Merge pull request 'scala_refactor' (#169) from scala_refactor into beta

Reviewed-on: D-Net/dnet-hadoop#169

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/scholix/SparkCreateActionset.scala

@@ -1,69 +0,0 @@
-package eu.dnetlib.dhp.actionmanager.scholix
-
-import eu.dnetlib.dhp.application.ArgumentApplicationParser
-import eu.dnetlib.dhp.schema.oaf.{Oaf, Relation, Result}
-import org.apache.spark.SparkConf
-import org.apache.spark.sql._
-import org.slf4j.{Logger, LoggerFactory}
-
-import scala.io.Source
-
-object SparkCreateActionset {
-
-  def main(args: Array[String]): Unit = {
-    val log: Logger = LoggerFactory.getLogger(getClass)
-    val conf: SparkConf = new SparkConf()
-    val parser = new ArgumentApplicationParser(Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/actionset/generate_actionset.json")).mkString)
-    parser.parseArgument(args)
-
-
-    val spark: SparkSession =
-      SparkSession
-        .builder()
-        .config(conf)
-        .appName(getClass.getSimpleName)
-        .master(parser.get("master")).getOrCreate()
-
-
-    val sourcePath = parser.get("sourcePath")
-    log.info(s"sourcePath  -> $sourcePath")
-
-    val targetPath = parser.get("targetPath")
-    log.info(s"targetPath  -> $targetPath")
-
-    val workingDirFolder = parser.get("workingDirFolder")
-    log.info(s"workingDirFolder  -> $workingDirFolder")
-
-    implicit val oafEncoders: Encoder[Oaf] = Encoders.kryo[Oaf]
-    implicit val resultEncoders: Encoder[Result] = Encoders.kryo[Result]
-    implicit val relationEncoders: Encoder[Relation] = Encoders.kryo[Relation]
-
-    import spark.implicits._
-
-    val relation = spark.read.load(s"$sourcePath/relation").as[Relation]
-
-    relation.filter(r => (r.getDataInfo == null || r.getDataInfo.getDeletedbyinference == false) && !r.getRelClass.toLowerCase.contains("merge"))
-      .flatMap(r => List(r.getSource, r.getTarget)).distinct().write.mode(SaveMode.Overwrite).save(s"$workingDirFolder/id_relation")
-
-
-    val idRelation = spark.read.load(s"$workingDirFolder/id_relation").as[String]
-
-    log.info("extract source and target Identifier involved in relations")
-
-
-    log.info("save relation filtered")
-
-    relation.filter(r => (r.getDataInfo == null || r.getDataInfo.getDeletedbyinference == false) && !r.getRelClass.toLowerCase.contains("merge"))
-      .write.mode(SaveMode.Overwrite).save(s"$workingDirFolder/actionSetOaf")
-
-    log.info("saving entities")
-
-    val entities: Dataset[(String, Result)] = spark.read.load(s"$sourcePath/entities/*").as[Result].map(p => (p.getId, p))(Encoders.tuple(Encoders.STRING, resultEncoders))
-
-    entities
-      .joinWith(idRelation, entities("_1").equalTo(idRelation("value")))
-      .map(p => p._1._2)
-      .write.mode(SaveMode.Append).save(s"$workingDirFolder/actionSetOaf")
-  }
-
-}

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/scholix/SparkSaveActionSet.scala

@@ -1,86 +0,0 @@
-package eu.dnetlib.dhp.actionmanager.scholix
-
-import com.fasterxml.jackson.databind.ObjectMapper
-import eu.dnetlib.dhp.application.ArgumentApplicationParser
-import eu.dnetlib.dhp.schema.action.AtomicAction
-import eu.dnetlib.dhp.schema.oaf.{Oaf, Dataset => OafDataset,Publication, Software, OtherResearchProduct, Relation}
-import org.apache.hadoop.io.Text
-import org.apache.hadoop.io.compress.GzipCodec
-import org.apache.hadoop.mapred.SequenceFileOutputFormat
-import org.apache.spark.SparkConf
-import org.apache.spark.sql.{Encoder, Encoders, SparkSession}
-import org.slf4j.{Logger, LoggerFactory}
-
-import scala.io.Source
-
-object SparkSaveActionSet {
-
-
-  def toActionSet(item: Oaf): (String, String) = {
-    val mapper = new ObjectMapper()
-
-    item match {
-      case dataset: OafDataset =>
-        val a: AtomicAction[OafDataset] = new AtomicAction[OafDataset]
-        a.setClazz(classOf[OafDataset])
-        a.setPayload(dataset)
-        (dataset.getClass.getCanonicalName, mapper.writeValueAsString(a))
-      case publication: Publication =>
-        val a: AtomicAction[Publication] = new AtomicAction[Publication]
-        a.setClazz(classOf[Publication])
-        a.setPayload(publication)
-        (publication.getClass.getCanonicalName, mapper.writeValueAsString(a))
-      case software: Software =>
-        val a: AtomicAction[Software] = new AtomicAction[Software]
-        a.setClazz(classOf[Software])
-        a.setPayload(software)
-        (software.getClass.getCanonicalName, mapper.writeValueAsString(a))
-      case orp: OtherResearchProduct =>
-        val a: AtomicAction[OtherResearchProduct] = new AtomicAction[OtherResearchProduct]
-        a.setClazz(classOf[OtherResearchProduct])
-        a.setPayload(orp)
-        (orp.getClass.getCanonicalName, mapper.writeValueAsString(a))
-
-      case relation: Relation =>
-        val a: AtomicAction[Relation] = new AtomicAction[Relation]
-        a.setClazz(classOf[Relation])
-        a.setPayload(relation)
-        (relation.getClass.getCanonicalName, mapper.writeValueAsString(a))
-      case _ =>
-        null
-    }
-
-  }
-
-  def main(args: Array[String]): Unit = {
-    val log: Logger = LoggerFactory.getLogger(getClass)
-    val conf: SparkConf = new SparkConf()
-    val parser = new ArgumentApplicationParser(Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/actionset/save_actionset.json")).mkString)
-    parser.parseArgument(args)
-
-
-    val spark: SparkSession =
-      SparkSession
-        .builder()
-        .config(conf)
-        .appName(getClass.getSimpleName)
-        .master(parser.get("master")).getOrCreate()
-
-
-    val sourcePath = parser.get("sourcePath")
-    log.info(s"sourcePath  -> $sourcePath")
-
-    val targetPath = parser.get("targetPath")
-    log.info(s"targetPath  -> $targetPath")
-
-    implicit val oafEncoders: Encoder[Oaf] = Encoders.kryo[Oaf]
-    implicit val tEncoder: Encoder[(String, String)] = Encoders.tuple(Encoders.STRING, Encoders.STRING)
-
-    spark.read.load(sourcePath).as[Oaf]
-      .map(o => toActionSet(o))
-      .filter(o => o != null)
-      .rdd.map(s => (new Text(s._1), new Text(s._2))).saveAsHadoopFile(s"$targetPath", classOf[Text], classOf[Text], classOf[SequenceFileOutputFormat[Text, Text]], classOf[GzipCodec])
-
-  }
-
-}

dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/datacite/DataciteModelConstants.scala

@@ -1,8 +1,8 @@
 package eu.dnetlib.dhp.datacite
 
 import eu.dnetlib.dhp.schema.common.ModelConstants
-import eu.dnetlib.dhp.schema.oaf.{DataInfo, KeyValue}
 import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils
+import eu.dnetlib.dhp.schema.oaf.{DataInfo, KeyValue}
 
 import java.io.InputStream
 import java.time.format.DateTimeFormatter

dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/datacite/DataciteToOAFTransformation.scala

@@ -6,7 +6,7 @@ import eu.dnetlib.dhp.datacite.DataciteModelConstants._
 import eu.dnetlib.dhp.schema.action.AtomicAction
 import eu.dnetlib.dhp.schema.common.ModelConstants
 import eu.dnetlib.dhp.schema.oaf.utils.{IdentifierFactory, OafMapperUtils}
-import eu.dnetlib.dhp.schema.oaf.{AccessRight, Author, DataInfo, Instance, KeyValue, Oaf, OtherResearchProduct, Publication, Qualifier, Relation, Result, Software, StructuredProperty, Dataset => OafDataset}
+import eu.dnetlib.dhp.schema.oaf.{Dataset => OafDataset, _}
 import eu.dnetlib.dhp.utils.DHPUtils
 import org.apache.commons.lang3.StringUtils
 import org.json4s.DefaultFormats
@@ -29,6 +29,7 @@ object DataciteToOAFTransformation {
   /**
    * This method should skip record if json contains invalid text
    * defined in gile datacite_filter
+   *
    * @param json
    * @return True if the record should be skipped
    */
@@ -107,9 +108,9 @@ object DataciteToOAFTransformation {
     d
   }
 
-  def fix_thai_date(input:String, format:String) :String = {
+  def fix_thai_date(input: String, format: String): String = {
     try {
-      val a_date = LocalDate.parse(input,DateTimeFormatter.ofPattern(format))
+      val a_date = LocalDate.parse(input, DateTimeFormatter.ofPattern(format))
       val d = ThaiBuddhistDate.of(a_date.getYear, a_date.getMonth.getValue, a_date.getDayOfMonth)
       LocalDate.from(d).toString
     } catch {
@@ -236,7 +237,7 @@ object DataciteToOAFTransformation {
       val p = match_pattern.get._2
       val grantId = m.matcher(awardUri).replaceAll("$2")
       val targetId = s"$p${DHPUtils.md5(grantId)}"
-      List( generateRelation(sourceId, targetId, "isProducedBy", DATACITE_COLLECTED_FROM, dataInfo) )
+      List(generateRelation(sourceId, targetId, "isProducedBy", DATACITE_COLLECTED_FROM, dataInfo))
     }
     else
       List()
@@ -335,15 +336,15 @@ object DataciteToOAFTransformation {
       .map(d => d.get)
 
     if (a_date.isDefined) {
-      if(doi.startsWith("10.14457"))
+      if (doi.startsWith("10.14457"))
-        result.setEmbargoenddate(OafMapperUtils.field(fix_thai_date(a_date.get,"[yyyy-MM-dd]"), null))
+        result.setEmbargoenddate(OafMapperUtils.field(fix_thai_date(a_date.get, "[yyyy-MM-dd]"), null))
       else
         result.setEmbargoenddate(OafMapperUtils.field(a_date.get, null))
     }
     if (i_date.isDefined && i_date.get.isDefined) {
-      if(doi.startsWith("10.14457")) {
+      if (doi.startsWith("10.14457")) {
-        result.setDateofacceptance(OafMapperUtils.field(fix_thai_date(i_date.get.get,"[yyyy-MM-dd]"), null))
+        result.setDateofacceptance(OafMapperUtils.field(fix_thai_date(i_date.get.get, "[yyyy-MM-dd]"), null))
-        result.getInstance().get(0).setDateofacceptance(OafMapperUtils.field(fix_thai_date(i_date.get.get,"[yyyy-MM-dd]"), null))
+        result.getInstance().get(0).setDateofacceptance(OafMapperUtils.field(fix_thai_date(i_date.get.get, "[yyyy-MM-dd]"), null))
       }
       else {
         result.setDateofacceptance(OafMapperUtils.field(i_date.get.get, null))
@@ -351,9 +352,9 @@ object DataciteToOAFTransformation {
       }
     }
     else if (publication_year != null) {
-      if(doi.startsWith("10.14457")) {
+      if (doi.startsWith("10.14457")) {
-        result.setDateofacceptance(OafMapperUtils.field(fix_thai_date(s"01-01-$publication_year","[dd-MM-yyyy]"), null))
+        result.setDateofacceptance(OafMapperUtils.field(fix_thai_date(s"01-01-$publication_year", "[dd-MM-yyyy]"), null))
-        result.getInstance().get(0).setDateofacceptance(OafMapperUtils.field(fix_thai_date(s"01-01-$publication_year","[dd-MM-yyyy]"), null))
+        result.getInstance().get(0).setDateofacceptance(OafMapperUtils.field(fix_thai_date(s"01-01-$publication_year", "[dd-MM-yyyy]"), null))
 
       } else {
         result.setDateofacceptance(OafMapperUtils.field(s"01-01-$publication_year", null))
@@ -457,7 +458,7 @@ object DataciteToOAFTransformation {
         JField("relatedIdentifier", JString(relatedIdentifier)) <- relIdentifier
       } yield RelatedIdentifierType(relationType, relatedIdentifier, relatedIdentifierType)
 
-      relations = relations ::: generateRelations(rels,result.getId, if (i_date.isDefined && i_date.get.isDefined) i_date.get.get else null)
+      relations = relations ::: generateRelations(rels, result.getId, if (i_date.isDefined && i_date.get.isDefined) i_date.get.get else null)
     }
     if (relations != null && relations.nonEmpty) {
       List(result) ::: relations
@@ -466,7 +467,7 @@ object DataciteToOAFTransformation {
       List(result)
   }
 
-  private def generateRelations(rels: List[RelatedIdentifierType], id:String, date:String):List[Relation] = {
+  private def generateRelations(rels: List[RelatedIdentifierType], id: String, date: String): List[Relation] = {
     rels
       .filter(r =>
         subRelTypeMapping.contains(r.relationType) && (
@@ -484,12 +485,12 @@ object DataciteToOAFTransformation {
         rel.setSubRelType(subRelType)
         rel.setRelClass(r.relationType)
 
-        val dateProps:KeyValue = OafMapperUtils.keyValue(DATE_RELATION_KEY, date)
+        val dateProps: KeyValue = OafMapperUtils.keyValue(DATE_RELATION_KEY, date)
 
         rel.setProperties(List(dateProps).asJava)
 
         rel.setSource(id)
-        rel.setTarget(DHPUtils.generateUnresolvedIdentifier(r.relatedIdentifier,r.relatedIdentifierType))
+        rel.setTarget(DHPUtils.generateUnresolvedIdentifier(r.relatedIdentifier, r.relatedIdentifierType))
         rel.setCollectedfrom(List(DATACITE_COLLECTED_FROM).asJava)
         rel.getCollectedfrom.asScala.map(c => c.getValue).toList
         rel

dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/sx/bio/BioDBToOAF.scala

@@ -7,6 +7,7 @@ import org.json4s.DefaultFormats
 import org.json4s.JsonAST.{JField, JObject, JString}
 import org.json4s.jackson.JsonMethods.{compact, parse, render}
 import collection.JavaConverters._
+
 object BioDBToOAF {
 
   case class EBILinkItem(id: Long, links: String) {}

dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/sx/bio/SparkTransformBioDatabaseToOAF.scala

@@ -1,9 +1,9 @@
 package eu.dnetlib.dhp.sx.bio
 
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
-import eu.dnetlib.dhp.schema.oaf.Oaf
-import BioDBToOAF.ScholixResolved
 import eu.dnetlib.dhp.collection.CollectionUtils
+import eu.dnetlib.dhp.schema.oaf.Oaf
+import eu.dnetlib.dhp.sx.bio.BioDBToOAF.ScholixResolved
 import org.apache.commons.io.IOUtils
 import org.apache.spark.SparkConf
 import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
@@ -36,13 +36,13 @@ object SparkTransformBioDatabaseToOAF {
     import spark.implicits._
     database.toUpperCase() match {
       case "UNIPROT" =>
-        spark.createDataset(sc.textFile(dbPath).flatMap(i => BioDBToOAF.uniprotToOAF(i))).flatMap(i=> CollectionUtils.fixRelations(i)).filter(i => i != null).write.mode(SaveMode.Overwrite).save(targetPath)
+        spark.createDataset(sc.textFile(dbPath).flatMap(i => BioDBToOAF.uniprotToOAF(i))).flatMap(i => CollectionUtils.fixRelations(i)).filter(i => i != null).write.mode(SaveMode.Overwrite).save(targetPath)
       case "PDB" =>
-        spark.createDataset(sc.textFile(dbPath).flatMap(i => BioDBToOAF.pdbTOOaf(i))).flatMap(i=> CollectionUtils.fixRelations(i)).filter(i => i != null).write.mode(SaveMode.Overwrite).save(targetPath)
+        spark.createDataset(sc.textFile(dbPath).flatMap(i => BioDBToOAF.pdbTOOaf(i))).flatMap(i => CollectionUtils.fixRelations(i)).filter(i => i != null).write.mode(SaveMode.Overwrite).save(targetPath)
       case "SCHOLIX" =>
-        spark.read.load(dbPath).as[ScholixResolved].map(i => BioDBToOAF.scholixResolvedToOAF(i)).flatMap(i=> CollectionUtils.fixRelations(i)).filter(i => i != null).write.mode(SaveMode.Overwrite).save(targetPath)
+        spark.read.load(dbPath).as[ScholixResolved].map(i => BioDBToOAF.scholixResolvedToOAF(i)).flatMap(i => CollectionUtils.fixRelations(i)).filter(i => i != null).write.mode(SaveMode.Overwrite).save(targetPath)
       case "CROSSREF_LINKS" =>
-        spark.createDataset(sc.textFile(dbPath).map(i => BioDBToOAF.crossrefLinksToOaf(i))).flatMap(i=> CollectionUtils.fixRelations(i)).filter(i => i != null).write.mode(SaveMode.Overwrite).save(targetPath)
+        spark.createDataset(sc.textFile(dbPath).map(i => BioDBToOAF.crossrefLinksToOaf(i))).flatMap(i => CollectionUtils.fixRelations(i)).filter(i => i != null).write.mode(SaveMode.Overwrite).save(targetPath)
     }
   }
 

dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/sx/bio/ebi/SparkCreateBaselineDataFrame.scala

@@ -3,7 +3,7 @@ package eu.dnetlib.dhp.sx.bio.ebi
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
 import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup
 import eu.dnetlib.dhp.schema.oaf.Result
-import eu.dnetlib.dhp.sx.bio.pubmed.{PMArticle, PMAuthor, PMJournal, PMParser, PubMedToOaf}
+import eu.dnetlib.dhp.sx.bio.pubmed._
 import eu.dnetlib.dhp.utils.ISLookupClientFactory
 import org.apache.commons.io.IOUtils
 import org.apache.hadoop.conf.Configuration

dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/sx/bio/ebi/SparkDownloadEBILinks.scala

@@ -1,9 +1,8 @@
 package eu.dnetlib.dhp.sx.bio.ebi
 
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
-import eu.dnetlib.dhp.sx.bio.pubmed.{PMArticle, PMAuthor, PMJournal}
 import eu.dnetlib.dhp.sx.bio.BioDBToOAF.EBILinkItem
-import eu.dnetlib.dhp.sx.bio.pubmed.PMJournal
+import eu.dnetlib.dhp.sx.bio.pubmed.{PMArticle, PMAuthor, PMJournal}
 import org.apache.commons.io.IOUtils
 import org.apache.http.client.config.RequestConfig
 import org.apache.http.client.methods.HttpGet

dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/sx/bio/ebi/SparkEBILinksToOaf.scala

@@ -1,11 +1,10 @@
 package eu.dnetlib.dhp.sx.bio.ebi
 
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
+import eu.dnetlib.dhp.collection.CollectionUtils
 import eu.dnetlib.dhp.schema.oaf.Oaf
 import eu.dnetlib.dhp.sx.bio.BioDBToOAF
 import eu.dnetlib.dhp.sx.bio.BioDBToOAF.EBILinkItem
-import BioDBToOAF.EBILinkItem
-import eu.dnetlib.dhp.collection.CollectionUtils
 import org.apache.commons.io.IOUtils
 import org.apache.spark.SparkConf
 import org.apache.spark.sql._
@@ -38,7 +37,7 @@ object SparkEBILinksToOaf {
     ebLinks.flatMap(j => BioDBToOAF.parse_ebi_links(j.links))
       .filter(p => BioDBToOAF.EBITargetLinksFilter(p))
       .flatMap(p => BioDBToOAF.convertEBILinksToOaf(p))
-      .flatMap(i=> CollectionUtils.fixRelations(i)).filter(i => i != null)
+      .flatMap(i => CollectionUtils.fixRelations(i)).filter(i => i != null)
       .write.mode(SaveMode.Overwrite).save(targetPath)
   }
 }

dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/sx/bio/pubmed/PubMedToOaf.scala

