fixed doiboost mapping and workflows

dhp-schemas/src/main/java/eu/dnetlib/dhp/schema/orcid/OrcidDOI.java

@@ -1,24 +1,25 @@
+
 package eu.dnetlib.dhp.schema.orcid;
 
 import java.util.List;
 
 public class OrcidDOI {
-    private String doi;
-    private List<AuthorData> authors;
+	private String doi;
+	private List<AuthorData> authors;
 
-    public String getDoi() {
-        return doi;
-    }
+	public String getDoi() {
+		return doi;
+	}
 
-    public void setDoi(String doi) {
-        this.doi = doi;
-    }
+	public void setDoi(String doi) {
+		this.doi = doi;
+	}
 
-    public List<AuthorData> getAuthors() {
-        return authors;
-    }
+	public List<AuthorData> getAuthors() {
+		return authors;
+	}
 
-    public void setAuthors(List<AuthorData> authors) {
-        this.authors = authors;
-    }
+	public void setAuthors(List<AuthorData> authors) {
+		this.authors = authors;
+	}
 }

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

@@ -62,7 +62,7 @@ object SparkGenerateDoiBoost {
     val orcidPublication: Dataset[(String, Publication)] = spark.read.load(s"$workingDirPath/orcidPublication").as[Publication].map(p => (p.getId, p))
     fj.joinWith(orcidPublication, fj("_1").equalTo(orcidPublication("_1")), "left").map(applyMerge).write.mode(SaveMode.Overwrite).save(s"$workingDirPath/secondJoin")
 
-    logger.info("Phase 3) Join Result with MAG")
+    logger.info("Phase 4) Join Result with MAG")
     val sj: Dataset[(String, Publication)] = spark.read.load(s"$workingDirPath/secondJoin").as[Publication].map(p => (p.getId, p))
 
     val magPublication: Dataset[(String, Publication)] = spark.read.load(s"$workingDirPath/magPublication").as[Publication].map(p => (p.getId, p))

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

@@ -21,15 +21,17 @@ object SparkImportMagIntoDataset {
 
 
   val stream = Map(
-    "Affiliations" -> Tuple2("mag/Affiliations.txt", Seq("AffiliationId:long", "Rank:uint", "NormalizedName:string", "DisplayName:string", "GridId:string", "OfficialPage:string", "WikiPage:string", "PaperCount:long", "CitationCount:long", "Latitude:float?", "Longitude:float?", "CreatedDate:DateTime")),
-    "Authors" -> Tuple2("mag/Authors.txt", Seq("AuthorId:long", "Rank:uint", "NormalizedName:string", "DisplayName:string", "LastKnownAffiliationId:long?", "PaperCount: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", "CitationCount:long", "Latitude:float?", "Longitude:float?", "CreatedDate:DateTime")),
+    "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")),
     "ConferenceSeries" -> Tuple2("mag/ConferenceSeries.txt", Seq("ConferenceSeriesId:long", "Rank:uint", "NormalizedName:string", "DisplayName:string", "PaperCount: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", "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", "CitationCount:long", "CreatedDate:DateTime")),
+    //                                                         ['FieldOfStudyId:long', 'Rank:uint', 'NormalizedName:string', 'DisplayName:string', 'MainType:string', 'Level:int', 'PaperCount:long', 'PaperFamilyCount:long', 'CitationCount:long', 'CreatedDate:DateTime']
+    "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")),
     "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")),
@@ -39,7 +41,7 @@ object SparkImportMagIntoDataset {
     "PaperReferences" -> Tuple2("mag/PaperReferences.txt", Seq("PaperId:long", "PaperReferenceId:long")),
     "PaperResources" -> Tuple2("mag/PaperResources.txt", Seq("PaperId:long", "ResourceType:int", "ResourceUrl:string", "SourceUrl:string", "RelationshipType:int")),
     "PaperUrls" -> Tuple2("mag/PaperUrls.txt", Seq("PaperId:long", "SourceType:int?", "SourceUrl:string", "LanguageCode:string")),
-    "Papers" -> Tuple2("mag/Papers.txt", Seq("PaperId:long", "Rank:uint", "Doi:string", "DocType:string", "PaperTitle:string", "OriginalTitle:string", "BookTitle:string", "Year:int?", "Date:DateTime?", "Publisher:string", "JournalId:long?", "ConferenceSeriesId:long?", "ConferenceInstanceId:long?", "Volume:string", "Issue:string", "FirstPage:string", "LastPage:string", "ReferenceCount:long", "CitationCount:long", "EstimatedCitation:long", "OriginalVenue:string", "FamilyId:long?", "CreatedDate:DateTime")),
+    "Papers" -> Tuple2("mag/Papers.txt", Seq("PaperId:long", "Rank:uint", "Doi:string", "DocType:string", "PaperTitle:string", "OriginalTitle:string", "BookTitle:string", "Year:int?", "Date:DateTime?", "OnlineDate:DateTime?", "Publisher:string", "JournalId:long?", "ConferenceSeriesId:long?", "ConferenceInstanceId:long?", "Volume:string", "Issue:string", "FirstPage:string", "LastPage:string", "ReferenceCount:long", "CitationCount:long", "EstimatedCitation:long", "OriginalVenue:string", "FamilyId:long?", "FamilyRank:uint?", "CreatedDate:DateTime")),
     "RelatedFieldOfStudy" -> Tuple2("advanced/RelatedFieldOfStudy.txt", Seq("FieldOfStudyId1:long", "Type1:string", "FieldOfStudyId2:long", "Type2:string", "Rank:float"))
   )
 

