forked from D-Net/dnet-hadoop
unit test for orcid to result propagation from semrel
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package eu.dnetlib.dhp.orcidtoresultfromsemrel;
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package eu.dnetlib.dhp.orcidtoresultfromsemrel;
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import com.fasterxml.jackson.databind.ObjectMapper;
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import eu.dnetlib.dhp.resulttoorganizationfrominstrepo.Result2OrganizationJobTest;
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import eu.dnetlib.dhp.schema.oaf.Dataset;
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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.JavaRDD;
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import org.apache.spark.api.java.JavaSparkContext;
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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.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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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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public class OrcidPropagationJobTest {
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public class OrcidPropagationJobTest {
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private static final Logger log = LoggerFactory.getLogger(Result2OrganizationJobTest.class);
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private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
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private static final ClassLoader cl = Result2OrganizationJobTest.class.getClassLoader();
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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 beforeAll() throws IOException {
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workingDir = Files.createTempDirectory(OrcidPropagationJobTest.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.setAppName(OrcidPropagationJobTest.class.getSimpleName());
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conf.setMaster("local[*]");
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conf.set("spark.driver.host", "localhost");
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conf.set("hive.metastore.local", "true");
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conf.set("spark.ui.enabled", "false");
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conf.set("spark.sql.warehouse.dir", workingDir.toString());
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conf.set("hive.metastore.warehouse.dir", workingDir.resolve("warehouse").toString());
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spark = SparkSession
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.builder()
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.appName(OrcidPropagationJobTest.class.getSimpleName())
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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 noUpdateTest()throws Exception{
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SparkOrcidToResultFromSemRelJob3.main(new String[]{
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"-isTest", Boolean.TRUE.toString(),
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"-isSparkSessionManaged", Boolean.FALSE.toString(),
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"-sourcePath", getClass().getResource("/eu/dnetlib/dhp/orcidtoresultfromsemrel/sample/noupdate").getPath(),
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"-hive_metastore_uris", "",
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"-saveGraph","true",
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"-resultTableName","eu.dnetlib.dhp.schema.oaf.Dataset",
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"-outputPath",workingDir.toString() + "/dataset",
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"-possibleUpdatesPath", getClass().getResource("/eu/dnetlib/dhp/orcidtoresultfromsemrel/preparedInfo/mergedOrcidAssoc").getPath()
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});
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final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
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JavaRDD<Dataset> tmp = sc.textFile(workingDir.toString()+"/dataset")
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.map(item -> OBJECT_MAPPER.readValue(item, Dataset.class));
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//tmp.map(s -> new Gson().toJson(s)).foreach(s -> System.out.println(s));
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Assertions.assertEquals(10, tmp.count());
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org.apache.spark.sql.Dataset<Dataset> verificationDataset = spark.createDataset(tmp.rdd(), Encoders.bean(Dataset.class));
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verificationDataset.createOrReplaceTempView("dataset");
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String query = "select id " +
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"from dataset " +
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"lateral view explode(author) a as MyT " +
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"lateral view explode(MyT.pid) p as MyP " +
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"where MyP.datainfo.inferenceprovenance = 'propagation'";
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Assertions.assertEquals(0, spark.sql(query).count());
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}
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@Test
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public void oneUpdateTest() throws Exception{
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SparkOrcidToResultFromSemRelJob3.main(new String[]{
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"-isTest", Boolean.TRUE.toString(),
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"-isSparkSessionManaged", Boolean.FALSE.toString(),
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"-sourcePath", getClass().getResource("/eu/dnetlib/dhp/orcidtoresultfromsemrel/sample/oneupdate").getPath(),
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"-hive_metastore_uris", "",
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"-saveGraph","true",
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"-resultTableName","eu.dnetlib.dhp.schema.oaf.Dataset",
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"-outputPath",workingDir.toString() + "/dataset",