@@ -4,7 +4,7 @@ import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup
 import eu.dnetlib.dhp.schema.common.ModelConstants
 import eu.dnetlib.dhp.schema.oaf.utils.{GraphCleaningFunctions, IdentifierFactory, OafMapperUtils, PidType}
 import eu.dnetlib.dhp.schema.oaf._
-import scala.collection.JavaConverters._
+import collection.JavaConverters._
 
 import java.util.regex.Pattern
 
@@ -22,10 +22,10 @@ object PubMedToOaf {
   val collectedFrom: KeyValue = OafMapperUtils.keyValue(ModelConstants.EUROPE_PUBMED_CENTRAL_ID, "Europe PubMed Central")
 
 
-
   /**
    * Cleaning the DOI Applying regex in order to
    * remove doi starting with URL
+   *
    * @param doi input DOI
    * @return cleaned DOI
    */
@@ -49,7 +49,7 @@ object PubMedToOaf {
    * starting from OAF instanceType value
    *
    * @param cobjQualifier OAF instance type
-   * @param vocabularies All dnet vocabularies
+   * @param vocabularies  All dnet vocabularies
    * @return the correct instance
    */
   def createResult(cobjQualifier: Qualifier, vocabularies: VocabularyGroup): Result = {
@@ -65,7 +65,7 @@ object PubMedToOaf {
   }
 
   /**
-   *  Mapping the Pubmedjournal info into the OAF Journale
+   * Mapping the Pubmedjournal info into the OAF Journale
    *
    * @param j the pubmedJournal
    * @return the OAF Journal
@@ -91,9 +91,8 @@ object PubMedToOaf {
    * Find vocabulary term into synonyms and term in the vocabulary
    *
    * @param vocabularyName the input vocabulary name
-   * @param vocabularies all the vocabularies
+   * @param vocabularies   all the vocabularies
-   * @param term the term to find
+   * @param term           the term to find
-   *
    * @return the cleaned term value
    */
   def getVocabularyTerm(vocabularyName: String, vocabularies: VocabularyGroup, term: String): Qualifier = {
@@ -104,10 +103,9 @@ object PubMedToOaf {
 
 
   /**
-   *  Map the Pubmed Article into the OAF instance
+   * Map the Pubmed Article into the OAF instance
    *
-   *
+   * @param article      the pubmed articles
-   * @param article the pubmed articles
    * @param vocabularies the vocabularies
    * @return The OAF instance if the mapping did not fail
    */
@@ -185,7 +183,6 @@ object PubMedToOaf {
     //--------------------------------------------------------------------------------------
 
 
-
     // RESULT MAPPING
     //--------------------------------------------------------------------------------------
     result.setDateofacceptance(OafMapperUtils.field(GraphCleaningFunctions.cleanDate(article.getDate), dataInfo))

dhp-workflows/dhp-aggregation/src/test/java/eu/dnetlib/dhp/actionmanager/opencitations/CreateOpenCitationsASTest.java

@@ -89,13 +89,13 @@ public class CreateOpenCitationsASTest {
 					"-inputPath",
 					inputPath,
 					"-outputPath",
-					workingDir.toString() + "/actionSet"
+					workingDir.toString() + "/actionSet1"
 				});
 
 		final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
 
 		JavaRDD<Relation> tmp = sc
-			.sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class)
+			.sequenceFile(workingDir.toString() + "/actionSet1", Text.class, Text.class)
 			.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
 			.map(aa -> ((Relation) aa.getPayload()));
 
@@ -121,13 +121,13 @@ public class CreateOpenCitationsASTest {
 					"-inputPath",
 					inputPath,
 					"-outputPath",
-					workingDir.toString() + "/actionSet"
+					workingDir.toString() + "/actionSet2"
 				});
 
 		final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
 
 		JavaRDD<Relation> tmp = sc
-			.sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class)
+			.sequenceFile(workingDir.toString() + "/actionSet2", Text.class, Text.class)
 			.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
 			.map(aa -> ((Relation) aa.getPayload()));
 
@@ -153,13 +153,13 @@ public class CreateOpenCitationsASTest {
 					"-inputPath",
 					inputPath,
 					"-outputPath",
-					workingDir.toString() + "/actionSet"
+					workingDir.toString() + "/actionSet3"
 				});
 
 		final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
 
 		JavaRDD<Relation> tmp = sc
-			.sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class)
+			.sequenceFile(workingDir.toString() + "/actionSet3", Text.class, Text.class)
 			.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
 			.map(aa -> ((Relation) aa.getPayload()));
 
@@ -186,13 +186,13 @@ public class CreateOpenCitationsASTest {
 					"-inputPath",
 					inputPath,
 					"-outputPath",
-					workingDir.toString() + "/actionSet"
+					workingDir.toString() + "/actionSet4"
 				});
 
 		final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
 
 		JavaRDD<Relation> tmp = sc
-			.sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class)
+			.sequenceFile(workingDir.toString() + "/actionSet4", Text.class, Text.class)
 			.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
 			.map(aa -> ((Relation) aa.getPayload()));
 
@@ -226,13 +226,13 @@ public class CreateOpenCitationsASTest {
 					"-inputPath",
 					inputPath,
 					"-outputPath",
-					workingDir.toString() + "/actionSet"
+					workingDir.toString() + "/actionSet5"
 				});
 
 		final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
 
 		JavaRDD<Relation> tmp = sc
-			.sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class)
+			.sequenceFile(workingDir.toString() + "/actionSet5", Text.class, Text.class)
 			.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
 			.map(aa -> ((Relation) aa.getPayload()));
 
@@ -261,13 +261,13 @@ public class CreateOpenCitationsASTest {
 					"-inputPath",
 					inputPath,
 					"-outputPath",
-					workingDir.toString() + "/actionSet"
+					workingDir.toString() + "/actionSet6"
 				});
 
 		final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
 
 		JavaRDD<Relation> tmp = sc
-			.sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class)
+			.sequenceFile(workingDir.toString() + "/actionSet6", Text.class, Text.class)
 			.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
 			.map(aa -> ((Relation) aa.getPayload()));
 
@@ -306,13 +306,13 @@ public class CreateOpenCitationsASTest {
 					"-inputPath",
 					inputPath,
 					"-outputPath",
-					workingDir.toString() + "/actionSet"
+					workingDir.toString() + "/actionSet7"
 				});
 
 		final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
 
 		JavaRDD<Relation> tmp = sc
-			.sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class)
+			.sequenceFile(workingDir.toString() + "/actionSet7", Text.class, Text.class)
 			.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
 			.map(aa -> ((Relation) aa.getPayload()));
 

dhp-workflows/dhp-aggregation/src/test/scala/eu/dnetlib/dhp/datacite/DataciteToOAFTest.scala

@@ -8,6 +8,7 @@ import org.apache.commons.io.FileUtils
 import org.apache.spark.SparkConf
 import org.apache.spark.sql.functions.{col, count}
 import org.apache.spark.sql.{Dataset, Encoder, Encoders, SparkSession}
+import org.junit.jupiter.api.Assertions._
 import org.junit.jupiter.api.extension.ExtendWith
 import org.junit.jupiter.api.{AfterEach, BeforeEach, Test}
 import org.mockito.junit.jupiter.MockitoExtension
@@ -17,7 +18,6 @@ import java.nio.file.{Files, Path}
 import java.text.SimpleDateFormat
 import java.util.Locale
 import scala.io.Source
-import org.junit.jupiter.api.Assertions._
 
 @ExtendWith(Array(classOf[MockitoExtension]))
 class DataciteToOAFTest extends  AbstractVocabularyTest{

dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/DoiBoostMappingUtil.scala

@@ -1,21 +1,19 @@
 package eu.dnetlib.doiboost
 
-import java.time.LocalDate
+import com.fasterxml.jackson.databind.ObjectMapper
-import java.time.format.DateTimeFormatter
-
 import eu.dnetlib.dhp.schema.action.AtomicAction
-import eu.dnetlib.dhp.schema.oaf.{AccessRight, DataInfo, Dataset, Field, Instance, KeyValue, Oaf, OpenAccessRoute, Organization, Publication, Qualifier, Relation, Result, StructuredProperty}
+import eu.dnetlib.dhp.schema.common.ModelConstants
+import eu.dnetlib.dhp.schema.oaf._
+import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils
 import eu.dnetlib.dhp.utils.DHPUtils
 import org.apache.commons.lang3.StringUtils
-import com.fasterxml.jackson.databind.ObjectMapper
-import eu.dnetlib.dhp.schema.common.ModelConstants
-import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils
-import eu.dnetlib.doiboost.DoiBoostMappingUtil.{getClosedAccessQualifier, getEmbargoedAccessQualifier, getUnknownQualifier}
 import org.json4s
 import org.json4s.DefaultFormats
 import org.json4s.jackson.JsonMethods.parse
 import org.slf4j.{Logger, LoggerFactory}
 
+import java.time.LocalDate
+import java.time.format.DateTimeFormatter
 import scala.collection.JavaConverters._
 
 

dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/SparkGenerateDOIBoostActionSet.scala

@@ -8,11 +8,12 @@ import org.apache.hadoop.io.Text
 import org.apache.hadoop.io.compress.GzipCodec
 import org.apache.hadoop.mapred.SequenceFileOutputFormat
 import org.apache.spark.SparkConf
-import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
+import org.apache.spark.sql.{Dataset, Encoder, Encoders, SparkSession}
 import org.slf4j.{Logger, LoggerFactory}
 
 object SparkGenerateDOIBoostActionSet {
   val logger: Logger = LoggerFactory.getLogger(getClass)
+
   def main(args: Array[String]): Unit = {
 
     val conf: SparkConf = new SparkConf()
@@ -33,53 +34,41 @@ object SparkGenerateDOIBoostActionSet {
 
     implicit val mapEncoderAtomiAction: Encoder[AtomicAction[OafDataset]] = Encoders.kryo[AtomicAction[OafDataset]]
 
-    val dbPublicationPath           = parser.get("dbPublicationPath")
+    val dbPublicationPath = parser.get("dbPublicationPath")
-    val dbDatasetPath               = parser.get("dbDatasetPath")
+    val dbDatasetPath = parser.get("dbDatasetPath")
-    val crossRefRelation            = parser.get("crossRefRelation")
+    val crossRefRelation = parser.get("crossRefRelation")
-    val dbaffiliationRelationPath   = parser.get("dbaffiliationRelationPath")
+    val dbaffiliationRelationPath = parser.get("dbaffiliationRelationPath")
-    val dbOrganizationPath          = parser.get("dbOrganizationPath")
+    val dbOrganizationPath = parser.get("dbOrganizationPath")
-    val sequenceFilePath            = parser.get("sFilePath")
+    val sequenceFilePath = parser.get("sFilePath")
 
     val asDataset = spark.read.load(dbDatasetPath).as[OafDataset]
       .filter(p => p != null || p.getId != null)
-      .map(d =>DoiBoostMappingUtil.fixResult(d))
+      .map(d => DoiBoostMappingUtil.fixResult(d))
-      .map(d=>DoiBoostMappingUtil.toActionSet(d))(Encoders.tuple(Encoders.STRING, Encoders.STRING))
+      .map(d => DoiBoostMappingUtil.toActionSet(d))(Encoders.tuple(Encoders.STRING, Encoders.STRING))
 
 
-    val asPublication =spark.read.load(dbPublicationPath).as[Publication]
+    val asPublication = spark.read.load(dbPublicationPath).as[Publication]
       .filter(p => p != null || p.getId != null)
-      .map(d=>DoiBoostMappingUtil.toActionSet(d))(Encoders.tuple(Encoders.STRING, Encoders.STRING))
+      .map(d => DoiBoostMappingUtil.toActionSet(d))(Encoders.tuple(Encoders.STRING, Encoders.STRING))
 
 
     val asOrganization = spark.read.load(dbOrganizationPath).as[Organization]
-      .map(d=>DoiBoostMappingUtil.toActionSet(d))(Encoders.tuple(Encoders.STRING, Encoders.STRING))
+      .map(d => DoiBoostMappingUtil.toActionSet(d))(Encoders.tuple(Encoders.STRING, Encoders.STRING))
-
 
 
     val asCRelation = spark.read.load(crossRefRelation).as[Relation]
-      .filter(r => r!= null && r.getSource != null && r.getTarget != null)
+      .filter(r => r != null && r.getSource != null && r.getTarget != null)
-      .map(d=>DoiBoostMappingUtil.toActionSet(d))(Encoders.tuple(Encoders.STRING, Encoders.STRING))
+      .map(d => DoiBoostMappingUtil.toActionSet(d))(Encoders.tuple(Encoders.STRING, Encoders.STRING))
 
 
     val asRelAffiliation = spark.read.load(dbaffiliationRelationPath).as[Relation]
-      .map(d=>DoiBoostMappingUtil.toActionSet(d))(Encoders.tuple(Encoders.STRING, Encoders.STRING))
+      .map(d => DoiBoostMappingUtil.toActionSet(d))(Encoders.tuple(Encoders.STRING, Encoders.STRING))
-
-
-
 
 
     val d: Dataset[(String, String)] = asDataset.union(asPublication).union(asOrganization).union(asCRelation).union(asRelAffiliation)
 
 
-
+    d.rdd.repartition(6000).map(s => (new Text(s._1), new Text(s._2))).saveAsHadoopFile(s"$sequenceFilePath", classOf[Text], classOf[Text], classOf[SequenceFileOutputFormat[Text, Text]], classOf[GzipCodec])
-    d.rdd.repartition(6000).map(s => (new Text(s._1), new Text(s._2))).saveAsHadoopFile(s"$sequenceFilePath", classOf[Text], classOf[Text], classOf[SequenceFileOutputFormat[Text,Text]], classOf[GzipCodec])
-
-
-
-
-
-
-
 
 
   }

dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/SparkGenerateDoiBoost.scala

@@ -9,28 +9,26 @@ import org.apache.commons.io.IOUtils
 import org.apache.spark.SparkConf
 import org.apache.spark.sql.expressions.Aggregator
 import org.apache.spark.sql.functions.col
-import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
+import org.apache.spark.sql._
-import org.slf4j.{Logger, LoggerFactory}
-
-import scala.collection.JavaConverters._
 import org.json4s.DefaultFormats
-import org.json4s.JsonAST.{JField, JObject, JString,JArray}
+import org.json4s.JsonAST.{JField, JObject, JString}
 import org.json4s.jackson.JsonMethods.parse
-
+import org.slf4j.{Logger, LoggerFactory}
+import scala.collection.JavaConverters._
 object SparkGenerateDoiBoost {
 
 
-  def extractIdGRID(input:String):List[(String,String)] = {
+  def extractIdGRID(input: String): List[(String, String)] = {
     implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
     lazy val json: org.json4s.JValue = parse(input)
 
-    val id:String = (json \ "id").extract[String]
+    val id: String = (json \ "id").extract[String]
 
-    val grids:List[String] = for {
+    val grids: List[String] = for {
 
       JObject(pid) <- json \ "pid"
       JField("qualifier", JObject(qualifier)) <- pid
-      JField("classid",   JString(classid)) <-qualifier
+      JField("classid", JString(classid)) <- qualifier
       JField("value", JString(vl)) <- pid
       if classid == "GRID"
     } yield vl
@@ -38,7 +36,6 @@ object SparkGenerateDoiBoost {
   }
 
 
-
   def main(args: Array[String]): Unit = {
 
     val logger: Logger = LoggerFactory.getLogger(getClass)
@@ -73,7 +70,7 @@ object SparkGenerateDoiBoost {
           if (a != null && a._2 != null) {
             b.mergeFrom(a._2)
             b.setId(a._1)
-            val authors =AuthorMerger.mergeAuthor(b.getAuthor, a._2.getAuthor)
+            val authors = AuthorMerger.mergeAuthor(b.getAuthor, a._2.getAuthor)
             b.setAuthor(authors)
             return b
           }
@@ -87,11 +84,11 @@ object SparkGenerateDoiBoost {
             return b2
         }
         else {
-          if (b2 != null ) {
+          if (b2 != null) {
             b1.mergeFrom(b2)
-            val authors =AuthorMerger.mergeAuthor(b1.getAuthor, b2.getAuthor)
+            val authors = AuthorMerger.mergeAuthor(b1.getAuthor, b2.getAuthor)
             b1.setAuthor(authors)
-            if (b2.getId!= null && b2.getId.nonEmpty)
+            if (b2.getId != null && b2.getId.nonEmpty)
               b1.setId(b2.getId)
             return b1
           }
@@ -118,10 +115,9 @@ object SparkGenerateDoiBoost {
     val crossrefPublication: Dataset[(String, Publication)] = spark.read.load(s"$workingDirPath/crossrefPublication").as[Publication].map(p => (p.getId, p))
     val uwPublication: Dataset[(String, Publication)] = spark.read.load(s"$workingDirPath/uwPublication").as[Publication].map(p => (p.getId, p))
 
-    def applyMerge(item:((String, Publication), (String, Publication))) : Publication =
+    def applyMerge(item: ((String, Publication), (String, Publication))): Publication = {
-    {
       val crossrefPub = item._1._2
-      if (item._2!= null) {
+      if (item._2 != null) {
         val otherPub = item._2._2
         if (otherPub != null) {
           crossrefPub.mergeFrom(otherPub)
@@ -130,6 +126,7 @@ object SparkGenerateDoiBoost {
       }
       crossrefPub
     }
+
     crossrefPublication.joinWith(uwPublication, crossrefPublication("_1").equalTo(uwPublication("_1")), "left").map(applyMerge).write.mode(SaveMode.Overwrite).save(s"$workingDirPath/firstJoin")
     logger.info("Phase 3) Join Result with ORCID")
     val fj: Dataset[(String, Publication)] = spark.read.load(s"$workingDirPath/firstJoin").as[Publication].map(p => (p.getId, p))
@@ -143,9 +140,9 @@ object SparkGenerateDoiBoost {
     sj.joinWith(magPublication, sj("_1").equalTo(magPublication("_1")), "left").map(applyMerge).write.mode(SaveMode.Overwrite).save(s"$workingDirPath/doiBoostPublication")
 
 
-    val doiBoostPublication: Dataset[(String,Publication)] = spark.read.load(s"$workingDirPath/doiBoostPublication").as[Publication].filter(p=>DoiBoostMappingUtil.filterPublication(p)).map(DoiBoostMappingUtil.toISSNPair)(tupleForJoinEncoder)
+    val doiBoostPublication: Dataset[(String, Publication)] = spark.read.load(s"$workingDirPath/doiBoostPublication").as[Publication].filter(p => DoiBoostMappingUtil.filterPublication(p)).map(DoiBoostMappingUtil.toISSNPair)(tupleForJoinEncoder)
 
-    val hostedByDataset : Dataset[(String, HostedByItemType)] = spark.createDataset(spark.sparkContext.textFile(hostedByMapPath).map(DoiBoostMappingUtil.toHostedByItem))
+    val hostedByDataset: Dataset[(String, HostedByItemType)] = spark.createDataset(spark.sparkContext.textFile(hostedByMapPath).map(DoiBoostMappingUtil.toHostedByItem))
 
 
     doiBoostPublication.joinWith(hostedByDataset, doiBoostPublication("_1").equalTo(hostedByDataset("_1")), "left")
@@ -164,21 +161,20 @@ object SparkGenerateDoiBoost {
     val paperAffiliation = spark.read.load(paperAffiliationPath).select(col("AffiliationId").alias("affId"), col("PaperId"))
 
 
-    val a:Dataset[DoiBoostAffiliation] = paperAffiliation
+    val a: Dataset[DoiBoostAffiliation] = paperAffiliation
       .joinWith(affiliation, paperAffiliation("affId").equalTo(affiliation("AffiliationId")))
       .select(col("_1.PaperId"), col("_2.AffiliationId"), col("_2.GridId"), col("_2.OfficialPage"), col("_2.DisplayName")).as[DoiBoostAffiliation]
 
 
-
+    val magPubs: Dataset[(String, Publication)] = spark.read.load(s"$workingDirPath/doiBoostPublicationFiltered").as[Publication]
-    val magPubs:Dataset[(String,Publication)]= spark.read.load(s"$workingDirPath/doiBoostPublicationFiltered").as[Publication]
+      .map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p))(tupleForJoinEncoder).filter(s => s._1 != null)
-      .map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p))(tupleForJoinEncoder).filter(s =>s._1!= null )
 
