282 lines
9.6 KiB
Java
282 lines
9.6 KiB
Java
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package eu.dnetlib.dhp.oa.graph.dump.skgif;
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import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
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import java.io.Serializable;
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import java.util.*;
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import java.util.stream.Collectors;
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import org.apache.commons.io.IOUtils;
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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.api.java.function.FlatMapFunction;
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import org.apache.spark.api.java.function.MapFunction;
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import org.apache.spark.api.java.function.MapGroupsFunction;
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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.SaveMode;
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import org.apache.spark.sql.SparkSession;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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import eu.dnetlib.dhp.application.ArgumentApplicationParser;
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import eu.dnetlib.dhp.oa.graph.dump.skgif.beans.EmitPerManifestation;
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import eu.dnetlib.dhp.schema.common.EntityType;
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import eu.dnetlib.dhp.schema.common.ModelSupport;
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import eu.dnetlib.dhp.schema.oaf.*;
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import eu.dnetlib.dhp.schema.oaf.Datasource;
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import eu.dnetlib.dhp.skgif.model.*;
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import eu.dnetlib.dhp.utils.DHPUtils;
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import scala.Tuple2;
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/**
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* @author miriam.baglioni
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* @Date 06/02/24
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*/
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public class EmitFromResults implements Serializable {
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private static final Logger log = LoggerFactory.getLogger(EmitFromResults.class);
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public static void main(String[] args) throws Exception {
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String jsonConfiguration = IOUtils
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.toString(
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EmitFromResults.class
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.getResourceAsStream(
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"/eu/dnetlib/dhp/oa/graph/dump/emit_biblio_parameters.json"));
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final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration);
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parser.parseArgument(args);
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Boolean isSparkSessionManaged = Optional
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.ofNullable(parser.get("isSparkSessionManaged"))
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.map(Boolean::valueOf)
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.orElse(Boolean.TRUE);
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log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
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final String inputPath = parser.get("sourcePath");
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log.info("inputPath: {}", inputPath);
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final String outputPath = parser.get("outputPath");
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log.info("outputPath: {}", outputPath);
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final String workingDir = parser.get("workingDir");
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log.info("workingDir: {}", workingDir);
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SparkConf conf = new SparkConf();
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runWithSparkSession(
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conf,
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isSparkSessionManaged,
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spark -> {
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Utils.removeOutputDir(spark, outputPath);
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emitFromResult(spark, inputPath, outputPath, workingDir);
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});
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}
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//per ogni result emetto id + journal se esiste + istanza + hosted by dell'istanza
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public static <R extends Result> void emitFromResult(SparkSession spark, String inputPath, String outputPath,
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String workingDir) {
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emitManifestation(spark, inputPath, workingDir);
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emitPerson(spark, inputPath, outputPath, workingDir);
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emitTopic(spark, inputPath, outputPath, workingDir);
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}
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private static <R extends Result> void emitTopic(SparkSession spark, String inputPath, String outputPath,
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String workingDir) {
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ModelSupport.entityTypes.keySet().forEach(e -> {
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if (ModelSupport.isResult(e)) {
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Class<R> resultClazz = ModelSupport.entityTypes.get(e);
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Utils
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.readPath(spark, inputPath + e.name(), resultClazz)
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.filter((FilterFunction<R>) r -> Optional.ofNullable(r.getSubject()).isPresent())
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.flatMap(
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(FlatMapFunction<R, Topic>) r -> r
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.getSubject()
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.stream()
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.filter(
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s -> s.getQualifier().getClassid().equalsIgnoreCase("fos")
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|| s.getQualifier().getClassid().equalsIgnoreCase("sdg"))
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.map(s -> {
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Topic t = new Topic();
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t
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.setLocal_identifier(
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Utils
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.getIdentifier(
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Prefixes.TOPIC, s.getQualifier().getClassid() + s.getValue()));
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t
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.setIdentifiers(
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Arrays
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.asList(
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Identifier.newInstance(s.getQualifier().getClassid(), s.getValue())));
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t.setName(s.getValue());
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return t;
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})
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.collect(Collectors.toList())
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.iterator(),
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Encoders.bean(Topic.class))
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.write()
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.mode(SaveMode.Overwrite)
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.option("compression", "gzip")
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.json(workingDir + e.name() + "/topic");
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}
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});
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Dataset<Topic> topics = spark.emptyDataset(Encoders.bean(Topic.class));
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for (EntityType entityType : ModelSupport.entityTypes.keySet()) {
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if (ModelSupport.isResult(entityType))
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topics = topics.union(Utils.readPath(spark, workingDir + entityType.name() + "/topic", Topic.class));
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}
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topics
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.groupByKey((MapFunction<Topic, String>) p -> p.getLocal_identifier(), Encoders.STRING())
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.mapGroups((MapGroupsFunction<String, Topic, Topic>) (k, v) -> v.next(), Encoders.bean(Topic.class))
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.write()
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.mode(SaveMode.Overwrite)
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.option("compression", "gzip")
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.json(outputPath + "/Topic");
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}
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private static <R extends Result> void emitPerson(SparkSession spark, String inputPath, String outputPath,
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String workingDir) {
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ModelSupport.entityTypes.keySet().forEach(e -> {
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if (ModelSupport.isResult(e)) {
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Class<R> resultClazz = ModelSupport.entityTypes.get(e);