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"-possibleUpdatesPath", getClass().getResource("/eu/dnetlib/dhp/orcidtoresultfromsemrel/preparedInfo/mergedOrcidAssoc").getPath()
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});
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final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
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JavaRDD<Dataset> tmp = sc.textFile(workingDir.toString()+"/dataset")
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.map(item -> OBJECT_MAPPER.readValue(item, Dataset.class));
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//tmp.map(s -> new Gson().toJson(s)).foreach(s -> System.out.println(s));
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Assertions.assertEquals(10, tmp.count());
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org.apache.spark.sql.Dataset<Dataset> verificationDataset = spark.createDataset(tmp.rdd(), Encoders.bean(Dataset.class));
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verificationDataset.createOrReplaceTempView("dataset");
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String query = "select id, MyT.name name, MyT.surname surname, MyP.value pid, MyP.qualifier.classid pidType " +
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"from dataset " +
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"lateral view explode(author) a as MyT " +
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"lateral view explode(MyT.pid) p as MyP " +
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"where MyP.datainfo.inferenceprovenance = 'propagation'";
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org.apache.spark.sql.Dataset<Row> propagatedAuthors = spark.sql(query);
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Assertions.assertEquals(1, propagatedAuthors.count());
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Assertions.assertEquals(1, propagatedAuthors.filter("id = '50|dedup_wf_001::95b033c0c3961f6a1cdcd41a99a9632e' " +
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"and name = 'Vajinder' and surname = 'Kumar' and pidType = 'ORCID'").count());
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Assertions.assertEquals(1, propagatedAuthors.filter("pid = '0000-0002-8825-3517'").count());
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}
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@Test
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public void twoUpdatesTest() throws Exception{
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SparkOrcidToResultFromSemRelJob3.main(new String[]{
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"-isTest", Boolean.TRUE.toString(),
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"-isSparkSessionManaged", Boolean.FALSE.toString(),
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"-sourcePath", getClass().getResource("/eu/dnetlib/dhp/orcidtoresultfromsemrel/sample/twoupdates").getPath(),
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"-hive_metastore_uris", "",
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"-saveGraph","true",
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"-resultTableName","eu.dnetlib.dhp.schema.oaf.Dataset",
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"-outputPath",workingDir.toString() + "/dataset",
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"-possibleUpdatesPath", getClass().getResource("/eu/dnetlib/dhp/orcidtoresultfromsemrel/preparedInfo/mergedOrcidAssoc").getPath()
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});
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final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
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JavaRDD<Dataset> tmp = sc.textFile(workingDir.toString()+"/dataset")
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.map(item -> OBJECT_MAPPER.readValue(item, Dataset.class));
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Assertions.assertEquals(10, tmp.count());
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org.apache.spark.sql.Dataset<Dataset> verificationDataset = spark.createDataset(tmp.rdd(), Encoders.bean(Dataset.class));
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verificationDataset.createOrReplaceTempView("dataset");
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String query = "select id, MyT.name name, MyT.surname surname, MyP.value pid, MyP.qualifier.classid pidType " +
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"from dataset " +
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"lateral view explode(author) a as MyT " +
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"lateral view explode(MyT.pid) p as MyP " +
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"where MyP.datainfo.inferenceprovenance = 'propagation'";
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org.apache.spark.sql.Dataset<Row> propagatedAuthors = spark.sql(query);
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Assertions.assertEquals(2, propagatedAuthors.count());
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Assertions.assertEquals(1, propagatedAuthors.filter("name = 'Marc' and surname = 'Schmidtmann'").count());
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Assertions.assertEquals(1, propagatedAuthors.filter("name = 'Ruediger' and surname = 'Beckhaus'").count());
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query = "select id, MyT.name name, MyT.surname surname, MyP.value pid ,MyP.qualifier.classid pidType " +
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"from dataset " +
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"lateral view explode(author) a as MyT " +
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"lateral view explode(MyT.pid) p as MyP ";
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org.apache.spark.sql.Dataset<Row> authorsExplodedPids = spark.sql(query);
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Assertions.assertEquals(2, authorsExplodedPids.filter("name = 'Marc' and surname = 'Schmidtmann'").count());
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Assertions.assertEquals(1, authorsExplodedPids.filter("name = 'Marc' and surname = 'Schmidtmann' and pidType = 'MAG Identifier'").count());
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}
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}
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}
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