 
-    magPubs.joinWith(a,magPubs("_1").equalTo(a("PaperId"))).flatMap(item => {
+    magPubs.joinWith(a, magPubs("_1").equalTo(a("PaperId"))).flatMap(item => {
-      val pub:Publication = item._1._2
+      val pub: Publication = item._1._2
       val affiliation = item._2
-      val affId:String = if (affiliation.GridId.isDefined) s"unresolved::grid::${affiliation.GridId.get.toLowerCase}" else  DoiBoostMappingUtil.generateMAGAffiliationId(affiliation.AffiliationId.toString)
+      val affId: String = if (affiliation.GridId.isDefined) s"unresolved::grid::${affiliation.GridId.get.toLowerCase}" else DoiBoostMappingUtil.generateMAGAffiliationId(affiliation.AffiliationId.toString)
-      val r:Relation = new Relation
+      val r: Relation = new Relation
       r.setSource(pub.getId)
       r.setTarget(affId)
       r.setRelType(ModelConstants.RESULT_ORGANIZATION)
@@ -186,7 +182,7 @@ object SparkGenerateDoiBoost {
       r.setSubRelType(ModelConstants.AFFILIATION)
       r.setDataInfo(pub.getDataInfo)
       r.setCollectedfrom(List(DoiBoostMappingUtil.createMAGCollectedFrom()).asJava)
-      val r1:Relation = new Relation
+      val r1: Relation = new Relation
       r1.setTarget(pub.getId)
       r1.setSource(affId)
       r1.setRelType(ModelConstants.RESULT_ORGANIZATION)
@@ -198,33 +194,31 @@ object SparkGenerateDoiBoost {
     })(mapEncoderRel).write.mode(SaveMode.Overwrite).save(s"$workingDirPath/doiBoostPublicationAffiliation_unresolved")
 
 
-
+    val unresolvedRels: Dataset[(String, Relation)] = spark.read.load(s"$workingDirPath/doiBoostPublicationAffiliation_unresolved").as[Relation].map(r => {
-
-    val unresolvedRels:Dataset[(String, Relation)] = spark.read.load(s"$workingDirPath/doiBoostPublicationAffiliation_unresolved").as[Relation].map(r => {
 
       if (r.getSource.startsWith("unresolved"))
         (r.getSource, r)
       else if (r.getTarget.startsWith("unresolved"))
-        (r.getTarget,r)
+        (r.getTarget, r)
-        else
+      else
         ("resolved", r)
     })(Encoders.tuple(Encoders.STRING, mapEncoderRel))
 
-    val openaireOrganization:Dataset[(String,String)] = spark.read.text(openaireOrganizationPath).as[String].flatMap(s => extractIdGRID(s)).groupByKey(_._2).reduceGroups((x,y) => if (x != null) x else y ).map(_._2)
+    val openaireOrganization: Dataset[(String, String)] = spark.read.text(openaireOrganizationPath).as[String].flatMap(s => extractIdGRID(s)).groupByKey(_._2).reduceGroups((x, y) => if (x != null) x else y).map(_._2)
 
-    unresolvedRels.joinWith(openaireOrganization,unresolvedRels("_1").equalTo(openaireOrganization("_2")))
+    unresolvedRels.joinWith(openaireOrganization, unresolvedRels("_1").equalTo(openaireOrganization("_2")))
       .map { x =>
         val currentRels = x._1._2
         val currentOrgs = x._2
-        if (currentOrgs!= null)
+        if (currentOrgs != null)
-          if(currentRels.getSource.startsWith("unresolved"))
+          if (currentRels.getSource.startsWith("unresolved"))
             currentRels.setSource(currentOrgs._1)
           else
             currentRels.setTarget(currentOrgs._1)
-      currentRels
+        currentRels
-      }.filter(r=> !r.getSource.startsWith("unresolved") && !r.getTarget.startsWith("unresolved")).write.mode(SaveMode.Overwrite).save(s"$workingDirPath/doiBoostPublicationAffiliation")
+      }.filter(r => !r.getSource.startsWith("unresolved") && !r.getTarget.startsWith("unresolved")).write.mode(SaveMode.Overwrite).save(s"$workingDirPath/doiBoostPublicationAffiliation")
 
-    magPubs.joinWith(a,magPubs("_1").equalTo(a("PaperId"))).map( item => {
+    magPubs.joinWith(a, magPubs("_1").equalTo(a("PaperId"))).map(item => {
       val affiliation = item._2
       if (affiliation.GridId.isEmpty) {
         val o = new Organization
@@ -241,7 +235,7 @@ object SparkGenerateDoiBoost {
       }
       else
         null
-    }).filter(o=> o!=null).write.mode(SaveMode.Overwrite).save(s"$workingDirPath/doiBoostOrganization")
+    }).filter(o => o != null).write.mode(SaveMode.Overwrite).save(s"$workingDirPath/doiBoostOrganization")
-    }
+  }
 
 }

dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/crossref/Crossref2Oaf.scala

@@ -4,20 +4,19 @@ import eu.dnetlib.dhp.schema.common.ModelConstants
 import eu.dnetlib.dhp.schema.oaf._
 import eu.dnetlib.dhp.schema.oaf.utils.{IdentifierFactory, OafMapperUtils}
 import eu.dnetlib.dhp.utils.DHPUtils
-import eu.dnetlib.doiboost.DoiBoostMappingUtil.{decideAccessRight, _}
+import eu.dnetlib.doiboost.DoiBoostMappingUtil
+import eu.dnetlib.doiboost.DoiBoostMappingUtil._
 import org.apache.commons.lang.StringUtils
 import org.json4s
 import org.json4s.DefaultFormats
-import org.json4s.JsonAST.{JValue, _}
+import org.json4s.JsonAST._
 import org.json4s.jackson.JsonMethods._
 import org.slf4j.{Logger, LoggerFactory}
 
+import java.util
 import scala.collection.JavaConverters._
 import scala.collection.mutable
 import scala.util.matching.Regex
-import java.util
-
-import eu.dnetlib.doiboost.DoiBoostMappingUtil
 
 case class CrossrefDT(doi: String, json:String, timestamp: Long) {}
 

dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/crossref/CrossrefDataset.scala

@@ -6,7 +6,7 @@ import org.apache.commons.io.IOUtils
 import org.apache.hadoop.io.{IntWritable, Text}
 import org.apache.spark.SparkConf
 import org.apache.spark.sql.expressions.Aggregator
-import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
+import org.apache.spark.sql.{Dataset, Encoder, SaveMode, SparkSession}
 import org.json4s
 import org.json4s.DefaultFormats
 import org.json4s.jackson.JsonMethods.parse
@@ -17,12 +17,12 @@ object CrossrefDataset {
   val logger: Logger = LoggerFactory.getLogger(SparkMapDumpIntoOAF.getClass)
 
 
-  def to_item(input:String):CrossrefDT = {
+  def to_item(input: String): CrossrefDT = {
 
     implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
     lazy val json: json4s.JValue = parse(input)
-    val ts:Long = (json \ "indexed" \ "timestamp").extract[Long]
+    val ts: Long = (json \ "indexed" \ "timestamp").extract[Long]
-    val doi:String  = DoiBoostMappingUtil.normalizeDoi((json \ "DOI").extract[String])
+    val doi: String = DoiBoostMappingUtil.normalizeDoi((json \ "DOI").extract[String])
     CrossrefDT(doi, input, ts)
 
   }
@@ -30,7 +30,6 @@ object CrossrefDataset {
   def main(args: Array[String]): Unit = {
 
 
-
     val conf: SparkConf = new SparkConf()
     val parser = new ArgumentApplicationParser(IOUtils.toString(CrossrefDataset.getClass.getResourceAsStream("/eu/dnetlib/dhp/doiboost/crossref_to_dataset_params.json")))
     parser.parseArgument(args)
@@ -54,7 +53,7 @@ object CrossrefDataset {
           return b
 
 
-        if(a.timestamp >b.timestamp) {
+        if (a.timestamp > b.timestamp) {
           return a
         }
         b
@@ -66,7 +65,7 @@ object CrossrefDataset {
         if (a == null)
           return b
 
-        if(a.timestamp >b.timestamp) {
+        if (a.timestamp > b.timestamp) {
           return a
         }
         b
@@ -79,20 +78,20 @@ object CrossrefDataset {
       override def finish(reduction: CrossrefDT): CrossrefDT = reduction
     }
 
-    val workingPath:String = parser.get("workingPath")
+    val workingPath: String = parser.get("workingPath")
 
 
-    val main_ds:Dataset[CrossrefDT] = spark.read.load(s"$workingPath/crossref_ds").as[CrossrefDT]
+    val main_ds: Dataset[CrossrefDT] = spark.read.load(s"$workingPath/crossref_ds").as[CrossrefDT]
 
 
     val update =
-      spark.createDataset(spark.sparkContext.sequenceFile(s"$workingPath/index_update",  classOf[IntWritable], classOf[Text])
+      spark.createDataset(spark.sparkContext.sequenceFile(s"$workingPath/index_update", classOf[IntWritable], classOf[Text])
-        .map(i =>CrossrefImporter.decompressBlob(i._2.toString))
+        .map(i => CrossrefImporter.decompressBlob(i._2.toString))
-        .map(i =>to_item(i)))
+        .map(i => to_item(i)))
 
     main_ds.union(update).groupByKey(_.doi)
       .agg(crossrefAggregator.toColumn)
-      .map(s=>s._2)
+      .map(s => s._2)
       .write.mode(SaveMode.Overwrite).save(s"$workingPath/crossref_ds_updated")
 
   }

dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/crossref/GenerateCrossrefDataset.scala

@@ -2,17 +2,12 @@ package eu.dnetlib.doiboost.crossref
 
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
 import eu.dnetlib.doiboost.DoiBoostMappingUtil
-import eu.dnetlib.doiboost.crossref.CrossrefDataset.to_item
-import eu.dnetlib.doiboost.crossref.UnpackCrtossrefEntries.getClass
-import org.apache.hadoop.io.{IntWritable, Text}
-import org.apache.hadoop.io.compress.GzipCodec
 import org.apache.spark.rdd.RDD
-import org.apache.spark.{SparkConf, SparkContext}
 import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
+import org.apache.spark.{SparkConf, SparkContext}
 import org.json4s
 import org.json4s.DefaultFormats
-import org.json4s.JsonAST.JArray
+import org.json4s.jackson.JsonMethods.parse
-import org.json4s.jackson.JsonMethods.{compact, parse, render}
 import org.slf4j.{Logger, LoggerFactory}
 
 import scala.io.Source
@@ -24,11 +19,10 @@ object GenerateCrossrefDataset {
   implicit val mrEncoder: Encoder[CrossrefDT] = Encoders.kryo[CrossrefDT]
 
 
-
   def crossrefElement(meta: String): CrossrefDT = {
     implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
     lazy val json: json4s.JValue = parse(meta)
-    val doi:String = DoiBoostMappingUtil.normalizeDoi((json \ "DOI").extract[String])
+    val doi: String = DoiBoostMappingUtil.normalizeDoi((json \ "DOI").extract[String])
     val timestamp: Long = (json \ "indexed" \ "timestamp").extract[Long]
     CrossrefDT(doi, meta, timestamp)
 
@@ -51,14 +45,14 @@ object GenerateCrossrefDataset {
     import spark.implicits._
 
 
-    val tmp : RDD[String] = sc.textFile(sourcePath,6000)
+    val tmp: RDD[String] = sc.textFile(sourcePath, 6000)
 
     spark.createDataset(tmp)
       .map(entry => crossrefElement(entry))
       .write.mode(SaveMode.Overwrite).save(targetPath)
-//               .map(meta => crossrefElement(meta))
+    //               .map(meta => crossrefElement(meta))
-//               .toDS.as[CrossrefDT]
+    //               .toDS.as[CrossrefDT]
-//              .write.mode(SaveMode.Overwrite).save(targetPath)
+    //              .write.mode(SaveMode.Overwrite).save(targetPath)
 
   }
 

dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/crossref/SparkMapDumpIntoOAF.scala

@@ -4,10 +4,8 @@ import eu.dnetlib.dhp.application.ArgumentApplicationParser
 import eu.dnetlib.dhp.schema.oaf
 import eu.dnetlib.dhp.schema.oaf.{Oaf, Publication, Relation, Dataset => OafDataset}
 import org.apache.commons.io.IOUtils
-
 import org.apache.spark.SparkConf
-
+import org.apache.spark.sql._
-import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
 import org.slf4j.{Logger, LoggerFactory}
 
 

dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/crossref/UnpackCrtossrefEntries.scala

@@ -2,8 +2,8 @@ package eu.dnetlib.doiboost.crossref
 
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
 import org.apache.hadoop.io.compress.GzipCodec
+import org.apache.spark.sql.SparkSession
 import org.apache.spark.{SparkConf, SparkContext}
-import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
 import org.json4s
 import org.json4s.DefaultFormats
 import org.json4s.JsonAST.JArray
@@ -17,9 +17,7 @@ object UnpackCrtossrefEntries {
   val log: Logger = LoggerFactory.getLogger(UnpackCrtossrefEntries.getClass)
 
 
-
+  def extractDump(input: String): List[String] = {
-
-  def extractDump(input:String):List[String] = {
     implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
     lazy val json: json4s.JValue = parse(input)
 
@@ -30,7 +28,6 @@ object UnpackCrtossrefEntries {
   }
 
 
-
   def main(args: Array[String]): Unit = {
     val conf = new SparkConf
     val parser = new ArgumentApplicationParser(Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/doiboost/crossref_dump_reader/generate_dataset_params.json")).mkString)
@@ -45,7 +42,7 @@ object UnpackCrtossrefEntries {
       .getOrCreate()
     val sc: SparkContext = spark.sparkContext
 
-    sc.wholeTextFiles(sourcePath,6000).flatMap(d =>extractDump(d._2))
+    sc.wholeTextFiles(sourcePath, 6000).flatMap(d => extractDump(d._2))
       .saveAsTextFile(targetPath, classOf[GzipCodec])
 
 

dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/mag/MagDataModel.scala

@@ -5,10 +5,10 @@ import eu.dnetlib.dhp.schema.common.ModelConstants
 import eu.dnetlib.dhp.schema.oaf.utils.IdentifierFactory
 import eu.dnetlib.dhp.schema.oaf.{Instance, Journal, Publication, StructuredProperty}
 import eu.dnetlib.doiboost.DoiBoostMappingUtil
+import eu.dnetlib.doiboost.DoiBoostMappingUtil._
 import org.json4s
 import org.json4s.DefaultFormats
 import org.json4s.jackson.JsonMethods.parse
-import eu.dnetlib.doiboost.DoiBoostMappingUtil._
 
 import scala.collection.JavaConverters._
 import scala.collection.mutable

dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/mag/SparkImportMagIntoDataset.scala

@@ -3,8 +3,8 @@ package eu.dnetlib.doiboost.mag
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
 import org.apache.commons.io.IOUtils
 import org.apache.spark.SparkConf
-import org.apache.spark.sql.{SaveMode, SparkSession}
 import org.apache.spark.sql.types._
+import org.apache.spark.sql.{SaveMode, SparkSession}
 import org.slf4j.{Logger, LoggerFactory}
 
 object SparkImportMagIntoDataset {
@@ -24,13 +24,13 @@ object SparkImportMagIntoDataset {
     "Affiliations" -> Tuple2("mag/Affiliations.txt", Seq("AffiliationId:long", "Rank:uint", "NormalizedName:string", "DisplayName:string", "GridId:string", "OfficialPage:string", "WikiPage:string", "PaperCount:long", "PaperFamilyCount:long", "CitationCount:long", "Iso3166Code:string", "Latitude:float?", "Longitude:float?", "CreatedDate:DateTime")),
     "AuthorExtendedAttributes" -> Tuple2("mag/AuthorExtendedAttributes.txt", Seq("AuthorId:long", "AttributeType:int", "AttributeValue:string")),
     "Authors" -> Tuple2("mag/Authors.txt", Seq("AuthorId:long", "Rank:uint", "NormalizedName:string", "DisplayName:string", "LastKnownAffiliationId:long?", "PaperCount:long", "PaperFamilyCount:long", "CitationCount:long", "CreatedDate:DateTime")),
-    "ConferenceInstances" -> Tuple2("mag/ConferenceInstances.txt", Seq("ConferenceInstanceId:long", "NormalizedName:string", "DisplayName:string", "ConferenceSeriesId:long", "Location:string", "OfficialUrl:string", "StartDate:DateTime?", "EndDate:DateTime?", "AbstractRegistrationDate:DateTime?", "SubmissionDeadlineDate:DateTime?", "NotificationDueDate:DateTime?", "FinalVersionDueDate:DateTime?", "PaperCount:long", "PaperFamilyCount:long" ,"CitationCount:long", "Latitude:float?", "Longitude:float?", "CreatedDate:DateTime")),
+    "ConferenceInstances" -> Tuple2("mag/ConferenceInstances.txt", Seq("ConferenceInstanceId:long", "NormalizedName:string", "DisplayName:string", "ConferenceSeriesId:long", "Location:string", "OfficialUrl:string", "StartDate:DateTime?", "EndDate:DateTime?", "AbstractRegistrationDate:DateTime?", "SubmissionDeadlineDate:DateTime?", "NotificationDueDate:DateTime?", "FinalVersionDueDate:DateTime?", "PaperCount:long", "PaperFamilyCount:long", "CitationCount:long", "Latitude:float?", "Longitude:float?", "CreatedDate:DateTime")),
     "ConferenceSeries" -> Tuple2("mag/ConferenceSeries.txt", Seq("ConferenceSeriesId:long", "Rank:uint", "NormalizedName:string", "DisplayName:string", "PaperCount:long", "PaperFamilyCount:long", "CitationCount:long", "CreatedDate:DateTime")),
     "EntityRelatedEntities" -> Tuple2("advanced/EntityRelatedEntities.txt", Seq("EntityId:long", "EntityType:string", "RelatedEntityId:long", "RelatedEntityType:string", "RelatedType:int", "Score:float")),
     "FieldOfStudyChildren" -> Tuple2("advanced/FieldOfStudyChildren.txt", Seq("FieldOfStudyId:long", "ChildFieldOfStudyId:long")),
     "FieldOfStudyExtendedAttributes" -> Tuple2("advanced/FieldOfStudyExtendedAttributes.txt", Seq("FieldOfStudyId:long", "AttributeType:int", "AttributeValue:string")),
     "FieldsOfStudy" -> Tuple2("advanced/FieldsOfStudy.txt", Seq("FieldOfStudyId:long", "Rank:uint", "NormalizedName:string", "DisplayName:string", "MainType:string", "Level:int", "PaperCount:long", "PaperFamilyCount:long", "CitationCount:long", "CreatedDate:DateTime")),
-    "Journals" -> Tuple2("mag/Journals.txt", Seq("JournalId:long", "Rank:uint", "NormalizedName:string", "DisplayName:string", "Issn:string", "Publisher:string", "Webpage:string", "PaperCount:long", "PaperFamilyCount:long" ,"CitationCount:long", "CreatedDate:DateTime")),
+    "Journals" -> Tuple2("mag/Journals.txt", Seq("JournalId:long", "Rank:uint", "NormalizedName:string", "DisplayName:string", "Issn:string", "Publisher:string", "Webpage:string", "PaperCount:long", "PaperFamilyCount:long", "CitationCount:long", "CreatedDate:DateTime")),
     "PaperAbstractsInvertedIndex" -> Tuple2("nlp/PaperAbstractsInvertedIndex.txt.*", Seq("PaperId:long", "IndexedAbstract:string")),
     "PaperAuthorAffiliations" -> Tuple2("mag/PaperAuthorAffiliations.txt", Seq("PaperId:long", "AuthorId:long", "AffiliationId:long?", "AuthorSequenceNumber:uint", "OriginalAuthor:string", "OriginalAffiliation:string")),
     "PaperCitationContexts" -> Tuple2("nlp/PaperCitationContexts.txt", Seq("PaperId:long", "PaperReferenceId:long", "CitationContext:string")),
@@ -75,7 +75,6 @@ object SparkImportMagIntoDataset {
         .master(parser.get("master")).getOrCreate()
 