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Utils
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.readPath(spark, inputPath + e.name(), resultClazz)
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.flatMap((FlatMapFunction<R, Persons>) r -> {
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List<Persons> authors = new ArrayList<>();
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if (Optional.ofNullable(r.getAuthor()).isPresent() && r.getAuthor().size() > 0) {
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int count = 0;
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for (Author a : r.getAuthor()) {
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count += 1;
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Persons p = new Persons();
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p.setFamily_name(a.getSurname());
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p.setGiven_name(a.getName());
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String identifier = new String();
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if (Optional.ofNullable(a.getPid()).isPresent()) {
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Tuple2<String, Boolean> orcid = eu.dnetlib.dhp.oa.graph.dump.skgif.Utils
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.getOrcid(a.getPid());
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if (orcid != null) {
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identifier = Utils.getIdentifier(Prefixes.PERSON, orcid._1() + orcid._2());
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if (orcid._2())
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p
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.setIdentifiers(
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Arrays.asList(Identifier.newInstance("orcid", orcid._1())));
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else
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p
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.setIdentifiers(
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Arrays
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.asList(Identifier.newInstance("inferred_orcid", orcid._1())));
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} else {
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if (Optional.ofNullable(a.getRank()).isPresent()) {
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identifier = Utils
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.getIdentifier(Prefixes.TEMPORARY_PERSON, r.getId() + a.getRank());
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} else {
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identifier = Utils
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.getIdentifier(Prefixes.TEMPORARY_PERSON, r.getId() + count);
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}
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}
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}
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p.setLocal_identifier(identifier);
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authors.add(p);
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}
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}
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return authors.iterator();
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}, Encoders.bean(Persons.class))
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.filter(Objects::nonNull)
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.write()
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.mode(SaveMode.Overwrite)
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.option("compression", "gzip")
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.json(workingDir + e.name() + "/person");
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}
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});
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Dataset<Persons> persons = spark.emptyDataset(Encoders.bean(Persons.class));
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for (EntityType entityType : ModelSupport.entityTypes.keySet()) {
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if (ModelSupport.isResult(entityType))
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persons = persons
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.union(Utils.readPath(spark, workingDir + entityType.name() + "/person", Persons.class));
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}
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persons
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.groupByKey((MapFunction<Persons, String>) p -> p.getLocal_identifier(), Encoders.STRING())
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.mapGroups((MapGroupsFunction<String, Persons, Persons>) (k, v) -> v.next(), Encoders.bean(Persons.class))
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.write()
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.mode(SaveMode.Overwrite)
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.option("compression", "gzip")
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.json(outputPath + "/Persons");
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}
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private static <R extends Result> void emitManifestation(SparkSession spark, String inputPath, String workingDir) {
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Dataset<Datasource> datasource = Utils
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.readPath(spark, inputPath + "datasource", Datasource.class)
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.filter(
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(FilterFunction<Datasource>) d -> Optional.ofNullable(d.getEosctype()).isPresent() &&
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d.getEosctype().getClassname().equalsIgnoreCase("Journal archive"));
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ModelSupport.entityTypes.keySet().forEach(e -> {
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if (ModelSupport.isResult(e)) {
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Class<R> resultClazz = ModelSupport.entityTypes.get(e);
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// Dataset<EmitPerManifestation> emitformanifestation =
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Utils
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.readPath(spark, inputPath + e.name(), resultClazz)
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.flatMap((FlatMapFunction<R, EmitPerManifestation>) p -> p.getInstance().stream().map(i -> {
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EmitPerManifestation epb = new EmitPerManifestation();
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epb.setResultId(p.getId());
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epb.setInstance(i);
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epb.setHostedBy(i.getHostedby().getKey());
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epb
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.setPublisher(
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Optional
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.ofNullable(p.getPublisher())
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.map(v -> v.getValue())
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.orElse(new String()));
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if (p.getClass() == Publication.class) {
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epb.setJournal(((Publication) p).getJournal());
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}
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return epb;
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}).collect(Collectors.toList()).iterator(), Encoders.bean(EmitPerManifestation.class))
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.write()
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.mode(SaveMode.Overwrite)
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.option("compression", "gzip")
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.json(workingDir + e.name() + "/manifestation");
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;
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}
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});
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Dataset<EmitPerManifestation> emitPerManifestationDataset = Utils
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.readPath(
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spark, workingDir + "software/manifestation", EmitPerManifestation.class)
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.union(
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Utils
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.readPath(
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spark, workingDir + "dataset/manifestation", EmitPerManifestation.class))
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.union(
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Utils
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.readPath(
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spark, workingDir + "publication/manifestation", EmitPerManifestation.class))
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.union(
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Utils
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.readPath(
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spark, workingDir + "otherresearchproduct/manifestation", EmitPerManifestation.class));
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emitPerManifestationDataset
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.groupByKey((MapFunction<EmitPerManifestation, String>) p -> p.getHostedBy(), Encoders.STRING())
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.mapGroups(
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(MapGroupsFunction<String, EmitPerManifestation, EmitPerManifestation>) (k, v) -> v.next(),
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Encoders.bean(EmitPerManifestation.class))
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.write()
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.mode(SaveMode.Overwrite)
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.option("compression", "gzip")
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.json(workingDir + "/datasourcePublisher");
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}
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}
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