forked from D-Net/dnet-hadoop
114 lines
3.3 KiB
Java
114 lines
3.3 KiB
Java
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package eu.dnetlib.dhp.oa.provision;
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import java.io.IOException;
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import java.nio.file.Files;
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import java.nio.file.Path;
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import java.util.List;
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import org.apache.commons.io.FileUtils;
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import org.apache.spark.SparkConf;
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import org.apache.spark.api.java.function.FilterFunction;
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import org.apache.spark.sql.Dataset;
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import org.apache.spark.sql.Encoders;
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import org.apache.spark.sql.Row;
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import org.apache.spark.sql.SparkSession;
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import org.junit.jupiter.api.AfterAll;
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import org.junit.jupiter.api.Assertions;
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import org.junit.jupiter.api.BeforeAll;
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import org.junit.jupiter.api.Test;
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import org.junit.jupiter.api.io.TempDir;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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import eu.dnetlib.dhp.oa.provision.model.ProvisionModelSupport;
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import eu.dnetlib.dhp.schema.oaf.Relation;
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public class PrepareRelationsJobTest {
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private static final Logger log = LoggerFactory.getLogger(PrepareRelationsJobTest.class);
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public static final String SUBRELTYPE = "subRelType";
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public static final String OUTCOME = "outcome";
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public static final String PARTICIPATION = "participation";
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public static final String AFFILIATION = "affiliation";
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private static SparkSession spark;
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private static Path workingDir;
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@BeforeAll
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public static void setUp() throws IOException {
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workingDir = Files.createTempDirectory(PrepareRelationsJobTest.class.getSimpleName());
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log.info("using work dir {}", workingDir);
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SparkConf conf = new SparkConf();
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conf.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer");
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conf.registerKryoClasses(ProvisionModelSupport.getModelClasses());
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spark = SparkSession
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.builder()
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.appName(PrepareRelationsJobTest.class.getSimpleName())
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.master("local[*]")
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.config(conf)
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.getOrCreate();
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}
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@AfterAll
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public static void afterAll() throws IOException {
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FileUtils.deleteDirectory(workingDir.toFile());
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spark.stop();
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}
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@Test
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public void testRunPrepareRelationsJob(@TempDir Path testPath) throws Exception {
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final int maxRelations = 20;
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PrepareRelationsJob
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.main(
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new String[] {
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"-isSparkSessionManaged", Boolean.FALSE.toString(),
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"-inputRelationsPath", getClass().getResource("relations.gz").getPath(),
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"-outputPath", testPath.toString(),
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"-relPartitions", "10",
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"-relationFilter", "asd",
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"-sourceMaxRelations", String.valueOf(maxRelations),
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"-targetMaxRelations", String.valueOf(maxRelations * 100)
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});
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Dataset<Relation> out = spark
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.read()
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.parquet(testPath.toString())
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.as(Encoders.bean(Relation.class))
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.cache();
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Assertions.assertEquals(maxRelations, out.count());
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Dataset<Row> freq = out
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.toDF()
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.cube(SUBRELTYPE)
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.count()
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.filter((FilterFunction<Row>) value -> !value.isNullAt(0));
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log.info(freq.collectAsList().toString());
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long outcome = getRows(freq, OUTCOME).get(0).getAs("count");
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long participation = getRows(freq, PARTICIPATION).get(0).getAs("count");
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long affiliation = getRows(freq, AFFILIATION).get(0).getAs("count");
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Assertions.assertTrue(participation == outcome);
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Assertions.assertTrue(outcome > affiliation);
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Assertions.assertTrue(participation > affiliation);
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Assertions.assertEquals(7, outcome);
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Assertions.assertEquals(7, participation);
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Assertions.assertEquals(6, affiliation);
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}
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protected List<Row> getRows(Dataset<Row> freq, String col) {
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return freq.filter(freq.col(SUBRELTYPE).equalTo(col)).collectAsList();
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}
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}
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