 
-
     stream.foreach { case (k, v) =>
       val s: StructType = getSchema(k)
       val df = spark.read

dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/mag/SparkProcessMAG.scala

@@ -5,22 +5,19 @@ import eu.dnetlib.dhp.schema.oaf.Publication
 import eu.dnetlib.doiboost.DoiBoostMappingUtil
 import org.apache.commons.io.IOUtils
 import org.apache.spark.SparkConf
-import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.functions.{col, collect_list, struct}
-import org.apache.spark.sql.functions._
 import org.apache.spark.sql._
 import org.slf4j.{Logger, LoggerFactory}
-
 import scala.collection.JavaConverters._
-
 object SparkProcessMAG {
 
-  def getDistinctResults (d:Dataset[MagPapers]):Dataset[MagPapers]={
+  def getDistinctResults(d: Dataset[MagPapers]): Dataset[MagPapers] = {
     d.where(col("Doi").isNotNull)
       .groupByKey(mp => DoiBoostMappingUtil.normalizeDoi(mp.Doi))(Encoders.STRING)
-      .reduceGroups((p1:MagPapers,p2:MagPapers) => ConversionUtil.choiceLatestMagArtitcle(p1,p2))
+      .reduceGroups((p1: MagPapers, p2: MagPapers) => ConversionUtil.choiceLatestMagArtitcle(p1, p2))
       .map(_._2)(Encoders.product[MagPapers])
       .map(mp => {
-        new MagPapers(mp.PaperId, mp.Rank, DoiBoostMappingUtil.normalizeDoi(mp.Doi),
+        MagPapers(mp.PaperId, mp.Rank, DoiBoostMappingUtil.normalizeDoi(mp.Doi),
           mp.DocType, mp.PaperTitle, mp.OriginalTitle,
           mp.BookTitle, mp.Year, mp.Date, mp.Publisher: String,
           mp.JournalId, mp.ConferenceSeriesId, mp.ConferenceInstanceId,
@@ -98,13 +95,13 @@ object SparkProcessMAG {
 
     var magPubs: Dataset[(String, Publication)] =
       spark.read.load(s"$workingPath/merge_step_2").as[Publication]
-      .map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p)).as[(String, Publication)]
+        .map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p)).as[(String, Publication)]
 
 
     val conference = spark.read.load(s"$sourcePath/ConferenceInstances")
-      .select($"ConferenceInstanceId".as("ci"), $"DisplayName", $"Location", $"StartDate",$"EndDate" )
+      .select($"ConferenceInstanceId".as("ci"), $"DisplayName", $"Location", $"StartDate", $"EndDate")
     val conferenceInstance = conference.joinWith(papers, papers("ConferenceInstanceId").equalTo(conference("ci")))
-      .select($"_1.ci", $"_1.DisplayName", $"_1.Location", $"_1.StartDate",$"_1.EndDate", $"_2.PaperId").as[MagConferenceInstance]
+      .select($"_1.ci", $"_1.DisplayName", $"_1.Location", $"_1.StartDate", $"_1.EndDate", $"_2.PaperId").as[MagConferenceInstance]
 
 
     magPubs.joinWith(conferenceInstance, col("_1").equalTo(conferenceInstance("PaperId")), "left")
@@ -122,7 +119,7 @@ object SparkProcessMAG {
 
     magPubs.joinWith(paperAbstract, col("_1").equalTo(paperAbstract("PaperId")), "left")
       .map(item => ConversionUtil.updatePubsWithDescription(item)
-    ).write.mode(SaveMode.Overwrite).save(s"$workingPath/merge_step_4")
+      ).write.mode(SaveMode.Overwrite).save(s"$workingPath/merge_step_4")
 
 
     logger.info("Phase 7) Enrich Publication with FieldOfStudy")
@@ -148,11 +145,10 @@ object SparkProcessMAG {
     spark.read.load(s"$workingPath/mag_publication").as[Publication]
       .filter(p => p.getId != null)
       .groupByKey(p => p.getId)
-      .reduceGroups((a:Publication, b:Publication) => ConversionUtil.mergePublication(a,b))
+      .reduceGroups((a: Publication, b: Publication) => ConversionUtil.mergePublication(a, b))
       .map(_._2)
       .write.mode(SaveMode.Overwrite).save(s"$targetPath/magPublication")
 
 
-
   }
 }

dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/orcid/ORCIDToOAF.scala

@@ -4,17 +4,16 @@ import com.fasterxml.jackson.databind.ObjectMapper
 import eu.dnetlib.dhp.schema.common.ModelConstants
 import eu.dnetlib.dhp.schema.oaf.utils.IdentifierFactory
 import eu.dnetlib.dhp.schema.oaf.{Author, DataInfo, Publication}
-import eu.dnetlib.dhp.schema.orcid.{AuthorData, OrcidDOI}
 import eu.dnetlib.doiboost.DoiBoostMappingUtil
 import eu.dnetlib.doiboost.DoiBoostMappingUtil.{createSP, generateDataInfo}
 import org.apache.commons.lang.StringUtils
-import org.slf4j.{Logger, LoggerFactory}
-
-import scala.collection.JavaConverters._
 import org.json4s
 import org.json4s.DefaultFormats
 import org.json4s.JsonAST._
 import org.json4s.jackson.JsonMethods._
+import org.slf4j.{Logger, LoggerFactory}
+
+import scala.collection.JavaConverters._
 
 
 case class ORCIDItem(doi:String, authors:List[OrcidAuthor]){}

dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/orcid/SparkConvertORCIDToOAF.scala

@@ -11,10 +11,10 @@ object SparkConvertORCIDToOAF {
   val logger: Logger = LoggerFactory.getLogger(SparkConvertORCIDToOAF.getClass)
 
 
-  def run(spark:SparkSession, workingPath:String, targetPath:String) :Unit = {
+  def run(spark: SparkSession, workingPath: String, targetPath: String): Unit = {
     implicit val mapEncoderPubs: Encoder[Publication] = Encoders.kryo[Publication]
     import spark.implicits._
-    val dataset: Dataset[ORCIDItem] =spark.read.load(s"$workingPath/orcidworksWithAuthor").as[ORCIDItem]
+    val dataset: Dataset[ORCIDItem] = spark.read.load(s"$workingPath/orcidworksWithAuthor").as[ORCIDItem]
 
     logger.info("Converting ORCID to OAF")
     dataset.map(o => ORCIDToOAF.convertTOOAF(o)).write.mode(SaveMode.Overwrite).save(targetPath)
@@ -35,7 +35,7 @@ object SparkConvertORCIDToOAF {
     val workingPath = parser.get("workingPath")
     val targetPath = parser.get("targetPath")
 
-   run(spark,workingPath, targetPath)
+    run(spark, workingPath, targetPath)
 
   }
 

dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/orcid/SparkPreprocessORCID.scala

@@ -1,48 +1,45 @@
 package eu.dnetlib.doiboost.orcid
 
-import com.fasterxml.jackson.databind.{DeserializationFeature, ObjectMapper}
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
-import eu.dnetlib.dhp.oa.merge.AuthorMerger
 import eu.dnetlib.dhp.schema.oaf.Publication
-import eu.dnetlib.dhp.schema.orcid.OrcidDOI
 import org.apache.commons.io.IOUtils
 import org.apache.spark.SparkConf
 import org.apache.spark.rdd.RDD
-import org.apache.spark.sql.functions._
+import org.apache.spark.sql.functions.{col, collect_list}
-import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
+import org.apache.spark.sql._
 import org.slf4j.{Logger, LoggerFactory}
 
 object SparkPreprocessORCID {
   val logger: Logger = LoggerFactory.getLogger(SparkConvertORCIDToOAF.getClass)
 
-    def fixORCIDItem(item :ORCIDItem):ORCIDItem = {
+  def fixORCIDItem(item: ORCIDItem): ORCIDItem = {
-      ORCIDItem(item.doi, item.authors.groupBy(_.oid).map(_._2.head).toList)
+    ORCIDItem(item.doi, item.authors.groupBy(_.oid).map(_._2.head).toList)
 
   }
 
 
-  def run(spark:SparkSession,sourcePath:String,workingPath:String):Unit = {
+  def run(spark: SparkSession, sourcePath: String, workingPath: String): Unit = {
     import spark.implicits._
     implicit val mapEncoderPubs: Encoder[Publication] = Encoders.kryo[Publication]
 
-    val inputRDD:RDD[OrcidAuthor]  = spark.sparkContext.textFile(s"$sourcePath/authors").map(s => ORCIDToOAF.convertORCIDAuthor(s)).filter(s => s!= null).filter(s => ORCIDToOAF.authorValid(s))
+    val inputRDD: RDD[OrcidAuthor] = spark.sparkContext.textFile(s"$sourcePath/authors").map(s => ORCIDToOAF.convertORCIDAuthor(s)).filter(s => s != null).filter(s => ORCIDToOAF.authorValid(s))
 
     spark.createDataset(inputRDD).as[OrcidAuthor].write.mode(SaveMode.Overwrite).save(s"$workingPath/author")
 
-    val res = spark.sparkContext.textFile(s"$sourcePath/works").flatMap(s => ORCIDToOAF.extractDOIWorks(s)).filter(s => s!= null)
+    val res = spark.sparkContext.textFile(s"$sourcePath/works").flatMap(s => ORCIDToOAF.extractDOIWorks(s)).filter(s => s != null)
 
     spark.createDataset(res).as[OrcidWork].write.mode(SaveMode.Overwrite).save(s"$workingPath/works")
 
-    val authors :Dataset[OrcidAuthor] = spark.read.load(s"$workingPath/author").as[OrcidAuthor]
+    val authors: Dataset[OrcidAuthor] = spark.read.load(s"$workingPath/author").as[OrcidAuthor]
 
-    val works :Dataset[OrcidWork] = spark.read.load(s"$workingPath/works").as[OrcidWork]
+    val works: Dataset[OrcidWork] = spark.read.load(s"$workingPath/works").as[OrcidWork]
 
     works.joinWith(authors, authors("oid").equalTo(works("oid")))
-      .map(i =>{
+      .map(i => {
         val doi = i._1.doi
         val author = i._2
-      (doi, author)
+        (doi, author)
-    }).groupBy(col("_1").alias("doi"))
+      }).groupBy(col("_1").alias("doi"))
       .agg(collect_list(col("_2")).alias("authors")).as[ORCIDItem]
       .map(s => fixORCIDItem(s))
       .write.mode(SaveMode.Overwrite).save(s"$workingPath/orcidworksWithAuthor")

dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/uw/SparkMapUnpayWallToOAF.scala

@@ -1,16 +1,14 @@
 package eu.dnetlib.doiboost.uw
 
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
-
 import eu.dnetlib.dhp.schema.oaf.Publication
 import eu.dnetlib.doiboost.crossref.SparkMapDumpIntoOAF
 import org.apache.commons.io.IOUtils
 import org.apache.spark.SparkConf
 import org.apache.spark.rdd.RDD
-import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
+import org.apache.spark.sql._
 import org.slf4j.{Logger, LoggerFactory}
 
-
 object SparkMapUnpayWallToOAF {
 
   def main(args: Array[String]): Unit = {
@@ -32,11 +30,11 @@ object SparkMapUnpayWallToOAF {
 
     val sourcePath = parser.get("sourcePath")
     val targetPath = parser.get("targetPath")
-    val inputRDD:RDD[String] = spark.sparkContext.textFile(s"$sourcePath")
+    val inputRDD: RDD[String] = spark.sparkContext.textFile(s"$sourcePath")
 
     logger.info("Converting UnpayWall to OAF")
 
-    val d:Dataset[Publication] = spark.createDataset(inputRDD.map(UnpayWallToOAF.convertToOAF).filter(p=>p!=null)).as[Publication]
+    val d: Dataset[Publication] = spark.createDataset(inputRDD.map(UnpayWallToOAF.convertToOAF).filter(p => p != null)).as[Publication]
     d.write.mode(SaveMode.Overwrite).save(targetPath)
   }
 

dhp-workflows/dhp-doiboost/src/main/scala/eu/dnetlib/doiboost/uw/UnpayWallToOAF.scala

@@ -4,14 +4,13 @@ import eu.dnetlib.dhp.schema.common.ModelConstants
 import eu.dnetlib.dhp.schema.oaf.utils.IdentifierFactory
 import eu.dnetlib.dhp.schema.oaf.{AccessRight, Instance, OpenAccessRoute, Publication}
 import eu.dnetlib.doiboost.DoiBoostMappingUtil
+import eu.dnetlib.doiboost.DoiBoostMappingUtil._
 import org.json4s
 import org.json4s.DefaultFormats
 import org.json4s.jackson.JsonMethods.parse
 import org.slf4j.{Logger, LoggerFactory}
 
 import scala.collection.JavaConverters._
-import eu.dnetlib.doiboost.DoiBoostMappingUtil._
-import eu.dnetlib.doiboost.uw.UnpayWallToOAF.get_unpaywall_color
 
 
 

dhp-workflows/dhp-doiboost/src/test/java/eu/dnetlib/dhp/doiboost/DoiBoostHostedByMapTest.scala

@@ -1,70 +0,0 @@
-package eu.dnetlib.dhp.doiboost
-
-import eu.dnetlib.dhp.schema.oaf.{Publication, Dataset => OafDataset}
-import eu.dnetlib.doiboost.{DoiBoostMappingUtil, HostedByItemType}
-import eu.dnetlib.doiboost.SparkGenerateDoiBoost.getClass
-import eu.dnetlib.doiboost.mag.ConversionUtil
-import eu.dnetlib.doiboost.orcid.ORCIDElement
-import org.apache.spark.SparkConf
-import org.apache.spark.rdd.RDD
-import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
-import org.codehaus.jackson.map.{ObjectMapper, SerializationConfig}
-import org.junit.jupiter.api.Test
-
-import scala.io.Source
-
-class DoiBoostHostedByMapTest {
-
-
-
-//  @Test
-//  def testMerge():Unit = {
-//    val conf: SparkConf = new SparkConf()
-//    val spark: SparkSession =
-//      SparkSession
-//        .builder()
-//        .config(conf)
-//        .appName(getClass.getSimpleName)
-//        .master("local[*]").getOrCreate()
-//
-//
-//
-//    implicit val mapEncoderPub: Encoder[Publication] = Encoders.kryo[Publication]
-//    implicit val mapEncoderDataset: Encoder[OafDataset] = Encoders.kryo[OafDataset]
-//    implicit val tupleForJoinEncoder: Encoder[(String, Publication)] = Encoders.tuple(Encoders.STRING, mapEncoderPub)
-//
-//
-//    import spark.implicits._
-//    val dataset:RDD[String]= spark.sparkContext.textFile("/home/sandro/Downloads/hbMap.gz")
-//
-//
-//    val hbMap:Dataset[(String, HostedByItemType)] =spark.createDataset(dataset.map(DoiBoostMappingUtil.toHostedByItem))
-//
-//
-//    hbMap.show()
-//
-//
-//
-//
-//
-//
-//
-//
-//
-//
-//  }
-
-
-  @Test
-  def idDSGeneration():Unit = {
-    val s ="doajarticles::0066-782X"
-
-
-
-    println(DoiBoostMappingUtil.generateDSId(s))
-
-
-  }
-
-
-}

dhp-workflows/dhp-doiboost/src/test/scala/eu/dnetlib/dhp/doiboost/DoiBoostHostedByMapTest.scala

@@ -0,0 +1,20 @@
+package eu.dnetlib.dhp.doiboost
+
+import eu.dnetlib.doiboost.DoiBoostMappingUtil
+import org.junit.jupiter.api.Test
+
+class DoiBoostHostedByMapTest {
+
+  @Test
+  def idDSGeneration():Unit = {
+    val s ="doajarticles::0066-782X"
+
+
+
+    println(DoiBoostMappingUtil.generateDSId(s))
+
+
+  }
+
+
+}

dhp-workflows/dhp-doiboost/src/test/scala/eu/dnetlib/dhp/doiboost/crossref/CrossrefMappingTest.scala

@@ -1,7 +1,8 @@
-package eu.dnetlib.doiboost.crossref
+package eu.dnetlib.dhp.doiboost.crossref
 
 import eu.dnetlib.dhp.schema.oaf._
 import eu.dnetlib.dhp.utils.DHPUtils
+import eu.dnetlib.doiboost.crossref.Crossref2Oaf
 import org.codehaus.jackson.map.{ObjectMapper, SerializationConfig}
 import org.junit.jupiter.api.Assertions._
 import org.junit.jupiter.api.Test
@@ -21,9 +22,9 @@ class CrossrefMappingTest {
 
   @Test
   def testFunderRelationshipsMapping(): Unit = {
-    val template = Source.fromInputStream(getClass.getResourceAsStream("article_funder_template.json")).mkString
+    val template = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/article_funder_template.json")).mkString
-    val funder_doi = Source.fromInputStream(getClass.getResourceAsStream("funder_doi")).mkString
+    val funder_doi = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/funder_doi")).mkString
-    val funder_name = Source.fromInputStream(getClass.getResourceAsStream("funder_doi")).mkString
+    val funder_name = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/funder_doi")).mkString
 
 
     for (line <- funder_doi.lines) {
@@ -72,7 +73,7 @@ class CrossrefMappingTest {
 
   @Test
   def testOrcidID() :Unit = {
-    val json = Source.fromInputStream(getClass.getResourceAsStream("orcid_data.json")).mkString
+    val json = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/orcid_data.json")).mkString
 
 
     assertNotNull(json)
@@ -93,7 +94,7 @@ class CrossrefMappingTest {
 
   @Test
   def testEmptyTitle() :Unit = {
-    val json = Source.fromInputStream(getClass.getResourceAsStream("empty_title.json")).mkString
+    val json = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/empty_title.json")).mkString
 
 
     assertNotNull(json)
@@ -115,7 +116,7 @@ class CrossrefMappingTest {
 
   @Test
   def testPeerReviewed(): Unit = {
-    val json = Source.fromInputStream(getClass.getResourceAsStream("prwTest.json")).mkString
+    val json = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/prwTest.json")).mkString
     mapper.getSerializationConfig.enable(SerializationConfig.Feature.INDENT_OUTPUT)
 
     assertNotNull(json)
@@ -156,7 +157,7 @@ class CrossrefMappingTest {
 
   @Test
   def testJournalRelation(): Unit = {
-    val json = Source.fromInputStream(getClass.getResourceAsStream("awardTest.json")).mkString
+    val json = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/awardTest.json")).mkString
     assertNotNull(json)
 
     assertFalse(json.isEmpty)
@@ -177,7 +178,7 @@ class CrossrefMappingTest {
 
   @Test
   def testConvertBookFromCrossRef2Oaf(): Unit = {
-    val json = Source.fromInputStream(getClass.getResourceAsStream("book.json")).mkString
+    val json = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/book.json")).mkString
     assertNotNull(json)
 
     assertFalse(json.isEmpty);
@@ -233,7 +234,7 @@ class CrossrefMappingTest {
 
   @Test
   def testConvertPreprintFromCrossRef2Oaf(): Unit = {
-    val json = Source.fromInputStream(getClass.getResourceAsStream("preprint.json")).mkString
+    val json = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/preprint.json")).mkString
     assertNotNull(json)
 
     assertFalse(json.isEmpty);
@@ -291,7 +292,7 @@ class CrossrefMappingTest {
 
   @Test
   def testConvertDatasetFromCrossRef2Oaf(): Unit = {
-    val json = Source.fromInputStream(getClass.getResourceAsStream("dataset.json")).mkString
+    val json = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/dataset.json")).mkString
     assertNotNull(json)
 
     assertFalse(json.isEmpty);
@@ -332,7 +333,7 @@ class CrossrefMappingTest {
 
   @Test
   def testConvertArticleFromCrossRef2Oaf(): Unit = {
-    val json = Source.fromInputStream(getClass.getResourceAsStream("article.json")).mkString
+    val json = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/article.json")).mkString
     assertNotNull(json)
 
     assertFalse(json.isEmpty);
@@ -400,7 +401,7 @@ class CrossrefMappingTest {
   @Test
   def testSetDateOfAcceptanceCrossRef2Oaf(): Unit = {
 