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

@@ -26,12 +26,15 @@ object SparkPreProcessMAG {
         .master(parser.get("master")).getOrCreate()
 
     val sourcePath = parser.get("sourcePath")
+    val workingPath = parser.get("workingPath")
+    val targetPath = parser.get("targetPath")
+
     import spark.implicits._
     implicit val mapEncoderPubs: Encoder[Publication] = org.apache.spark.sql.Encoders.kryo[Publication]
     implicit val tupleForJoinEncoder: Encoder[(String, Publication)] = Encoders.tuple(Encoders.STRING, mapEncoderPubs)
 
     logger.info("Phase 1) make uninque DOI in Papers:")
-    val d: Dataset[MagPapers] = spark.read.load(s"${parser.get("sourcePath")}/Papers").as[MagPapers]
+    val d: Dataset[MagPapers] = spark.read.load(s"$sourcePath/Papers").as[MagPapers]
 
     // Filtering Papers with DOI, and since for the same DOI we have multiple version of item with different PapersId we get the last one
     val result: RDD[MagPapers] = d.where(col("Doi").isNotNull)
@@ -41,11 +44,12 @@ object SparkPreProcessMAG {
       .map(_._2)
 
     val distinctPaper: Dataset[MagPapers] = spark.createDataset(result)
-    distinctPaper.write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/Papers_distinct")
+
+    distinctPaper.write.mode(SaveMode.Overwrite).save(s"$workingPath/Papers_distinct")
 
     logger.info("Phase 0) Enrich Publication with description")
-    val pa = spark.read.load(s"${parser.get("sourcePath")}/PaperAbstractsInvertedIndex").as[MagPaperAbstract]
-    pa.map(ConversionUtil.transformPaperAbstract).write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/PaperAbstract")
+    val pa = spark.read.load(s"$sourcePath/PaperAbstractsInvertedIndex").as[MagPaperAbstract]
+    pa.map(ConversionUtil.transformPaperAbstract).write.mode(SaveMode.Overwrite).save(s"$workingPath/PaperAbstract")
 
     logger.info("Phase 3) Group Author by PaperId")
     val authors = spark.read.load(s"$sourcePath/Authors").as[MagAuthor]
@@ -64,24 +68,24 @@ object SparkPreProcessMAG {
         } else
           mpa
       }).groupBy("PaperId").agg(collect_list(struct($"author", $"affiliation")).as("authors"))
-      .write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/merge_step_1_paper_authors")
+      .write.mode(SaveMode.Overwrite).save(s"$workingPath/merge_step_1_paper_authors")
 
     logger.info("Phase 4) create First Version of publication Entity with Paper Journal and Authors")
 
     val journals = spark.read.load(s"$sourcePath/Journals").as[MagJournal]
 
-    val papers = spark.read.load((s"${parser.get("targetPath")}/Papers_distinct")).as[MagPapers]
+    val papers = spark.read.load((s"$workingPath/Papers_distinct")).as[MagPapers]
 
