoFn<Integer, Integer>() {
          @ProcessElement
          public void processElement(ProcessContext c) {
            c.output(c.element() + 1);
          }
        };
  }
  