-    val json = Source.fromInputStream(getClass.getResourceAsStream("dump_file.json")).mkString
+    val json = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/dump_file.json")).mkString
     assertNotNull(json)
 
     assertFalse(json.isEmpty);
@@ -415,55 +416,12 @@ class CrossrefMappingTest {
     assert(items.size == 1)
     val result: Result = items.head.asInstanceOf[Publication]
     assertNotNull(result)
-
     logger.info(mapper.writeValueAsString(result));
-
-//    assertNotNull(result.getDataInfo, "Datainfo test not null Failed");
-//    assertNotNull(
-//      result.getDataInfo.getProvenanceaction,
-//      "DataInfo/Provenance test not null Failed");
-//    assertFalse(
-//      result.getDataInfo.getProvenanceaction.getClassid.isEmpty,
-//      "DataInfo/Provenance/classId test not null Failed");
-//    assertFalse(
-//      result.getDataInfo.getProvenanceaction.getClassname.isEmpty,
-//      "DataInfo/Provenance/className test not null Failed");
-//    assertFalse(
-//      result.getDataInfo.getProvenanceaction.getSchemeid.isEmpty,
-//      "DataInfo/Provenance/SchemeId test not null Failed");
-//    assertFalse(
-//      result.getDataInfo.getProvenanceaction.getSchemename.isEmpty,
-//      "DataInfo/Provenance/SchemeName test not null Failed");
-//
-//    assertNotNull(result.getCollectedfrom, "CollectedFrom test not null Failed");
-//    assertFalse(result.getCollectedfrom.isEmpty);
-//
-//    val collectedFromList = result.getCollectedfrom.asScala
-//    assert(collectedFromList.exists(c => c.getKey.equalsIgnoreCase("10|openaire____::081b82f96300b6a6e3d282bad31cb6e2")), "Wrong collected from assertion")
-//
-//    assert(collectedFromList.exists(c => c.getValue.equalsIgnoreCase("crossref")), "Wrong collected from assertion")
-//
-//
-//    val relevantDates = result.getRelevantdate.asScala
-//
-//    assert(relevantDates.exists(d => d.getQualifier.getClassid.equalsIgnoreCase("created")), "Missing relevant date of type created")
-//
-//    val rels = resultList.filter(p => p.isInstanceOf[Relation]).asInstanceOf[List[Relation]]
-//    assertFalse(rels.isEmpty)
-//    rels.foreach(relation => {
-//      assertNotNull(relation)
-//      assertFalse(relation.getSource.isEmpty)
-//      assertFalse(relation.getTarget.isEmpty)
-//      assertFalse(relation.getRelClass.isEmpty)
-//      assertFalse(relation.getRelType.isEmpty)
-//      assertFalse(relation.getSubRelType.isEmpty)
-//
-//    })
   }
 
   @Test
   def testNormalizeDOI(): Unit = {
-    val template = Source.fromInputStream(getClass.getResourceAsStream("article_funder_template.json")).mkString
+    val template = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/article_funder_template.json")).mkString
     val line :String = "\"funder\": [{\"name\": \"Wellcome Trust Masters Fellowship\",\"award\": [\"090633\"]}],"
     val json = template.replace("%s", line)
     val resultList: List[Oaf] = Crossref2Oaf.convert(json)
@@ -479,7 +437,7 @@ class CrossrefMappingTest {
 
   @Test
   def testNormalizeDOI2(): Unit = {
-    val template = Source.fromInputStream(getClass.getResourceAsStream("article.json")).mkString
+    val template = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/article.json")).mkString
 
     val resultList: List[Oaf] = Crossref2Oaf.convert(template)
     assertTrue(resultList.nonEmpty)
@@ -494,7 +452,7 @@ class CrossrefMappingTest {
 
   @Test
   def testLicenseVorClosed() :Unit = {
-    val json = Source.fromInputStream(getClass.getResourceAsStream("publication_license_vor.json")).mkString
+    val json = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/publication_license_vor.json")).mkString
 
 
     assertNotNull(json)
@@ -521,7 +479,7 @@ class CrossrefMappingTest {
 
   @Test
   def testLicenseOpen() :Unit = {
-    val json = Source.fromInputStream(getClass.getResourceAsStream("publication_license_open.json")).mkString
+    val json = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/publication_license_open.json")).mkString
 
 
     assertNotNull(json)
@@ -544,7 +502,7 @@ class CrossrefMappingTest {
 
   @Test
   def testLicenseEmbargoOpen() :Unit = {
-    val json = Source.fromInputStream(getClass.getResourceAsStream("publication_license_embargo_open.json")).mkString
+    val json = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/publication_license_embargo_open.json")).mkString
 
 
     assertNotNull(json)
@@ -567,7 +525,7 @@ class CrossrefMappingTest {
 
   @Test
   def testLicenseEmbargo() :Unit = {
-    val json = Source.fromInputStream(getClass.getResourceAsStream("publication_license_embargo.json")).mkString
+    val json = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/publication_license_embargo.json")).mkString
 
 
     assertNotNull(json)
@@ -591,7 +549,7 @@ class CrossrefMappingTest {
 
   @Test
   def testLicenseEmbargoDateTime() :Unit = {
-    val json = Source.fromInputStream(getClass.getResourceAsStream("publication_license_embargo_datetime.json")).mkString
+    val json = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/publication_license_embargo_datetime.json")).mkString
 
 
     assertNotNull(json)
@@ -614,7 +572,7 @@ class CrossrefMappingTest {
 
   @Test
   def testMultipleURLs() :Unit = {
-    val json = Source.fromInputStream(getClass.getResourceAsStream("multiple_urls.json")).mkString
+    val json = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/crossref/multiple_urls.json")).mkString
 
 
     assertNotNull(json)

dhp-workflows/dhp-doiboost/src/test/scala/eu/dnetlib/dhp/doiboost/mag/MAGMappingTest.scala

@@ -1,11 +1,12 @@
-package eu.dnetlib.doiboost.mag
+package eu.dnetlib.dhp.doiboost.mag
 
+import eu.dnetlib.doiboost.mag.{ConversionUtil, MagPapers, SparkProcessMAG}
 import org.apache.spark.SparkConf
 import org.apache.spark.sql.{Dataset, SparkSession}
 import org.codehaus.jackson.map.ObjectMapper
+import org.json4s.DefaultFormats
 import org.junit.jupiter.api.Assertions._
 import org.junit.jupiter.api.Test
-import org.json4s.DefaultFormats
 import org.slf4j.{Logger, LoggerFactory}
 
 import java.sql.Timestamp
@@ -47,7 +48,7 @@ class MAGMappingTest {
 
   @Test
   def buildInvertedIndexTest(): Unit = {
-    val json_input = Source.fromInputStream(getClass.getResourceAsStream("invertedIndex.json")).mkString
+    val json_input = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/mag/invertedIndex.json")).mkString
     val description = ConversionUtil.convertInvertedIndexString(json_input)
     assertNotNull(description)
     assertTrue(description.nonEmpty)
@@ -71,7 +72,7 @@ class MAGMappingTest {
         .appName(getClass.getSimpleName)
         .config(conf)
         .getOrCreate()
-    val path = getClass.getResource("magPapers.json").getPath
+    val path = getClass.getResource("/eu/dnetlib/doiboost/mag/magPapers.json").getPath
 
     import org.apache.spark.sql.Encoders
     val schema = Encoders.product[MagPapers].schema
@@ -101,7 +102,7 @@ class MAGMappingTest {
         .appName(getClass.getSimpleName)
         .config(conf)
         .getOrCreate()
-    val path = getClass.getResource("duplicatedMagPapers.json").getPath
+    val path = getClass.getResource("/eu/dnetlib/doiboost/mag/duplicatedMagPapers.json").getPath
 
     import org.apache.spark.sql.Encoders
     val schema = Encoders.product[MagPapers].schema

dhp-workflows/dhp-doiboost/src/test/scala/eu/dnetlib/dhp/doiboost/orcid/MappingORCIDToOAFTest.scala

@@ -1,7 +1,8 @@
-package eu.dnetlib.doiboost.orcid
+package eu.dnetlib.dhp.doiboost.orcid
 
 import com.fasterxml.jackson.databind.ObjectMapper
 import eu.dnetlib.dhp.schema.oaf.Publication
+import eu.dnetlib.doiboost.orcid._
 import org.apache.spark.SparkConf
 import org.apache.spark.sql.{Dataset, Encoder, Encoders, SparkSession}
 import org.junit.jupiter.api.Assertions._
@@ -10,9 +11,8 @@ import org.junit.jupiter.api.io.TempDir
 import org.slf4j.{Logger, LoggerFactory}
 
 import java.nio.file.Path
-import scala.io.Source
-
 import scala.collection.JavaConversions._
+import scala.io.Source
 
 class MappingORCIDToOAFTest {
   val logger: Logger = LoggerFactory.getLogger(ORCIDToOAF.getClass)
@@ -20,7 +20,7 @@ class MappingORCIDToOAFTest {
 
   @Test
   def testExtractData():Unit ={
-    val json = Source.fromInputStream(getClass.getResourceAsStream("dataOutput")).mkString
+    val json = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/orcid/dataOutput")).mkString
     assertNotNull(json)
     assertFalse(json.isEmpty)
     json.lines.foreach(s => {

dhp-workflows/dhp-doiboost/src/test/scala/eu/dnetlib/dhp/doiboost/uw/UnpayWallMappingTest.scala

@@ -1,13 +1,13 @@
-package eu.dnetlib.doiboost.uw
+package eu.dnetlib.dhp.doiboost.uw
-
 
 import com.fasterxml.jackson.databind.ObjectMapper
 import eu.dnetlib.dhp.schema.oaf.OpenAccessRoute
+import eu.dnetlib.doiboost.uw.UnpayWallToOAF
+import org.junit.jupiter.api.Assertions._
 import org.junit.jupiter.api.Test
+import org.slf4j.{Logger, LoggerFactory}
 
 import scala.io.Source
-import org.junit.jupiter.api.Assertions._
-import org.slf4j.{Logger, LoggerFactory}
 
 class UnpayWallMappingTest {
 
@@ -18,7 +18,7 @@ class UnpayWallMappingTest {
   @Test
   def testMappingToOAF():Unit ={
 
-    val Ilist = Source.fromInputStream(getClass.getResourceAsStream("input.json")).mkString
+    val Ilist = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/doiboost/uw/input.json")).mkString
 
     var i:Int = 0
     for (line <-Ilist.lines) {

dhp-workflows/dhp-graph-mapper/src/main/scala/eu/dnetlib/dhp/oa/graph/hostedbymap/Aggregators.scala

@@ -1,8 +1,8 @@
 package eu.dnetlib.dhp.oa.graph.hostedbymap
 
 import eu.dnetlib.dhp.oa.graph.hostedbymap.model.EntityInfo
-import org.apache.spark.sql.{Dataset, Encoder, Encoders, TypedColumn}
 import org.apache.spark.sql.expressions.Aggregator
+import org.apache.spark.sql.{Dataset, Encoder, Encoders, TypedColumn}
 
 
 case class HostedByItemType(id: String, officialname: String, issn: String, eissn: String, lissn: String, openAccess: Boolean) {}

dhp-workflows/dhp-graph-mapper/src/main/scala/eu/dnetlib/dhp/oa/graph/hostedbymap/SparkApplyHostedByMapToDatasource.scala

@@ -2,13 +2,12 @@ package eu.dnetlib.dhp.oa.graph.hostedbymap
 
 import com.fasterxml.jackson.databind.ObjectMapper
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
-import eu.dnetlib.dhp.oa.graph.hostedbymap.SparkApplyHostedByMapToResult.{applyHBtoPubs, getClass}
 import eu.dnetlib.dhp.oa.graph.hostedbymap.model.EntityInfo
 import eu.dnetlib.dhp.schema.common.ModelConstants
-import eu.dnetlib.dhp.schema.oaf.{Datasource, Publication}
+import eu.dnetlib.dhp.schema.oaf.Datasource
 import org.apache.commons.io.IOUtils
 import org.apache.spark.SparkConf
-import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
+import org.apache.spark.sql._
 import org.json4s.DefaultFormats
 import org.slf4j.{Logger, LoggerFactory}
 
@@ -52,18 +51,18 @@ object SparkApplyHostedByMapToDatasource {
 
     val mapper = new ObjectMapper()
 
-    val dats : Dataset[Datasource] = spark.read.textFile(graphPath + "/datasource")
+    val dats: Dataset[Datasource] = spark.read.textFile(graphPath + "/datasource")
       .map(r => mapper.readValue(r, classOf[Datasource]))
 
-    val pinfo : Dataset[EntityInfo] = Aggregators.datasourceToSingleId( spark.read.textFile(preparedInfoPath)
+    val pinfo: Dataset[EntityInfo] = Aggregators.datasourceToSingleId(spark.read.textFile(preparedInfoPath)
       .map(ei => mapper.readValue(ei, classOf[EntityInfo])))
 
-    applyHBtoDats(pinfo, dats).write.mode(SaveMode.Overwrite).option("compression","gzip").json(outputPath)
+    applyHBtoDats(pinfo, dats).write.mode(SaveMode.Overwrite).option("compression", "gzip").json(outputPath)
 
     spark.read.textFile(outputPath)
       .write
       .mode(SaveMode.Overwrite)
-      .option("compression","gzip")
+      .option("compression", "gzip")
       .text(graphPath + "/datasource")
   }
 

dhp-workflows/dhp-graph-mapper/src/main/scala/eu/dnetlib/dhp/oa/graph/hostedbymap/SparkApplyHostedByMapToResult.scala

@@ -5,16 +5,14 @@ import eu.dnetlib.dhp.application.ArgumentApplicationParser
 import eu.dnetlib.dhp.oa.graph.hostedbymap.model.EntityInfo
 import eu.dnetlib.dhp.schema.common.ModelConstants
 import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils
-import eu.dnetlib.dhp.schema.oaf.{Datasource, Instance, OpenAccessRoute, Publication}
+import eu.dnetlib.dhp.schema.oaf.{Instance, OpenAccessRoute, Publication}
 import org.apache.commons.io.IOUtils
 import org.apache.spark.SparkConf
-import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
+import org.apache.spark.sql._
 import org.json4s.DefaultFormats
 import org.slf4j.{Logger, LoggerFactory}
-
 import scala.collection.JavaConverters._
 
-
 object SparkApplyHostedByMapToResult {
 
   def applyHBtoPubs(join: Dataset[EntityInfo], pubs: Dataset[Publication]) = {
@@ -25,7 +23,7 @@ object SparkApplyHostedByMapToResult {
           val ei: EntityInfo = t2._2
           val i = p.getInstance().asScala
           if (i.size == 1) {
-            val inst: Instance = i(0)
+            val inst: Instance = i.head
             inst.getHostedby.setKey(ei.getHostedById)
             inst.getHostedby.setValue(ei.getName)
             if (ei.getOpenAccess) {
@@ -39,6 +37,7 @@ object SparkApplyHostedByMapToResult {
         p
       })(Encoders.bean(classOf[Publication]))
   }
+
   def main(args: Array[String]): Unit = {
 
 
@@ -67,18 +66,18 @@ object SparkApplyHostedByMapToResult {
     implicit val mapEncoderEinfo: Encoder[EntityInfo] = Encoders.bean(classOf[EntityInfo])
     val mapper = new ObjectMapper()
 
-    val pubs : Dataset[Publication] = spark.read.textFile(graphPath + "/publication")
+    val pubs: Dataset[Publication] = spark.read.textFile(graphPath + "/publication")
       .map(r => mapper.readValue(r, classOf[Publication]))
 
-    val pinfo : Dataset[EntityInfo] = spark.read.textFile(preparedInfoPath)
+    val pinfo: Dataset[EntityInfo] = spark.read.textFile(preparedInfoPath)
-        .map(ei => mapper.readValue(ei, classOf[EntityInfo]))
+      .map(ei => mapper.readValue(ei, classOf[EntityInfo]))
 
-    applyHBtoPubs(pinfo, pubs).write.mode(SaveMode.Overwrite).option("compression","gzip").json(outputPath)
+    applyHBtoPubs(pinfo, pubs).write.mode(SaveMode.Overwrite).option("compression", "gzip").json(outputPath)
 
     spark.read.textFile(outputPath)
       .write
       .mode(SaveMode.Overwrite)
-      .option("compression","gzip")
+      .option("compression", "gzip")
       .text(graphPath + "/publication")
   }
 

dhp-workflows/dhp-graph-mapper/src/main/scala/eu/dnetlib/dhp/oa/graph/hostedbymap/SparkPrepareHostedByInfoToApply.scala

@@ -3,61 +3,58 @@ package eu.dnetlib.dhp.oa.graph.hostedbymap
 import com.fasterxml.jackson.databind.ObjectMapper
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
 import eu.dnetlib.dhp.oa.graph.hostedbymap.model.EntityInfo
-
 import eu.dnetlib.dhp.schema.oaf.{Journal, Publication}
 import org.apache.commons.io.IOUtils
 import org.apache.spark.SparkConf
-import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
+import org.apache.spark.sql._
 import org.json4s
 import org.json4s.DefaultFormats
 import org.json4s.jackson.JsonMethods.parse
 import org.slf4j.{Logger, LoggerFactory}
 
-
-
 object SparkPrepareHostedByInfoToApply {
 
   implicit val mapEncoderPInfo: Encoder[EntityInfo] = Encoders.bean(classOf[EntityInfo])
 
-  def getList(id: String, j: Journal, name: String ) : List[EntityInfo] = {
+  def getList(id: String, j: Journal, name: String): List[EntityInfo] = {
-    var lst:List[EntityInfo] = List()
+    var lst: List[EntityInfo] = List()
 
 
-    if (j.getIssnLinking != null && !j.getIssnLinking.equals("")){
+    if (j.getIssnLinking != null && !j.getIssnLinking.equals("")) {
       lst = EntityInfo.newInstance(id, j.getIssnLinking, name) :: lst
     }
-    if (j.getIssnOnline != null && !j.getIssnOnline.equals("")){
+    if (j.getIssnOnline != null && !j.getIssnOnline.equals("")) {
       lst = EntityInfo.newInstance(id, j.getIssnOnline, name) :: lst
     }
-    if (j.getIssnPrinted != null && !j.getIssnPrinted.equals("")){
+    if (j.getIssnPrinted != null && !j.getIssnPrinted.equals("")) {
       lst = EntityInfo.newInstance(id, j.getIssnPrinted, name) :: lst
     }
     lst
   }
 
-  def prepareResultInfo(spark:SparkSession, publicationPath:String) : Dataset[EntityInfo] = {
+  def prepareResultInfo(spark: SparkSession, publicationPath: String): Dataset[EntityInfo] = {
     implicit val mapEncoderPubs: Encoder[Publication] = Encoders.bean(classOf[Publication])
 
     val mapper = new ObjectMapper()
 
-    val dd : Dataset[Publication] = spark.read.textFile(publicationPath)
+    val dd: Dataset[Publication] = spark.read.textFile(publicationPath)
       .map(r => mapper.readValue(r, classOf[Publication]))
 
-    dd.filter(p => p.getJournal != null ).flatMap(p => getList(p.getId, p.getJournal, ""))
+    dd.filter(p => p.getJournal != null).flatMap(p => getList(p.getId, p.getJournal, ""))
 
   }
 
 
-  def toEntityInfo(input:String): EntityInfo = {
+  def toEntityInfo(input: String): EntityInfo = {
     implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
 
     lazy val json: json4s.JValue = parse(input)
-    val c :Map[String,HostedByItemType] = json.extract[Map[String, HostedByItemType]]
+    val c: Map[String, HostedByItemType] = json.extract[Map[String, HostedByItemType]]
     toEntityItem(c.keys.head, c.values.head)
   }
 
 
-  def toEntityItem(journal_id: String , hbi: HostedByItemType): EntityInfo = {
+  def toEntityItem(journal_id: String, hbi: HostedByItemType): EntityInfo = {
 