-    val paperWithAuthors = spark.read.load(s"${parser.get("targetPath")}/merge_step_1_paper_authors").as[MagPaperWithAuthorList]
+    val paperWithAuthors = spark.read.load(s"$workingPath/merge_step_1_paper_authors").as[MagPaperWithAuthorList]
 
     val firstJoin = papers.joinWith(journals, papers("JournalId").equalTo(journals("JournalId")), "left")
     firstJoin.joinWith(paperWithAuthors, firstJoin("_1.PaperId").equalTo(paperWithAuthors("PaperId")), "left")
       .map { a => ConversionUtil.createOAFFromJournalAuthorPaper(a) }
-      .write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/merge_step_2")
+      .write.mode(SaveMode.Overwrite).save(s"$workingPath/merge_step_2")
 
 
     var magPubs: Dataset[(String, Publication)] =
-      spark.read.load(s"${parser.get("targetPath")}/merge_step_2").as[Publication]
+      spark.read.load(s"$workingPath/merge_step_2").as[Publication]
       .map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p)).as[(String, Publication)]
 
 
@@ -95,10 +99,10 @@ object SparkPreProcessMAG {
       .map(item => ConversionUtil.updatePubsWithConferenceInfo(item))
       .write
       .mode(SaveMode.Overwrite)
-      .save(s"${parser.get("targetPath")}/merge_step_2_conference")
+      .save(s"$workingPath/merge_step_2_conference")
 
 
-    magPubs= spark.read.load(s"${parser.get("targetPath")}/merge_step_2_conference").as[Publication]
+    magPubs= spark.read.load(s"$workingPath/merge_step_2_conference").as[Publication]
       .map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p)).as[(String, Publication)]
 
     val paperUrlDataset = spark.read.load(s"$sourcePath/PaperUrls").as[MagPaperUrl].groupBy("PaperId").agg(collect_list(struct("sourceUrl")).as("instances")).as[MagUrl]
@@ -108,27 +112,27 @@ object SparkPreProcessMAG {
     magPubs.joinWith(paperUrlDataset, col("_1").equalTo(paperUrlDataset("PaperId")), "left")
       .map { a: ((String, Publication), MagUrl) => ConversionUtil.addInstances((a._1._2, a._2)) }
       .write.mode(SaveMode.Overwrite)
-      .save(s"${parser.get("targetPath")}/merge_step_3")
+      .save(s"$workingPath/merge_step_3")
 
 
 //    logger.info("Phase 6) Enrich Publication with description")
 //    val pa = spark.read.load(s"${parser.get("sourcePath")}/PaperAbstractsInvertedIndex").as[MagPaperAbstract]
 //    pa.map(ConversionUtil.transformPaperAbstract).write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/PaperAbstract")
 
-    val paperAbstract = spark.read.load((s"${parser.get("targetPath")}/PaperAbstract")).as[MagPaperAbstract]
+    val paperAbstract = spark.read.load((s"$workingPath/PaperAbstract")).as[MagPaperAbstract]
 
 
-    magPubs = spark.read.load(s"${parser.get("targetPath")}/merge_step_3").as[Publication]
+    magPubs = spark.read.load(s"$workingPath/merge_step_3").as[Publication]
       .map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p)).as[(String, Publication)]
 
     magPubs.joinWith(paperAbstract, col("_1").equalTo(paperAbstract("PaperId")), "left")
       .map(item => ConversionUtil.updatePubsWithDescription(item)
-    ).write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/merge_step_4")
+    ).write.mode(SaveMode.Overwrite).save(s"$workingPath/merge_step_4")
 
 
     logger.info("Phase 7) Enrich Publication with FieldOfStudy")
 
-    magPubs = spark.read.load(s"${parser.get("targetPath")}/merge_step_4").as[Publication]
+    magPubs = spark.read.load(s"$workingPath/merge_step_4").as[Publication]
       .map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p)).as[(String, Publication)]
 
     val fos = spark.read.load(s"$sourcePath/FieldsOfStudy").select($"FieldOfStudyId".alias("fos"), $"DisplayName", $"MainType")
@@ -144,14 +148,14 @@ object SparkPreProcessMAG {
       .equalTo(paperField("PaperId")), "left")
       .map(item => ConversionUtil.updatePubsWithSubject(item))
       .write.mode(SaveMode.Overwrite)
-      .save(s"${parser.get("targetPath")}/mag_publication")
+      .save(s"$workingPath/mag_publication")
 
