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* Licensed to the Apache Software Foundation (ASF) under one
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* 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,
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package org.apache.beam.runners.spark;
import static org.junit.Assert.assertEquals;
import org.apache.beam.runners.spark.translation.EvaluationContext;
import org.apache.beam.runners.spark.translation.SparkContextFactory;
import org.apache.beam.runners.spark.translation.TransformTranslator;
import org.apache.beam.sdk.Pipeline;
import org.apache.beam.sdk.options.PipelineOptionsFactory;
import org.apache.beam.sdk.transforms.Count;
import org.apache.beam.sdk.transforms.Create;
import org.apache.beam.sdk.values.PCollection;
import org.apache.spark.api.java.JavaSparkContext;
import org.junit.Test;
/**
* This test checks how the cache candidates map is populated by the runner when evaluating the
* pipeline.
*/
public class CacheTest {
@Test
public void cacheCandidatesUpdaterTest() throws Exception {
SparkPipelineOptions options =
PipelineOptionsFactory.create().as(TestSparkPipelineOptions.class);
options.setRunner(TestSparkRunner.class);
Pipeline pipeline = Pipeline.create(options);
PCollection<String> pCollection = pipeline.apply(Create.of("foo", "bar"));
// first read
pCollection.apply(Count.<String>globally());
// second read
// as we access the same PCollection two times, the Spark runner does optimization and so
// will cache the RDD representing this PCollection
pCollection.apply(Count.<String>globally());
JavaSparkContext jsc = SparkContextFactory.getSparkContext(options);
EvaluationContext ctxt = new EvaluationContext(jsc, pipeline, options);
SparkRunner.CacheVisitor cacheVisitor =
new SparkRunner.CacheVisitor(new TransformTranslator.Translator(), ctxt);
pipeline.traverseTopologically(cacheVisitor);
assertEquals(2L, (long) ctxt.getCacheCandidates().get(pCollection));
}
}