     EntityInfo.newInstance(hbi.id, journal_id, hbi.officialname, hbi.openAccess)
 
@@ -67,7 +64,7 @@ object SparkPrepareHostedByInfoToApply {
     Aggregators.resultToSingleId(res.joinWith(hbm, res.col("journalId").equalTo(hbm.col("journalId")), "left")
       .map(t2 => {
         val res: EntityInfo = t2._1
-        if(t2._2 != null ){
+        if (t2._2 != null) {
           val ds = t2._2
           res.setHostedById(ds.getId)
           res.setOpenAccess(ds.getOpenAccess)
@@ -107,10 +104,10 @@ object SparkPrepareHostedByInfoToApply {
 
 
     //STEP1: read the hostedbymap and transform it in EntityInfo
-    val hostedByInfo:Dataset[EntityInfo] = spark.createDataset(spark.sparkContext.textFile(hostedByMapPath)).map(toEntityInfo)
+    val hostedByInfo: Dataset[EntityInfo] = spark.createDataset(spark.sparkContext.textFile(hostedByMapPath)).map(toEntityInfo)
 
-   //STEP2: create association (publication, issn), (publication, eissn), (publication, lissn)
+    //STEP2: create association (publication, issn), (publication, eissn), (publication, lissn)
-    val resultInfoDataset:Dataset[EntityInfo] = prepareResultInfo(spark, graphPath + "/publication")
+    val resultInfoDataset: Dataset[EntityInfo] = prepareResultInfo(spark, graphPath + "/publication")
 
     //STEP3: left join resultInfo with hostedByInfo on journal_id. Reduction of all the results with the same id in just
     //one entry (one result could be associated to issn and eissn and so possivly matching more than once against the map)

dhp-workflows/dhp-graph-mapper/src/main/scala/eu/dnetlib/dhp/oa/graph/hostedbymap/SparkProduceHostedByMap.scala

@@ -1,41 +1,39 @@
 package eu.dnetlib.dhp.oa.graph.hostedbymap
 
+import com.fasterxml.jackson.databind.ObjectMapper
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
 import eu.dnetlib.dhp.oa.graph.hostedbymap.model.{DOAJModel, UnibiGoldModel}
 import eu.dnetlib.dhp.schema.oaf.Datasource
 import org.apache.commons.io.IOUtils
+import org.apache.hadoop.conf.Configuration
+import org.apache.hadoop.fs.{FileSystem, Path}
+import org.apache.hadoop.io.compress.GzipCodec
 import org.apache.spark.SparkConf
-import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
+import org.apache.spark.sql.{Dataset, Encoder, Encoders, SparkSession}
 import org.json4s.DefaultFormats
 import org.slf4j.{Logger, LoggerFactory}
-import com.fasterxml.jackson.databind.ObjectMapper
+
-import org.apache.hadoop.conf.Configuration
-import org.apache.hadoop.fs.FileSystem
-import org.apache.hadoop.fs.Path
 import java.io.PrintWriter
 
-import org.apache.hadoop.io.compress.GzipCodec
-
-
 object SparkProduceHostedByMap {
 
 
   implicit val tupleForJoinEncoder: Encoder[(String, HostedByItemType)] = Encoders.tuple(Encoders.STRING, Encoders.product[HostedByItemType])
 
 
-  def toHostedByItemType(input: ((HostedByInfo, HostedByInfo), HostedByInfo)) : HostedByItemType = {
+  def toHostedByItemType(input: ((HostedByInfo, HostedByInfo), HostedByInfo)): HostedByItemType = {
     val openaire: HostedByInfo = input._1._1
     val doaj: HostedByInfo = input._1._2
     val gold: HostedByInfo = input._2
     val isOpenAccess: Boolean = doaj == null && gold == null
 
     openaire.journal_id match {
-      case Constants.ISSN =>  HostedByItemType(openaire.id, openaire.officialname, openaire.journal_id, "", "", isOpenAccess)
+      case Constants.ISSN => HostedByItemType(openaire.id, openaire.officialname, openaire.journal_id, "", "", isOpenAccess)
-      case Constants.EISSN =>  HostedByItemType(openaire.id, openaire.officialname, "", openaire.journal_id, "", isOpenAccess)
+      case Constants.EISSN => HostedByItemType(openaire.id, openaire.officialname, "", openaire.journal_id, "", isOpenAccess)
-      case Constants.ISSNL =>  HostedByItemType(openaire.id, openaire.officialname, "", "", openaire.journal_id, isOpenAccess)
+      case Constants.ISSNL => HostedByItemType(openaire.id, openaire.officialname, "", "", openaire.journal_id, isOpenAccess)
 
       // catch the default with a variable so you can print it
-      case whoa =>  null
+      case whoa => null
     }
   }
 
@@ -44,7 +42,7 @@ object SparkProduceHostedByMap {
 
     implicit val formats = org.json4s.DefaultFormats
 
-    val map: Map [String, HostedByItemType] = Map (input._1 -> input._2 )
+    val map: Map[String, HostedByItemType] = Map(input._1 -> input._2)
 
     Serialization.write(map)
 
@@ -52,34 +50,33 @@ object SparkProduceHostedByMap {
   }
 
 
-
+  def getHostedByItemType(id: String, officialname: String, issn: String, eissn: String, issnl: String, oa: Boolean): HostedByItemType = {
-  def getHostedByItemType(id:String, officialname: String, issn:String, eissn:String, issnl:String, oa:Boolean): HostedByItemType = {
+    if (issn != null) {
-    if(issn != null){
+      if (eissn != null) {
-      if(eissn != null){
+        if (issnl != null) {
-        if(issnl != null){
+          HostedByItemType(id, officialname, issn, eissn, issnl, oa)
-          HostedByItemType(id, officialname, issn, eissn, issnl  , oa)
+        } else {
-        }else{
+          HostedByItemType(id, officialname, issn, eissn, "", oa)
-          HostedByItemType(id, officialname, issn, eissn, ""  , oa)
         }
-      }else{
+      } else {
-        if(issnl != null){
+        if (issnl != null) {
-          HostedByItemType(id, officialname, issn, "", issnl  , oa)
+          HostedByItemType(id, officialname, issn, "", issnl, oa)
-        }else{
+        } else {
-          HostedByItemType(id, officialname, issn, "", ""  , oa)
+          HostedByItemType(id, officialname, issn, "", "", oa)
         }
       }
-    }else{
+    } else {
-      if(eissn != null){
+      if (eissn != null) {
-        if(issnl != null){
+        if (issnl != null) {
-          HostedByItemType(id, officialname, "", eissn, issnl  , oa)
+          HostedByItemType(id, officialname, "", eissn, issnl, oa)
-        }else{
+        } else {
-          HostedByItemType(id, officialname, "", eissn, ""  , oa)
+          HostedByItemType(id, officialname, "", eissn, "", oa)
         }
-      }else{
+      } else {
-        if(issnl != null){
+        if (issnl != null) {
-          HostedByItemType(id, officialname, "", "", issnl  , oa)
+          HostedByItemType(id, officialname, "", "", issnl, oa)
-        }else{
+        } else {
-          HostedByItemType("", "", "", "", ""  , oa)
+          HostedByItemType("", "", "", "", "", oa)
         }
       }
     }
@@ -90,10 +87,10 @@ object SparkProduceHostedByMap {
 
       return getHostedByItemType(dats.getId, dats.getOfficialname.getValue, dats.getJournal.getIssnPrinted, dats.getJournal.getIssnOnline, dats.getJournal.getIssnLinking, false)
     }
-    HostedByItemType("","","","","",false)
+    HostedByItemType("", "", "", "", "", false)
   }
 
-  def oaHostedByDataset(spark:SparkSession, datasourcePath : String) : Dataset[HostedByItemType] = {
+  def oaHostedByDataset(spark: SparkSession, datasourcePath: String): Dataset[HostedByItemType] = {
 
     import spark.implicits._
 
@@ -102,10 +99,10 @@ object SparkProduceHostedByMap {
 
     implicit var encoderD = Encoders.kryo[Datasource]
 
-    val dd : Dataset[Datasource] = spark.read.textFile(datasourcePath)
+    val dd: Dataset[Datasource] = spark.read.textFile(datasourcePath)
       .map(r => mapper.readValue(r, classOf[Datasource]))
 
-    dd.map{ddt => oaToHostedbyItemType(ddt)}.filter(hb => !(hb.id.equals("")))
+    dd.map { ddt => oaToHostedbyItemType(ddt) }.filter(hb => !(hb.id.equals("")))
 
   }
 
@@ -115,17 +112,17 @@ object SparkProduceHostedByMap {
   }
 
 
-  def goldHostedByDataset(spark:SparkSession, datasourcePath:String) : Dataset[HostedByItemType] = {
+  def goldHostedByDataset(spark: SparkSession, datasourcePath: String): Dataset[HostedByItemType] = {
     import spark.implicits._
 
     implicit val mapEncoderUnibi: Encoder[UnibiGoldModel] = Encoders.kryo[UnibiGoldModel]
 
     val mapper = new ObjectMapper()
 
-    val dd : Dataset[UnibiGoldModel] = spark.read.textFile(datasourcePath)
+    val dd: Dataset[UnibiGoldModel] = spark.read.textFile(datasourcePath)
       .map(r => mapper.readValue(r, classOf[UnibiGoldModel]))
 
-    dd.map{ddt => goldToHostedbyItemType(ddt)}.filter(hb => !(hb.id.equals("")))
+    dd.map { ddt => goldToHostedbyItemType(ddt) }.filter(hb => !(hb.id.equals("")))
 
   }
 
@@ -134,41 +131,40 @@ object SparkProduceHostedByMap {
     return getHostedByItemType(Constants.DOAJ, doaj.getJournalTitle, doaj.getIssn, doaj.getEissn, "", true)
   }
 
-  def doajHostedByDataset(spark:SparkSession, datasourcePath:String) : Dataset[HostedByItemType] = {
+  def doajHostedByDataset(spark: SparkSession, datasourcePath: String): Dataset[HostedByItemType] = {
     import spark.implicits._
 
     implicit val mapEncoderDOAJ: Encoder[DOAJModel] = Encoders.kryo[DOAJModel]
 
     val mapper = new ObjectMapper()
 
-    val dd : Dataset[DOAJModel] = spark.read.textFile(datasourcePath)
+    val dd: Dataset[DOAJModel] = spark.read.textFile(datasourcePath)
       .map(r => mapper.readValue(r, classOf[DOAJModel]))
 
-    dd.map{ddt => doajToHostedbyItemType(ddt)}.filter(hb => !(hb.id.equals("")))
+    dd.map { ddt => doajToHostedbyItemType(ddt) }.filter(hb => !(hb.id.equals("")))
 
   }
 
   def toList(input: HostedByItemType): List[(String, HostedByItemType)] = {
-    var lst : List[(String, HostedByItemType)] = List()
+    var lst: List[(String, HostedByItemType)] = List()
-    if(!input.issn.equals("")){
+    if (!input.issn.equals("")) {
       lst = (input.issn, input) :: lst
     }
-    if(!input.eissn.equals("")){
+    if (!input.eissn.equals("")) {
       lst = (input.eissn, input) :: lst
     }
-    if(!input.lissn.equals("")){
+    if (!input.lissn.equals("")) {
       lst = (input.lissn, input) :: lst
     }
     lst
   }
 
 
-
+  def writeToHDFS(input: Array[String], outputPath: String, hdfsNameNode: String): Unit = {
-  def writeToHDFS(input: Array[String], outputPath: String, hdfsNameNode : String):Unit = {
     val conf = new Configuration()
 
     conf.set("fs.defaultFS", hdfsNameNode)
-    val fs= FileSystem.get(conf)
+    val fs = FileSystem.get(conf)
     val output = fs.create(new Path(outputPath))
     val writer = new PrintWriter(output)
     try {
@@ -182,7 +178,6 @@ object SparkProduceHostedByMap {
   }
 
 
-
   def main(args: Array[String]): Unit = {
 
     val logger: Logger = LoggerFactory.getLogger(getClass)
@@ -213,7 +208,7 @@ object SparkProduceHostedByMap {
       .union(doajHostedByDataset(spark, workingDirPath + "/doaj.json"))
       .flatMap(hbi => toList(hbi))).filter(hbi => hbi._2.id.startsWith("10|"))
       .map(hbi => toHostedByMap(hbi))(Encoders.STRING)
-      .rdd.saveAsTextFile(outputPath , classOf[GzipCodec])
+      .rdd.saveAsTextFile(outputPath, classOf[GzipCodec])
 
 
   }

dhp-workflows/dhp-graph-mapper/src/main/scala/eu/dnetlib/dhp/oa/graph/raw/CopyHdfsOafSparkApplication.scala

@@ -4,17 +4,11 @@ import com.fasterxml.jackson.databind.ObjectMapper
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
 import eu.dnetlib.dhp.common.HdfsSupport
 import eu.dnetlib.dhp.schema.common.ModelSupport
-import eu.dnetlib.dhp.schema.mdstore.MDStoreWithInfo
 import eu.dnetlib.dhp.schema.oaf.Oaf
 import eu.dnetlib.dhp.utils.DHPUtils
-import org.apache.commons.io.IOUtils
-import org.apache.commons.lang3.StringUtils
-import org.apache.http.client.methods.HttpGet
-import org.apache.http.impl.client.HttpClients
 import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
 import org.apache.spark.{SparkConf, SparkContext}
 import org.slf4j.LoggerFactory
-
 import scala.collection.JavaConverters._
 import scala.io.Source
 
@@ -59,7 +53,7 @@ object CopyHdfsOafSparkApplication {
     if (validPaths.nonEmpty) {
       val oaf = spark.read.load(validPaths: _*).as[Oaf]
       val mapper = new ObjectMapper()
-      val l =ModelSupport.oafTypes.entrySet.asScala.map(e => e.getKey).toList
+      val l = ModelSupport.oafTypes.entrySet.asScala.map(e => e.getKey).toList
       l.foreach(
         e =>
           oaf.filter(o => o.getClass.getSimpleName.equalsIgnoreCase(e))

dhp-workflows/dhp-graph-mapper/src/main/scala/eu/dnetlib/dhp/oa/graph/resolution/SparkResolveEntities.scala

@@ -2,9 +2,8 @@ package eu.dnetlib.dhp.oa.graph.resolution
 
 import com.fasterxml.jackson.databind.ObjectMapper
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
-import eu.dnetlib.dhp.common.HdfsSupport
 import eu.dnetlib.dhp.schema.common.EntityType
-import eu.dnetlib.dhp.schema.oaf.{OtherResearchProduct, Publication, Result, Software, Dataset => OafDataset}
+import eu.dnetlib.dhp.schema.oaf.{Dataset => OafDataset,_}
 import org.apache.commons.io.IOUtils
 import org.apache.hadoop.fs.{FileSystem, Path}
 import org.apache.spark.SparkConf
@@ -75,7 +74,7 @@ object SparkResolveEntities {
     }
   }
 
-  def generateResolvedEntities(spark: SparkSession, workingPath: String, graphBasePath: String, targetPath:String) = {
+  def generateResolvedEntities(spark: SparkSession, workingPath: String, graphBasePath: String, targetPath: String) = {
 
     implicit val resEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
     import spark.implicits._

dhp-workflows/dhp-graph-mapper/src/main/scala/eu/dnetlib/dhp/oa/graph/resolution/SparkResolveRelation.scala

@@ -3,7 +3,7 @@ package eu.dnetlib.dhp.oa.graph.resolution
 import com.fasterxml.jackson.databind.ObjectMapper
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
 import eu.dnetlib.dhp.common.HdfsSupport
-import eu.dnetlib.dhp.schema.oaf.{Relation, Result}
+import eu.dnetlib.dhp.schema.oaf.Relation
 import eu.dnetlib.dhp.utils.DHPUtils
 import org.apache.commons.io.IOUtils
 import org.apache.hadoop.fs.{FileSystem, Path}

dhp-workflows/dhp-graph-mapper/src/main/scala/eu/dnetlib/dhp/oa/sx/graphimport/SparkDataciteToOAF.scala

@@ -18,7 +18,6 @@ object SparkDataciteToOAF {
         .config(conf)
         .appName(getClass.getSimpleName)
         .master(parser.get("master")).getOrCreate()
-    import spark.implicits._
 
 
     val sc = spark.sparkContext

dhp-workflows/dhp-graph-mapper/src/main/scala/eu/dnetlib/dhp/sx/graph/SparkConvertDatasetToJsonRDD.scala

@@ -2,7 +2,7 @@ package eu.dnetlib.dhp.sx.graph
 
 import com.fasterxml.jackson.databind.ObjectMapper
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
-import eu.dnetlib.dhp.schema.oaf.{Oaf, OtherResearchProduct, Publication, Result, Software, Dataset => OafDataset}
+import eu.dnetlib.dhp.schema.oaf.Result
 import org.apache.commons.io.IOUtils
 import org.apache.hadoop.io.compress.GzipCodec
 import org.apache.spark.SparkConf
@@ -29,13 +29,13 @@ object SparkConvertDatasetToJsonRDD {
     val targetPath = parser.get("targetPath")
     log.info(s"targetPath  -> $targetPath")
 
-    val resultObject = List("publication","dataset","software", "otherResearchProduct")
+    val resultObject = List("publication", "dataset", "software", "otherResearchProduct")
     val mapper = new ObjectMapper()
-    implicit  val oafEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
+    implicit val oafEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
 
 
-    resultObject.foreach{item =>
+    resultObject.foreach { item =>
-      spark.read.load(s"$sourcePath/$item").as[Result].map(r=> mapper.writeValueAsString(r))(Encoders.STRING).rdd.saveAsTextFile(s"$targetPath/${item.toLowerCase}", classOf[GzipCodec])
+      spark.read.load(s"$sourcePath/$item").as[Result].map(r => mapper.writeValueAsString(r))(Encoders.STRING).rdd.saveAsTextFile(s"$targetPath/${item.toLowerCase}", classOf[GzipCodec])
     }
   }
 

dhp-workflows/dhp-graph-mapper/src/main/scala/eu/dnetlib/dhp/sx/graph/SparkConvertObjectToJson.scala

@@ -5,10 +5,10 @@ import eu.dnetlib.dhp.application.ArgumentApplicationParser
 import eu.dnetlib.dhp.schema.sx.scholix.Scholix
 import eu.dnetlib.dhp.schema.sx.summary.ScholixSummary
 import org.apache.commons.io.IOUtils
+import org.apache.hadoop.io.compress.GzipCodec
 import org.apache.spark.SparkConf
 import org.apache.spark.sql.{Dataset, Encoder, Encoders, SparkSession}
 import org.slf4j.{Logger, LoggerFactory}
-import org.apache.hadoop.io.compress._
 
 object SparkConvertObjectToJson {
 
@@ -32,8 +32,8 @@ object SparkConvertObjectToJson {
     log.info(s"objectType  -> $objectType")
 
 
-    implicit val scholixEncoder :Encoder[Scholix]= Encoders.kryo[Scholix]
+    implicit val scholixEncoder: Encoder[Scholix] = Encoders.kryo[Scholix]
-    implicit val summaryEncoder :Encoder[ScholixSummary]= Encoders.kryo[ScholixSummary]
+    implicit val summaryEncoder: Encoder[ScholixSummary] = Encoders.kryo[ScholixSummary]
 
 
     val mapper = new ObjectMapper
@@ -42,11 +42,11 @@ object SparkConvertObjectToJson {
       case "scholix" =>
         log.info("Serialize Scholix")
         val d: Dataset[Scholix] = spark.read.load(sourcePath).as[Scholix]
-        d.map(s => mapper.writeValueAsString(s))(Encoders.STRING).rdd.repartition(6000).saveAsTextFile(targetPath,  classOf[GzipCodec])
+        d.map(s => mapper.writeValueAsString(s))(Encoders.STRING).rdd.repartition(6000).saveAsTextFile(targetPath, classOf[GzipCodec])
       case "summary" =>
         log.info("Serialize Summary")
         val d: Dataset[ScholixSummary] = spark.read.load(sourcePath).as[ScholixSummary]
-        d.map(s => mapper.writeValueAsString(s))(Encoders.STRING).rdd.repartition(1000).saveAsTextFile(targetPath,  classOf[GzipCodec])
+        d.map(s => mapper.writeValueAsString(s))(Encoders.STRING).rdd.repartition(1000).saveAsTextFile(targetPath, classOf[GzipCodec])
     }
   }
 

dhp-workflows/dhp-graph-mapper/src/main/scala/eu/dnetlib/dhp/sx/graph/SparkConvertRDDtoDataset.scala

