package eu.dnetlib.dhp.orcidtoresultfromsemrel; import java.io.IOException; import java.nio.file.Files; import java.nio.file.Path; import org.apache.commons.io.FileUtils; import org.apache.spark.SparkConf; import org.apache.spark.api.java.JavaRDD; import org.apache.spark.api.java.JavaSparkContext; import org.apache.spark.sql.Encoders; import org.apache.spark.sql.Row; import org.apache.spark.sql.SparkSession; import org.junit.jupiter.api.AfterAll; import org.junit.jupiter.api.Assertions; import org.junit.jupiter.api.BeforeAll; import org.junit.jupiter.api.Test; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import com.cloudera.org.codehaus.jackson.map.jsontype.impl.ClassNameIdResolver; import com.fasterxml.jackson.databind.ObjectMapper; import eu.dnetlib.dhp.PropagationConstant; import eu.dnetlib.dhp.schema.common.ModelConstants; import eu.dnetlib.dhp.schema.oaf.Dataset; public class OrcidPropagationJobTest { private static final Logger log = LoggerFactory.getLogger(OrcidPropagationJobTest.class); private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper(); private static SparkSession spark; private static Path workingDir; @BeforeAll public static void beforeAll() throws IOException { workingDir = Files.createTempDirectory(OrcidPropagationJobTest.class.getSimpleName()); log.info("using work dir {}", workingDir); SparkConf conf = new SparkConf(); conf.setAppName(OrcidPropagationJobTest.class.getSimpleName()); conf.setMaster("local[*]"); conf.set("spark.driver.host", "localhost"); conf.set("hive.metastore.local", "true"); conf.set("spark.ui.enabled", "false"); conf.set("spark.sql.warehouse.dir", workingDir.toString()); conf.set("hive.metastore.warehouse.dir", workingDir.resolve("warehouse").toString()); spark = SparkSession .builder() .appName(OrcidPropagationJobTest.class.getSimpleName()) .config(conf) .getOrCreate(); } @AfterAll public static void afterAll() throws IOException { FileUtils.deleteDirectory(workingDir.toFile()); spark.stop(); } @Test public void noUpdateTest() throws Exception { final String sourcePath = getClass() .getResource("/eu/dnetlib/dhp/orcidtoresultfromsemrel/sample/noupdate") .getPath(); final String possibleUpdatesPath = getClass() .getResource( "/eu/dnetlib/dhp/orcidtoresultfromsemrel/preparedInfo/mergedOrcidAssoc") .getPath(); SparkOrcidToResultFromSemRelJob .main( new String[] { "-isTest", Boolean.TRUE.toString(), "-isSparkSessionManaged", Boolean.FALSE.toString(), "-sourcePath", sourcePath, "-hive_metastore_uris", "", "-saveGraph", "true", "-resultTableName", Dataset.class.getCanonicalName(), "-outputPath", workingDir.toString() + "/dataset", "-possibleUpdatesPath", possibleUpdatesPath }); final JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext()); JavaRDD tmp = sc .textFile(workingDir.toString() + "/dataset") .map(item -> OBJECT_MAPPER.readValue(item, Dataset.class)); // tmp.map(s -> new Gson().toJson(s)).foreach(s -> System.out.println(s)); Assertions.assertEquals(10, tmp.count()); org.apache.spark.sql.Dataset verificationDataset = spark .createDataset(tmp.rdd(), Encoders.bean(Dataset.class)); verificationDataset.createOrReplaceTempView("dataset"); String query = "select id " + "from dataset " + "lateral view explode(author) a as MyT " + "lateral view explode(MyT.pid) p as MyP " + "where MyP.datainfo.inferenceprovenance = 'propagation'"; Assertions.assertEquals(0, spark.sql(query).count()); } @Test public void oneUpdateTest() throws Exception { SparkOrcidToResultFromSemRelJob .main( new