 
-    val s:RDD[Publication] = spark.read.load(s"${parser.get("targetPath")}/mag_publication").as[Publication]
+    val s:RDD[Publication] = spark.read.load(s"$workingPath/mag_publication").as[Publication]
       .map(p=>Tuple2(p.getId, p)).rdd.reduceByKey((a:Publication, b:Publication) => ConversionUtil.mergePublication(a,b))
     .map(_._2)
 
-    spark.createDataset(s).as[Publication].write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/mag_publication_u")
+    spark.createDataset(s).as[Publication].write.mode(SaveMode.Overwrite).save(s"$targetPath/magPublication")
 
   }
 }

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

@@ -1,6 +1,7 @@
 package eu.dnetlib.doiboost.orcid
 
-import eu.dnetlib.dhp.schema.oaf.{Author, Publication}
+import eu.dnetlib.dhp.schema.oaf.{Author, DataInfo, Publication}
+import eu.dnetlib.dhp.schema.orcid.OrcidDOI
 import eu.dnetlib.doiboost.DoiBoostMappingUtil
 import eu.dnetlib.doiboost.DoiBoostMappingUtil.{ORCID, PID_TYPES, createSP, generateDataInfo, generateIdentifier}
 import org.apache.commons.lang.StringUtils
@@ -43,16 +44,19 @@ object ORCIDToOAF {
   }
 
 
-  def convertTOOAF(input:ORCIDElement) :Publication = {
-    val doi = input.doi
+  def convertTOOAF(input:OrcidDOI) :Publication = {
+    val doi = input.getDoi
     val pub:Publication = new Publication
-    pub.setPid(List(createSP(doi, "doi", PID_TYPES)).asJava)
+    pub.setPid(List(createSP(doi.toLowerCase, "doi", PID_TYPES)).asJava)
     pub.setDataInfo(generateDataInfo())
     pub.setId(generateIdentifier(pub, doi.toLowerCase))
     try{
-      pub.setAuthor(input.authors.map(a=> {
-        generateAuthor(a.name, a.surname, a.creditName, a.oid)
-      }).asJava)
+
+      val l:List[Author]= input.getAuthors.asScala.map(a=> {
+              generateAuthor(a.getName, a.getSurname, a.getCreditName, a.getOid)
+            })(collection.breakOut)
+
+      pub.setAuthor(l.asJava)
       pub.setCollectedfrom(List(DoiBoostMappingUtil.createORIDCollectedFrom()).asJava)
       pub.setDataInfo(DoiBoostMappingUtil.generateDataInfo())
       pub
@@ -63,6 +67,13 @@ object ORCIDToOAF {
     }
   }
 
+  def generateOricPIDDatainfo():DataInfo = {
+    val di =DoiBoostMappingUtil.generateDataInfo("0.91")
+    di.getProvenanceaction.setClassid("sysimport:crosswalk:entityregistry")
+    di.getProvenanceaction.setClassname("Harvested")
+    di
+  }
+
   def generateAuthor(given: String, family: String, fullName:String, orcid: String): Author = {
     val a = new Author
     a.setName(given)
@@ -72,7 +83,7 @@ object ORCIDToOAF {
     else
       a.setFullname(s"$given $family")
     if (StringUtils.isNotBlank(orcid))
-      a.setPid(List(createSP(orcid, ORCID, PID_TYPES)).asJava)
+      a.setPid(List(createSP(orcid, ORCID, PID_TYPES, generateOricPIDDatainfo())).asJava)
 
     a
   }

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

@@ -1,21 +1,72 @@
 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 eu.dnetlib.doiboost.mag.ConversionUtil
 import org.apache.commons.io.IOUtils
 import org.apache.spark.SparkConf
 import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.expressions.Aggregator
 import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
 import org.slf4j.{Logger, LoggerFactory}
 
 object SparkConvertORCIDToOAF {
+  val logger: Logger = LoggerFactory.getLogger(SparkConvertORCIDToOAF.getClass)
 
+  def getPublicationAggregator(): Aggregator[(String, Publication), Publication, Publication] = new Aggregator[(String, Publication), Publication, Publication]{
 