@@ -2,11 +2,12 @@ package eu.dnetlib.dhp.sx.graph
 
 import com.fasterxml.jackson.databind.ObjectMapper
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
-import eu.dnetlib.dhp.schema.oaf.{OtherResearchProduct, Publication, Relation, Result, Software, Dataset => OafDataset}
+import eu.dnetlib.dhp.schema.oaf.{OtherResearchProduct, Publication, Relation, Software,Dataset => OafDataset}
 import org.apache.commons.io.IOUtils
 import org.apache.spark.SparkConf
 import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
 import org.slf4j.{Logger, LoggerFactory}
+
 object SparkConvertRDDtoDataset {
 
   def main(args: Array[String]): Unit = {
@@ -31,39 +32,39 @@ object SparkConvertRDDtoDataset {
     val entityPath = s"$t/entities"
     val relPath = s"$t/relation"
     val mapper = new ObjectMapper()
-    implicit  val datasetEncoder: Encoder[OafDataset] = Encoders.kryo(classOf[OafDataset])
+    implicit val datasetEncoder: Encoder[OafDataset] = Encoders.kryo(classOf[OafDataset])
-    implicit  val publicationEncoder: Encoder[Publication] = Encoders.kryo(classOf[Publication])
+    implicit val publicationEncoder: Encoder[Publication] = Encoders.kryo(classOf[Publication])
-    implicit  val relationEncoder: Encoder[Relation] = Encoders.kryo(classOf[Relation])
+    implicit val relationEncoder: Encoder[Relation] = Encoders.kryo(classOf[Relation])
-    implicit  val orpEncoder: Encoder[OtherResearchProduct] = Encoders.kryo(classOf[OtherResearchProduct])
+    implicit val orpEncoder: Encoder[OtherResearchProduct] = Encoders.kryo(classOf[OtherResearchProduct])
-    implicit  val softwareEncoder: Encoder[Software] = Encoders.kryo(classOf[Software])
+    implicit val softwareEncoder: Encoder[Software] = Encoders.kryo(classOf[Software])
 
 
     log.info("Converting dataset")
-    val rddDataset =spark.sparkContext.textFile(s"$sourcePath/dataset").map(s => mapper.readValue(s, classOf[OafDataset]))
+    val rddDataset = spark.sparkContext.textFile(s"$sourcePath/dataset").map(s => mapper.readValue(s, classOf[OafDataset]))
     spark.createDataset(rddDataset).as[OafDataset].write.mode(SaveMode.Overwrite).save(s"$entityPath/dataset")
 
 
     log.info("Converting publication")
-    val rddPublication =spark.sparkContext.textFile(s"$sourcePath/publication").map(s => mapper.readValue(s, classOf[Publication]))
+    val rddPublication = spark.sparkContext.textFile(s"$sourcePath/publication").map(s => mapper.readValue(s, classOf[Publication]))
     spark.createDataset(rddPublication).as[Publication].write.mode(SaveMode.Overwrite).save(s"$entityPath/publication")
 
     log.info("Converting software")
-    val rddSoftware =spark.sparkContext.textFile(s"$sourcePath/software").map(s => mapper.readValue(s, classOf[Software]))
+    val rddSoftware = spark.sparkContext.textFile(s"$sourcePath/software").map(s => mapper.readValue(s, classOf[Software]))
     spark.createDataset(rddSoftware).as[Software].write.mode(SaveMode.Overwrite).save(s"$entityPath/software")
 
     log.info("Converting otherresearchproduct")
-    val rddOtherResearchProduct =spark.sparkContext.textFile(s"$sourcePath/otherresearchproduct").map(s => mapper.readValue(s, classOf[OtherResearchProduct]))
+    val rddOtherResearchProduct = spark.sparkContext.textFile(s"$sourcePath/otherresearchproduct").map(s => mapper.readValue(s, classOf[OtherResearchProduct]))
     spark.createDataset(rddOtherResearchProduct).as[OtherResearchProduct].write.mode(SaveMode.Overwrite).save(s"$entityPath/otherresearchproduct")
 
 
     log.info("Converting Relation")
 
 
-    val relationSemanticFilter = List("cites", "iscitedby","merges", "ismergedin")
+    val relationSemanticFilter = List("cites", "iscitedby", "merges", "ismergedin")
 
-    val rddRelation =spark.sparkContext.textFile(s"$sourcePath/relation")
+    val rddRelation = spark.sparkContext.textFile(s"$sourcePath/relation")
       .map(s => mapper.readValue(s, classOf[Relation]))
-      .filter(r=> r.getSource.startsWith("50") && r.getTarget.startsWith("50"))
+      .filter(r => r.getSource.startsWith("50") && r.getTarget.startsWith("50"))
       .filter(r => !relationSemanticFilter.exists(k => k.equalsIgnoreCase(r.getRelClass)))
     spark.createDataset(rddRelation).as[Relation].write.mode(SaveMode.Overwrite).save(s"$relPath")
 

dhp-workflows/dhp-graph-mapper/src/main/scala/eu/dnetlib/dhp/sx/graph/SparkCreateInputGraph.scala

@@ -1,14 +1,12 @@
 package eu.dnetlib.dhp.sx.graph
 
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
-import eu.dnetlib.dhp.schema.oaf.{Oaf, OtherResearchProduct, Publication, Relation, Result, Software, Dataset => OafDataset}
+import eu.dnetlib.dhp.schema.oaf.{Dataset => OafDataset,_}
 import org.apache.commons.io.IOUtils
 import org.apache.spark.SparkConf
-import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
+import org.apache.spark.sql._
 import org.slf4j.{Logger, LoggerFactory}
 
-
-
 object SparkCreateInputGraph {
 
   def main(args: Array[String]): Unit = {
@@ -33,7 +31,7 @@ object SparkCreateInputGraph {
 
     )
 
-    implicit  val oafEncoder: Encoder[Oaf] = Encoders.kryo(classOf[Oaf])
+    implicit val oafEncoder: Encoder[Oaf] = Encoders.kryo(classOf[Oaf])
     implicit val publicationEncoder: Encoder[Publication] = Encoders.kryo(classOf[Publication])
     implicit val datasetEncoder: Encoder[OafDataset] = Encoders.kryo(classOf[OafDataset])
     implicit val softwareEncoder: Encoder[Software] = Encoders.kryo(classOf[Software])
@@ -41,16 +39,13 @@ object SparkCreateInputGraph {
     implicit val relEncoder: Encoder[Relation] = Encoders.kryo(classOf[Relation])
 
 
-
-
-
     val sourcePath = parser.get("sourcePath")
     log.info(s"sourcePath  -> $sourcePath")
     val targetPath = parser.get("targetPath")
     log.info(s"targetPath  -> $targetPath")
 
 
-    val oafDs:Dataset[Oaf] = spark.read.load(s"$sourcePath/*").as[Oaf]
+    val oafDs: Dataset[Oaf] = spark.read.load(s"$sourcePath/*").as[Oaf]
 
 
     log.info("Extract Publication")
@@ -70,27 +65,27 @@ object SparkCreateInputGraph {
 
     resultObject.foreach { r =>
       log.info(s"Make ${r._1} unique")
-      makeDatasetUnique(s"$targetPath/extracted/${r._1}",s"$targetPath/preprocess/${r._1}",spark, r._2)
+      makeDatasetUnique(s"$targetPath/extracted/${r._1}", s"$targetPath/preprocess/${r._1}", spark, r._2)
     }
   }
 
 
-  def extractEntities[T <: Oaf ](oafDs:Dataset[Oaf], targetPath:String, clazz:Class[T], log:Logger) :Unit = {
+  def extractEntities[T <: Oaf](oafDs: Dataset[Oaf], targetPath: String, clazz: Class[T], log: Logger): Unit = {
 
-    implicit  val resEncoder: Encoder[T] = Encoders.kryo(clazz)
+    implicit val resEncoder: Encoder[T] = Encoders.kryo(clazz)
     log.info(s"Extract ${clazz.getSimpleName}")
     oafDs.filter(o => o.isInstanceOf[T]).map(p => p.asInstanceOf[T]).write.mode(SaveMode.Overwrite).save(targetPath)
   }
 
 
-  def makeDatasetUnique[T <: Result ](sourcePath:String, targetPath:String, spark:SparkSession, clazz:Class[T]) :Unit = {
+  def makeDatasetUnique[T <: Result](sourcePath: String, targetPath: String, spark: SparkSession, clazz: Class[T]): Unit = {
     import spark.implicits._
 
-    implicit  val resEncoder: Encoder[T] = Encoders.kryo(clazz)
+    implicit val resEncoder: Encoder[T] = Encoders.kryo(clazz)
 
-    val ds:Dataset[T] = spark.read.load(sourcePath).as[T]
+    val ds: Dataset[T] = spark.read.load(sourcePath).as[T]
 
-    ds.groupByKey(_.getId).reduceGroups{(x,y) =>
+    ds.groupByKey(_.getId).reduceGroups { (x, y) =>
       x.mergeFrom(y)
       x
     }.map(_._2).write.mode(SaveMode.Overwrite).save(targetPath)

dhp-workflows/dhp-graph-mapper/src/main/scala/eu/dnetlib/dhp/sx/graph/SparkCreateScholix.scala

@@ -9,7 +9,7 @@ import eu.dnetlib.dhp.sx.graph.scholix.ScholixUtils.RelatedEntities
 import org.apache.commons.io.IOUtils
 import org.apache.spark.SparkConf
 import org.apache.spark.sql.functions.count
-import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
+import org.apache.spark.sql._
 import org.slf4j.{Logger, LoggerFactory}
 
 object SparkCreateScholix {
@@ -42,7 +42,7 @@ object SparkCreateScholix {
 
 
     val relationDS: Dataset[(String, Relation)] = spark.read.load(relationPath).as[Relation]
-      .filter(r => (r.getDataInfo== null || r.getDataInfo.getDeletedbyinference == false) && !r.getRelClass.toLowerCase.contains("merge"))
+      .filter(r => (r.getDataInfo == null || r.getDataInfo.getDeletedbyinference == false) && !r.getRelClass.toLowerCase.contains("merge"))
       .map(r => (r.getSource, r))(Encoders.tuple(Encoders.STRING, relEncoder))
 
     val summaryDS: Dataset[(String, ScholixSummary)] = spark.read.load(summaryPath).as[ScholixSummary]
@@ -51,54 +51,54 @@ object SparkCreateScholix {
 
     relationDS.joinWith(summaryDS, relationDS("_1").equalTo(summaryDS("_1")), "left")
       .map { input: ((String, Relation), (String, ScholixSummary)) =>
-        if (input._1!= null && input._2!= null) {
+        if (input._1 != null && input._2 != null) {
           val rel: Relation = input._1._2
           val source: ScholixSummary = input._2._2
           (rel.getTarget, ScholixUtils.scholixFromSource(rel, source))
         }
-        else  null
+        else null
       }(Encoders.tuple(Encoders.STRING, scholixEncoder))
-      .filter(r => r!= null)
+      .filter(r => r != null)
       .write.mode(SaveMode.Overwrite).save(s"$targetPath/scholix_from_source")
 
     val scholixSource: Dataset[(String, Scholix)] = spark.read.load(s"$targetPath/scholix_from_source").as[(String, Scholix)](Encoders.tuple(Encoders.STRING, scholixEncoder))
 
     scholixSource.joinWith(summaryDS, scholixSource("_1").equalTo(summaryDS("_1")), "left")
       .map { input: ((String, Scholix), (String, ScholixSummary)) =>
-        if (input._2== null) {
+        if (input._2 == null) {
           null
         } else {
           val s: Scholix = input._1._2
           val target: ScholixSummary = input._2._2
           ScholixUtils.generateCompleteScholix(s, target)
         }
-      }.filter(s => s!= null).write.mode(SaveMode.Overwrite).save(s"$targetPath/scholix_one_verse")
+      }.filter(s => s != null).write.mode(SaveMode.Overwrite).save(s"$targetPath/scholix_one_verse")
 
 
     val scholix_o_v: Dataset[Scholix] = spark.read.load(s"$targetPath/scholix_one_verse").as[Scholix]
 
     scholix_o_v.flatMap(s => List(s, ScholixUtils.createInverseScholixRelation(s))).as[Scholix]
-      .map(s=> (s.getIdentifier,s))(Encoders.tuple(Encoders.STRING, scholixEncoder))
+      .map(s => (s.getIdentifier, s))(Encoders.tuple(Encoders.STRING, scholixEncoder))
       .groupByKey(_._1)
       .agg(ScholixUtils.scholixAggregator.toColumn)
       .map(s => s._2)
       .write.mode(SaveMode.Overwrite).save(s"$targetPath/scholix")
 
-    val scholix_final:Dataset[Scholix] = spark.read.load(s"$targetPath/scholix").as[Scholix]
+    val scholix_final: Dataset[Scholix] = spark.read.load(s"$targetPath/scholix").as[Scholix]
 
-    val stats:Dataset[(String,String,Long)]= scholix_final.map(s => (s.getSource.getDnetIdentifier, s.getTarget.getObjectType)).groupBy("_1", "_2").agg(count("_1")).as[(String,String,Long)]
+    val stats: Dataset[(String, String, Long)] = scholix_final.map(s => (s.getSource.getDnetIdentifier, s.getTarget.getObjectType)).groupBy("_1", "_2").agg(count("_1")).as[(String, String, Long)]
 
 
     stats
-      .map(s => RelatedEntities(s._1, if ("dataset".equalsIgnoreCase(s._2)) s._3 else  0, if ("publication".equalsIgnoreCase(s._2)) s._3 else  0 ))
+      .map(s => RelatedEntities(s._1, if ("dataset".equalsIgnoreCase(s._2)) s._3 else 0, if ("publication".equalsIgnoreCase(s._2)) s._3 else 0))
       .groupByKey(_.id)
-      .reduceGroups((a, b) => RelatedEntities(a.id, a.relatedDataset+b.relatedDataset, a.relatedPublication+b.relatedPublication))
+      .reduceGroups((a, b) => RelatedEntities(a.id, a.relatedDataset + b.relatedDataset, a.relatedPublication + b.relatedPublication))
       .map(_._2)
       .write.mode(SaveMode.Overwrite).save(s"$targetPath/related_entities")
 
-    val relatedEntitiesDS:Dataset[RelatedEntities] = spark.read.load(s"$targetPath/related_entities").as[RelatedEntities].filter(r => r.relatedPublication>0 || r.relatedDataset > 0)
+    val relatedEntitiesDS: Dataset[RelatedEntities] = spark.read.load(s"$targetPath/related_entities").as[RelatedEntities].filter(r => r.relatedPublication > 0 || r.relatedDataset > 0)
 
-    relatedEntitiesDS.joinWith(summaryDS, relatedEntitiesDS("id").equalTo(summaryDS("_1")), "inner").map{i =>
+    relatedEntitiesDS.joinWith(summaryDS, relatedEntitiesDS("id").equalTo(summaryDS("_1")), "inner").map { i =>
       val re = i._1
       val sum = i._2._2
 

dhp-workflows/dhp-graph-mapper/src/main/scala/eu/dnetlib/dhp/sx/graph/SparkCreateSummaryObject.scala

@@ -6,7 +6,7 @@ import eu.dnetlib.dhp.schema.sx.summary.ScholixSummary
 import eu.dnetlib.dhp.sx.graph.scholix.ScholixUtils
 import org.apache.commons.io.IOUtils
 import org.apache.spark.SparkConf
-import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
+import org.apache.spark.sql._
 import org.slf4j.{Logger, LoggerFactory}
 
 object SparkCreateSummaryObject {
@@ -28,15 +28,15 @@ object SparkCreateSummaryObject {
     val targetPath = parser.get("targetPath")
     log.info(s"targetPath  -> $targetPath")
 
-    implicit val resultEncoder:Encoder[Result] = Encoders.kryo[Result]
+    implicit val resultEncoder: Encoder[Result] = Encoders.kryo[Result]
-    implicit val oafEncoder:Encoder[Oaf] = Encoders.kryo[Oaf]
+    implicit val oafEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
 
-    implicit val summaryEncoder:Encoder[ScholixSummary] = Encoders.kryo[ScholixSummary]
+    implicit val summaryEncoder: Encoder[ScholixSummary] = Encoders.kryo[ScholixSummary]
 
 
-    val ds:Dataset[Result] = spark.read.load(s"$sourcePath/*").as[Result].filter(r=>r.getDataInfo== null ||  r.getDataInfo.getDeletedbyinference== false)
+    val ds: Dataset[Result] = spark.read.load(s"$sourcePath/*").as[Result].filter(r => r.getDataInfo == null || r.getDataInfo.getDeletedbyinference == false)
 
-    ds.repartition(6000).map(r => ScholixUtils.resultToSummary(r)).filter(s => s!= null).write.mode(SaveMode.Overwrite).save(targetPath)
+    ds.repartition(6000).map(r => ScholixUtils.resultToSummary(r)).filter(s => s != null).write.mode(SaveMode.Overwrite).save(targetPath)
 
   }
 

dhp-workflows/dhp-graph-mapper/src/main/scala/eu/dnetlib/dhp/sx/graph/pangaea/PangaeaUtils.scala

@@ -5,6 +5,7 @@ import org.apache.spark.sql.{Encoder, Encoders}
 import org.json4s
 import org.json4s.DefaultFormats
 import org.json4s.jackson.JsonMethods.parse
+
 import java.util.regex.Pattern
 import scala.language.postfixOps
 import scala.xml.{Elem, Node, XML}

dhp-workflows/dhp-graph-mapper/src/main/scala/eu/dnetlib/dhp/sx/graph/pangaea/SparkGeneratePanagaeaDataset.scala

@@ -2,11 +2,11 @@ package eu.dnetlib.dhp.sx.graph.pangaea
 
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
 import org.apache.spark.rdd.RDD
-import org.apache.spark.{SparkConf, SparkContext}
 import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
+import org.apache.spark.{SparkConf, SparkContext}
 import org.slf4j.{Logger, LoggerFactory}
-
 import scala.collection.JavaConverters._
+
 import scala.io.Source
 
 object SparkGeneratePanagaeaDataset {
@@ -28,17 +28,17 @@ object SparkGeneratePanagaeaDataset {
 
     parser.getObjectMap.asScala.foreach(s => logger.info(s"${s._1} -> ${s._2}"))
     logger.info("Converting sequential file into Dataset")
-    val sc:SparkContext = spark.sparkContext
+    val sc: SparkContext = spark.sparkContext
 
-    val workingPath:String = parser.get("workingPath")
+    val workingPath: String = parser.get("workingPath")
 
     implicit val pangaeaEncoders: Encoder[PangaeaDataModel] = Encoders.kryo[PangaeaDataModel]
 
-    val inputRDD:RDD[PangaeaDataModel] =  sc.textFile(s"$workingPath/update").map(s => PangaeaUtils.toDataset(s))
+    val inputRDD: RDD[PangaeaDataModel] = sc.textFile(s"$workingPath/update").map(s => PangaeaUtils.toDataset(s))
 
     spark.createDataset(inputRDD).as[PangaeaDataModel]
-      .map(s => (s.identifier,s))(Encoders.tuple(Encoders.STRING, pangaeaEncoders))
+      .map(s => (s.identifier, s))(Encoders.tuple(Encoders.STRING, pangaeaEncoders))
-       .groupByKey(_._1)(Encoders.STRING)
+      .groupByKey(_._1)(Encoders.STRING)
       .agg(PangaeaUtils.getDatasetAggregator().toColumn)
       .map(s => s._2)
       .write.mode(SaveMode.Overwrite).save(s"$workingPath/dataset")
@@ -46,7 +46,4 @@ object SparkGeneratePanagaeaDataset {
   }
 
 
-
-
-
 }

dhp-workflows/dhp-graph-mapper/src/main/scala/eu/dnetlib/dhp/sx/graph/scholix/ScholixUtils.scala