String[] { "-isTest", Boolean.TRUE.toString(), "-isSparkSessionManaged", Boolean.FALSE.toString(), "-sourcePath", getClass() .getResource("/eu/dnetlib/dhp/orcidtoresultfromsemrel/sample/oneupdate") .getPath(), "-hive_metastore_uris", "", "-saveGraph", "true", "-resultTableName", "eu.dnetlib.dhp.schema.oaf.Dataset", "-outputPath", workingDir.toString() + "/dataset", "-possibleUpdatesPath", getClass() .getResource( "/eu/dnetlib/dhp/orcidtoresultfromsemrel/preparedInfo/mergedOrcidAssoc") .getPath() }); final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext()); JavaRDD tmp = sc .textFile(workingDir.toString() + "/dataset") .map(item -> OBJECT_MAPPER.readValue(item, Dataset.class)); // tmp.map(s -> new Gson().toJson(s)).foreach(s -> System.out.println(s)); Assertions.assertEquals(10, tmp.count()); org.apache.spark.sql.Dataset verificationDataset = spark .createDataset(tmp.rdd(), Encoders.bean(Dataset.class)); verificationDataset.createOrReplaceTempView("dataset"); String query = "select id, MyT.name name, MyT.surname surname, MyP.value pid, MyP.qualifier.classid pidType " + "from dataset " + "lateral view explode(author) a as MyT " + "lateral view explode(MyT.pid) p as MyP " + "where MyP.datainfo.inferenceprovenance = 'propagation'"; org.apache.spark.sql.Dataset propagatedAuthors = spark.sql(query); Assertions.assertEquals(1, propagatedAuthors.count()); Assertions .assertEquals( 1, propagatedAuthors .filter( "id = '50|dedup_wf_001::95b033c0c3961f6a1cdcd41a99a9632e' " + "and name = 'Vajinder' and surname = 'Kumar' and pidType = '" + ModelConstants.ORCID_PENDING + "'") .count()); Assertions.assertEquals(1, propagatedAuthors.filter("pid = '0000-0002-8825-3517'").count()); } @Test public void twoUpdatesTest() throws Exception { SparkOrcidToResultFromSemRelJob .main( new String[] { "-isTest", Boolean.TRUE.toString(), "-isSparkSessionManaged", Boolean.FALSE.toString(), "-sourcePath", getClass() .getResource( "/eu/dnetlib/dhp/orcidtoresultfromsemrel/sample/twoupdates") .getPath(), "-hive_metastore_uris", "", "-saveGraph", "true", "-resultTableName", "eu.dnetlib.dhp.schema.oaf.Dataset", "-outputPath", workingDir.toString() + "/dataset", "-possibleUpdatesPath", getClass() .getResource( "/eu/dnetlib/dhp/orcidtoresultfromsemrel/preparedInfo/mergedOrcidAssoc") .getPath() }); final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext()); JavaRDD tmp = sc .textFile(workingDir.toString() + "/dataset") .map(item -> OBJECT_MAPPER.readValue(item, Dataset.class)); Assertions.assertEquals(10, tmp.count()); org.apache.spark.sql.Dataset verificationDataset = spark .createDataset(tmp.rdd(), Encoders.bean(Dataset.class)); verificationDataset.createOrReplaceTempView("dataset"); String query = "select id, MyT.name name, MyT.surname surname, MyP.value pid, MyP.qualifier.classid pidType " + "from dataset " + "lateral view explode(author) a as MyT " + "lateral view explode(MyT.pid) p as MyP " + "where MyP.datainfo.inferenceprovenance = 'propagation'"; org.apache.spark.sql.Dataset propagatedAuthors = spark.sql(query); Assertions.assertEquals(2, propagatedAuthors.count()); Assertions .assertEquals( 1, propagatedAuthors.filter("name = 'Marc' and surname = 'Schmidtmann'").count()); Assertions .assertEquals( 1, propagatedAuthors.filter("name = 'Ruediger' and surname = 'Beckhaus'").count()); query = "select id, MyT.name name, MyT.surname surname, MyP.value pid ,MyP.qualifier.classid pidType " + "from dataset " + "lateral view explode(author) a as MyT " + "lateral view explode(MyT.pid) p as MyP "; org.apache.spark.sql.Dataset authorsExplodedPids = spark.sql(query); Assertions .assertEquals( 2, authorsExplodedPids.filter("name = 'Marc' and surname = 'Schmidtmann'").count()); Assertions .assertEquals( 1, authorsExplodedPids .filter( "name = 'Marc' and surname = 'Schmidtmann' and pidType = 'MAG Identifier'") .count()); } }