@@ -1,6 +1,5 @@
 package eu.dnetlib.dhp.sx.graph.scholix
 
-
 import eu.dnetlib.dhp.schema.oaf.{Publication, Relation, Result, StructuredProperty}
 import eu.dnetlib.dhp.schema.sx.scholix._
 import eu.dnetlib.dhp.schema.sx.summary.{CollectedFromType, SchemeValue, ScholixSummary, Typology}
@@ -10,23 +9,22 @@ import org.apache.spark.sql.{Encoder, Encoders}
 import org.json4s
 import org.json4s.DefaultFormats
 import org.json4s.jackson.JsonMethods.parse
-
 import scala.collection.JavaConverters._
 import scala.io.Source
-import scala.language.postfixOps
 
 object ScholixUtils {
 
 
   val DNET_IDENTIFIER_SCHEMA: String = "DNET Identifier"
 
-  val DATE_RELATION_KEY:String = "RelationDate"
+  val DATE_RELATION_KEY: String = "RelationDate"
-  case class RelationVocabulary(original:String, inverse:String){}
 
-  case class RelatedEntities(id:String, relatedDataset:Long, relatedPublication:Long){}
+  case class RelationVocabulary(original: String, inverse: String) {}
 
-  val relations:Map[String, RelationVocabulary] = {
+  case class RelatedEntities(id: String, relatedDataset: Long, relatedPublication: Long) {}
-    val input =Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/graph/relations.json")).mkString
+
+  val relations: Map[String, RelationVocabulary] = {
+    val input = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/graph/relations.json")).mkString
     implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
 
     lazy val json: json4s.JValue = parse(input)
@@ -35,12 +33,12 @@ object ScholixUtils {
   }
 
 
-  def extractRelationDate(relation: Relation):String = {
+  def extractRelationDate(relation: Relation): String = {
 
-    if (relation.getProperties== null || !relation.getProperties.isEmpty)
+    if (relation.getProperties == null || !relation.getProperties.isEmpty)
       null
     else {
-      val date =relation.getProperties.asScala.find(p => DATE_RELATION_KEY.equalsIgnoreCase(p.getKey)).map(p => p.getValue)
+      val date = relation.getProperties.asScala.find(p => DATE_RELATION_KEY.equalsIgnoreCase(p.getKey)).map(p => p.getValue)
       if (date.isDefined)
         date.get
       else
@@ -48,9 +46,9 @@ object ScholixUtils {
     }
   }
 
-  def extractRelationDate(summary: ScholixSummary):String = {
+  def extractRelationDate(summary: ScholixSummary): String = {
 
-    if(summary.getDate== null || summary.getDate.isEmpty)
+    if (summary.getDate == null || summary.getDate.isEmpty)
       null
     else {
       summary.getDate.get(0)
@@ -59,15 +57,14 @@ object ScholixUtils {
 
   }
 
-  def inverseRelationShip(rel:ScholixRelationship):ScholixRelationship = {
+  def inverseRelationShip(rel: ScholixRelationship): ScholixRelationship = {
     new ScholixRelationship(rel.getInverse, rel.getSchema, rel.getName)
 
 
   }
 
 
-
+  val statsAggregator: Aggregator[(String, String, Long), RelatedEntities, RelatedEntities] = new Aggregator[(String, String, Long), RelatedEntities, RelatedEntities] with Serializable {
-  val statsAggregator:Aggregator[(String,String, Long), RelatedEntities, RelatedEntities] = new Aggregator[(String,String, Long), RelatedEntities, RelatedEntities] with  Serializable {
     override def zero: RelatedEntities = null
 
     override def reduce(b: RelatedEntities, a: (String, String, Long)): RelatedEntities = {
@@ -78,17 +75,16 @@ object ScholixUtils {
       if (b == null)
         RelatedEntities(a._1, relatedDataset, relatedPublication)
       else
-        RelatedEntities(a._1,b.relatedDataset+ relatedDataset, b.relatedPublication+ relatedPublication )
+        RelatedEntities(a._1, b.relatedDataset + relatedDataset, b.relatedPublication + relatedPublication)
     }
 
     override def merge(b1: RelatedEntities, b2: RelatedEntities): RelatedEntities = {
-      if (b1!= null && b2!= null)
+      if (b1 != null && b2 != null)
-        RelatedEntities(b1.id, b1.relatedDataset+ b2.relatedDataset, b1.relatedPublication+ b2.relatedPublication)
+        RelatedEntities(b1.id, b1.relatedDataset + b2.relatedDataset, b1.relatedPublication + b2.relatedPublication)
 
+      else if (b1 != null)
+        b1
       else
-        if (b1!= null)
-          b1
-        else
         b2
     }
 
@@ -104,12 +100,12 @@ object ScholixUtils {
     override def zero: Scholix = null
 
 
-    def scholix_complete(s:Scholix):Boolean ={
+    def scholix_complete(s: Scholix): Boolean = {
-      if (s== null || s.getIdentifier==null) {
+      if (s == null || s.getIdentifier == null) {
         false
       } else if (s.getSource == null || s.getTarget == null) {
-          false
+        false
-        }
+      }
       else if (s.getLinkprovider == null || s.getLinkprovider.isEmpty)
         false
       else
@@ -121,7 +117,7 @@ object ScholixUtils {
     }
 
     override def merge(b1: Scholix, b2: Scholix): Scholix = {
-      if (scholix_complete(b1)) b1 else  b2
+      if (scholix_complete(b1)) b1 else b2
     }
 
     override def finish(reduction: Scholix): Scholix = reduction
@@ -132,7 +128,7 @@ object ScholixUtils {
   }
 
 
-  def createInverseScholixRelation(scholix: Scholix):Scholix = {
+  def createInverseScholixRelation(scholix: Scholix): Scholix = {
     val s = new Scholix
     s.setPublicationDate(scholix.getPublicationDate)
     s.setPublisher(scholix.getPublisher)
@@ -144,34 +140,33 @@ object ScholixUtils {
     s
 
 
-
   }
 
 
-  def extractCollectedFrom(summary:ScholixSummary): List[ScholixEntityId] = {
+  def extractCollectedFrom(summary: ScholixSummary): List[ScholixEntityId] = {
-    if (summary.getDatasources!= null && !summary.getDatasources.isEmpty) {
+    if (summary.getDatasources != null && !summary.getDatasources.isEmpty) {
-      val l: List[ScholixEntityId] = summary.getDatasources.asScala.map{
+      val l: List[ScholixEntityId] = summary.getDatasources.asScala.map {
         d => new ScholixEntityId(d.getDatasourceName, List(new ScholixIdentifier(d.getDatasourceId, "DNET Identifier", null)).asJava)
       }(collection.breakOut)
-       l
+      l
     } else List()
   }
 
-  def extractCollectedFrom(relation: Relation) : List[ScholixEntityId] = {
+  def extractCollectedFrom(relation: Relation): List[ScholixEntityId] = {
     if (relation.getCollectedfrom != null && !relation.getCollectedfrom.isEmpty) {
 
 
       val l: List[ScholixEntityId] = relation.getCollectedfrom.asScala.map {
         c =>
 
-          new ScholixEntityId(c.getValue, List(new ScholixIdentifier(c.getKey, DNET_IDENTIFIER_SCHEMA,null)).asJava)
+          new ScholixEntityId(c.getValue, List(new ScholixIdentifier(c.getKey, DNET_IDENTIFIER_SCHEMA, null)).asJava)
       }(collection breakOut)
       l
     } else List()
   }
 
 
-  def generateCompleteScholix(scholix: Scholix, target:ScholixSummary): Scholix = {
+  def generateCompleteScholix(scholix: Scholix, target: ScholixSummary): Scholix = {
     val s = new Scholix
     s.setPublicationDate(scholix.getPublicationDate)
     s.setPublisher(scholix.getPublisher)
@@ -192,29 +187,28 @@ object ScholixUtils {
     r.setObjectType(summaryObject.getTypology.toString)
     r.setObjectSubType(summaryObject.getSubType)
 
-    if (summaryObject.getTitle!= null && !summaryObject.getTitle.isEmpty)
+    if (summaryObject.getTitle != null && !summaryObject.getTitle.isEmpty)
-        r.setTitle(summaryObject.getTitle.get(0))
+      r.setTitle(summaryObject.getTitle.get(0))
 
-    if (summaryObject.getAuthor!= null && !summaryObject.getAuthor.isEmpty){
+    if (summaryObject.getAuthor != null && !summaryObject.getAuthor.isEmpty) {
-      val l:List[ScholixEntityId] = summaryObject.getAuthor.asScala.map(a => new ScholixEntityId(a,null)).toList
+      val l: List[ScholixEntityId] = summaryObject.getAuthor.asScala.map(a => new ScholixEntityId(a, null)).toList
       if (l.nonEmpty)
         r.setCreator(l.asJava)
     }
 
-    if (summaryObject.getDate!= null && !summaryObject.getDate.isEmpty)
+    if (summaryObject.getDate != null && !summaryObject.getDate.isEmpty)
       r.setPublicationDate(summaryObject.getDate.get(0))
-    if (summaryObject.getPublisher!= null && !summaryObject.getPublisher.isEmpty)
+    if (summaryObject.getPublisher != null && !summaryObject.getPublisher.isEmpty) {
-    {
+      val plist: List[ScholixEntityId] = summaryObject.getPublisher.asScala.map(p => new ScholixEntityId(p, null)).toList
-      val plist:List[ScholixEntityId] =summaryObject.getPublisher.asScala.map(p => new ScholixEntityId(p, null)).toList
 
       if (plist.nonEmpty)
         r.setPublisher(plist.asJava)
     }
 
 
-    if (summaryObject.getDatasources!= null && !summaryObject.getDatasources.isEmpty) {
+    if (summaryObject.getDatasources != null && !summaryObject.getDatasources.isEmpty) {
 
-      val l:List[ScholixCollectedFrom] = summaryObject.getDatasources.asScala.map(c => new ScholixCollectedFrom(
+      val l: List[ScholixCollectedFrom] = summaryObject.getDatasources.asScala.map(c => new ScholixCollectedFrom(
         new ScholixEntityId(c.getDatasourceName, List(new ScholixIdentifier(c.getDatasourceId, DNET_IDENTIFIER_SCHEMA, null)).asJava)
         , "collected", "complete"
 
@@ -228,12 +222,9 @@ object ScholixUtils {
   }
 
 
+  def scholixFromSource(relation: Relation, source: ScholixSummary): Scholix = {
 
-
+    if (relation == null || source == null)
-
-  def scholixFromSource(relation:Relation, source:ScholixSummary):Scholix = {
-
-    if (relation== null || source== null)
       return null
 
     val s = new Scholix
@@ -253,9 +244,9 @@ object ScholixUtils {
     s.setPublicationDate(d)
 
 
-    if (source.getPublisher!= null && !source.getPublisher.isEmpty) {
+    if (source.getPublisher != null && !source.getPublisher.isEmpty) {
       val l: List[ScholixEntityId] = source.getPublisher.asScala
-        .map{
+        .map {
           p =>
             new ScholixEntityId(p, null)
         }(collection.breakOut)
@@ -265,7 +256,7 @@ object ScholixUtils {
     }
 
     val semanticRelation = relations.getOrElse(relation.getRelClass.toLowerCase, null)
-    if (semanticRelation== null)
+    if (semanticRelation == null)
       return null
     s.setRelationship(new ScholixRelationship(semanticRelation.original, "datacite", semanticRelation.inverse))
     s.setSource(generateScholixResourceFromSummary(source))
@@ -274,8 +265,8 @@ object ScholixUtils {
   }
 
 
-  def findURLForPID(pidValue:List[StructuredProperty], urls:List[String]):List[(StructuredProperty, String)] = {
+  def findURLForPID(pidValue: List[StructuredProperty], urls: List[String]): List[(StructuredProperty, String)] = {
-    pidValue.map{
+    pidValue.map {
       p =>
         val pv = p.getValue
 
@@ -285,67 +276,67 @@ object ScholixUtils {
   }
 
 
-  def extractTypedIdentifierFromInstance(r:Result):List[ScholixIdentifier] = {
+  def extractTypedIdentifierFromInstance(r: Result): List[ScholixIdentifier] = {
     if (r.getInstance() == null || r.getInstance().isEmpty)
       return List()
-    r.getInstance().asScala.filter(i => i.getUrl!= null && !i.getUrl.isEmpty)
+    r.getInstance().asScala.filter(i => i.getUrl != null && !i.getUrl.isEmpty)
-      .filter(i => i.getPid!= null && i.getUrl != null)
+      .filter(i => i.getPid != null && i.getUrl != null)
       .flatMap(i => findURLForPID(i.getPid.asScala.toList, i.getUrl.asScala.toList))
       .map(i => new ScholixIdentifier(i._1.getValue, i._1.getQualifier.getClassid, i._2)).distinct.toList
   }
 
-  def resultToSummary(r:Result):ScholixSummary = {
+  def resultToSummary(r: Result): ScholixSummary = {
     val s = new ScholixSummary
     s.setId(r.getId)
     if (r.getPid == null || r.getPid.isEmpty)
       return null
 
-    val persistentIdentifiers:List[ScholixIdentifier] =  extractTypedIdentifierFromInstance(r)
+    val persistentIdentifiers: List[ScholixIdentifier] = extractTypedIdentifierFromInstance(r)
     if (persistentIdentifiers.isEmpty)
       return null
     s.setLocalIdentifier(persistentIdentifiers.asJava)
-    if (r.isInstanceOf[Publication] )
+    if (r.isInstanceOf[Publication])
       s.setTypology(Typology.publication)
     else
       s.setTypology(Typology.dataset)
 
     s.setSubType(r.getInstance().get(0).getInstancetype.getClassname)
 
-    if (r.getTitle!= null && r.getTitle.asScala.nonEmpty) {
+    if (r.getTitle != null && r.getTitle.asScala.nonEmpty) {
-      val titles:List[String] =r.getTitle.asScala.map(t => t.getValue)(collection breakOut)
+      val titles: List[String] = r.getTitle.asScala.map(t => t.getValue)(collection breakOut)
       if (titles.nonEmpty)
         s.setTitle(titles.asJava)
       else
-        return  null
+        return null
     }
 
-    if(r.getAuthor!= null && !r.getAuthor.isEmpty) {
+    if (r.getAuthor != null && !r.getAuthor.isEmpty) {
-      val authors:List[String] = r.getAuthor.asScala.map(a=> a.getFullname)(collection breakOut)
+      val authors: List[String] = r.getAuthor.asScala.map(a => a.getFullname)(collection breakOut)
       if (authors nonEmpty)
         s.setAuthor(authors.asJava)
     }
     if (r.getInstance() != null) {
-      val dt:List[String] = r.getInstance().asScala.filter(i => i.getDateofacceptance != null).map(i => i.getDateofacceptance.getValue)(collection.breakOut)
+      val dt: List[String] = r.getInstance().asScala.filter(i => i.getDateofacceptance != null).map(i => i.getDateofacceptance.getValue)(collection.breakOut)
       if (dt.nonEmpty)
         s.setDate(dt.distinct.asJava)
     }
-    if (r.getDescription!= null && !r.getDescription.isEmpty) {
+    if (r.getDescription != null && !r.getDescription.isEmpty) {
-      val d = r.getDescription.asScala.find(f => f!= null && f.getValue!=null)
+      val d = r.getDescription.asScala.find(f => f != null && f.getValue != null)
       if (d.isDefined)
         s.setDescription(d.get.getValue)
     }
 
-    if (r.getSubject!= null && !r.getSubject.isEmpty) {
+    if (r.getSubject != null && !r.getSubject.isEmpty) {
-      val subjects:List[SchemeValue] =r.getSubject.asScala.map(s => new SchemeValue(s.getQualifier.getClassname, s.getValue))(collection breakOut)
+      val subjects: List[SchemeValue] = r.getSubject.asScala.map(s => new SchemeValue(s.getQualifier.getClassname, s.getValue))(collection breakOut)
       if (subjects.nonEmpty)
         s.setSubject(subjects.asJava)
     }
 
-    if (r.getPublisher!= null)
+    if (r.getPublisher != null)
       s.setPublisher(List(r.getPublisher.getValue).asJava)
 
-    if (r.getCollectedfrom!= null && !r.getCollectedfrom.isEmpty) {
+    if (r.getCollectedfrom != null && !r.getCollectedfrom.isEmpty) {
-      val cf:List[CollectedFromType] = r.getCollectedfrom.asScala.map(c => new CollectedFromType(c.getValue, c.getKey, "complete"))(collection breakOut)
+      val cf: List[CollectedFromType] = r.getCollectedfrom.asScala.map(c => new CollectedFromType(c.getValue, c.getKey, "complete"))(collection breakOut)
       if (cf.nonEmpty)
         s.setDatasources(cf.distinct.asJava)
     }

dhp-workflows/dhp-graph-mapper/src/test/java/eu/dnetlib/dhp/oa/graph/dump/DumpJobTest.java

@@ -171,24 +171,6 @@ public class DumpJobTest {
 
 		GraphResult gr = verificationDataset.first();
 
-		Assertions.assertEquals(2, gr.getMeasures().size());
-		Assertions
-			.assertTrue(
-				gr
-					.getMeasures()
-					.stream()
-					.anyMatch(
-						m -> m.getKey().equals("influence")
-							&& m.getValue().equals("1.62759106106e-08")));
-		Assertions
-			.assertTrue(
-				gr
-					.getMeasures()
-					.stream()
-					.anyMatch(
-						m -> m.getKey().equals("popularity")
-							&& m.getValue().equals("0.22519296")));
-
 		Assertions.assertEquals(6, gr.getAuthor().size());
 		Assertions
 			.assertTrue(

dhp-workflows/dhp-graph-mapper/src/test/scala/eu/dnetlib/dhp/oa/graph/hostedbymap/TestPrepare.scala

@@ -3,13 +3,9 @@ package eu.dnetlib.dhp.oa.graph.hostedbymap
 import com.fasterxml.jackson.databind.ObjectMapper
 import eu.dnetlib.dhp.oa.graph.hostedbymap.SparkPrepareHostedByInfoToApply.{joinResHBM, prepareResultInfo, toEntityInfo}
 import eu.dnetlib.dhp.oa.graph.hostedbymap.model.EntityInfo
-import eu.dnetlib.dhp.schema.oaf.{Datasource, OpenAccessRoute, Publication}
-import javax.management.openmbean.OpenMBeanAttributeInfo
 import org.apache.spark.SparkConf
 import org.apache.spark.sql.{Dataset, Encoder, Encoders, SparkSession}
-import org.json4s
 import org.json4s.DefaultFormats
-import eu.dnetlib.dhp.schema.common.ModelConstants
 import org.junit.jupiter.api.Assertions.{assertEquals, assertTrue}
 import org.junit.jupiter.api.Test
 

dhp-workflows/dhp-graph-mapper/src/test/scala/eu/dnetlib/dhp/oa/graph/hostedbymap/TestPreprocess.scala

@@ -4,10 +4,9 @@ import eu.dnetlib.dhp.schema.oaf.Datasource
 import org.apache.spark.SparkConf
 import org.apache.spark.sql.{Dataset, Encoder, Encoders, SparkSession}
 import org.json4s.DefaultFormats
-import org.junit.jupiter.api.Assertions.{assertNotNull, assertTrue}
-import org.junit.jupiter.api.Test
-import org.junit.jupiter.api.Assertions._
 import org.json4s.jackson.Serialization.write
+import org.junit.jupiter.api.Assertions._
+import org.junit.jupiter.api.Test
 
 class TestPreprocess extends java.io.Serializable{
 

dhp-workflows/dhp-graph-mapper/src/test/scala/eu/dnetlib/dhp/sx/graph/scholix/ScholixGraphTest.scala

@@ -37,7 +37,8 @@ class ScholixGraphTest extends AbstractVocabularyTest{
     val input = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/graph/scholix/result.json")).mkString
     val res =SparkResolveRelation.extractPidsFromRecord(input)
     assertNotNull(res)
-    assertTrue(res._2.size == 2)
+
+    assertEquals(1,res._2.size)
 
   }