+    override def zero: Publication = new Publication()
+
+    override def reduce(b: Publication, a: (String, Publication)): Publication = {
+      b.mergeFrom(a._2)
+      b.setAuthor(AuthorMerger.mergeAuthor(a._2.getAuthor, b.getAuthor))
+      if (b.getId == null)
+        b.setId(a._2.getId)
+      b
+    }
+
+
+    override def merge(wx: Publication, wy: Publication): Publication = {
+      wx.mergeFrom(wy)
+      wx.setAuthor(AuthorMerger.mergeAuthor(wy.getAuthor, wx.getAuthor))
+      if(wx.getId == null && wy.getId.nonEmpty)
+        wx.setId(wy.getId)
+      wx
+    }
+    override def finish(reduction: Publication): Publication = reduction
+
+    override def bufferEncoder: Encoder[Publication] =
+      Encoders.kryo(classOf[Publication])
+
+    override def outputEncoder: Encoder[Publication] =
+      Encoders.kryo(classOf[Publication])
+  }
+
+def run(spark:SparkSession,sourcePath:String, targetPath:String):Unit = {
+  implicit val mapEncoderPubs: Encoder[Publication] = Encoders.kryo[Publication]
+  implicit val mapOrcid: Encoder[OrcidDOI] = Encoders.kryo[OrcidDOI]
+  implicit val tupleForJoinEncoder: Encoder[(String, Publication)] = Encoders.tuple(Encoders.STRING, mapEncoderPubs)
+
+  val mapper = new ObjectMapper()
+  mapper.getDeserializationConfig.withFeatures(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES)
+
+  val dataset:Dataset[OrcidDOI] = spark.createDataset(spark.sparkContext.textFile(sourcePath).map(s => mapper.readValue(s,classOf[OrcidDOI])))
+
+  logger.info("Converting ORCID to OAF")
+  dataset.map(o => ORCIDToOAF.convertTOOAF(o)).filter(p=>p!=null)
+    .map(d => (d.getId, d))
+    .groupByKey(_._1)(Encoders.STRING)
+    .agg(getPublicationAggregator().toColumn)
+    .map(p => p._2)
+    .write.mode(SaveMode.Overwrite).save(targetPath)
+}
 
   def main(args: Array[String]): Unit = {
 
-    val logger: Logger = LoggerFactory.getLogger(SparkConvertORCIDToOAF.getClass)
+
     val conf: SparkConf = new SparkConf()
     val parser = new ArgumentApplicationParser(IOUtils.toString(SparkConvertORCIDToOAF.getClass.getResourceAsStream("/eu/dnetlib/dhp/doiboost/convert_map_to_oaf_params.json")))
     parser.parseArgument(args)
@@ -26,19 +77,12 @@ object SparkConvertORCIDToOAF {
         .appName(getClass.getSimpleName)
         .master(parser.get("master")).getOrCreate()
 
-    implicit val mapEncoderPubs: Encoder[Publication] = Encoders.kryo[Publication]
-    implicit val tupleForJoinEncoder: Encoder[(String, Publication)] = Encoders.tuple(Encoders.STRING, mapEncoderPubs)
-    import spark.implicits._
-    val sourcePath = parser.get("sourcePath")
-    val targetPath = parser.get("targetPath")
-    val dataset:Dataset[ORCIDElement] = spark.read.json(sourcePath).as[ORCIDElement]
 
 
-    logger.info("Converting ORCID to OAF")
-    val d:RDD[Publication] = dataset.map(o => ORCIDToOAF.convertTOOAF(o)).filter(p=>p!=null).map(p=>(p.getId,p)).rdd.reduceByKey(ConversionUtil.mergePublication)
-      .map(_._2)
+    val sourcePath = parser.get("sourcePath")
+    val targetPath = parser.get("targetPath")
+    run(spark, sourcePath, targetPath)
 
-    spark.createDataset(d).as[Publication].write.mode(SaveMode.Overwrite).save(targetPath)
   }
 
 }

dhp-workflows/dhp-doiboost/src/main/resources/eu/dnetlib/dhp/doiboost/intersection/oozie_app/workflow.xml

@@ -39,14 +39,7 @@
         <message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
     </kill>
 
-    <action name="ResetWorkingPath">
-        <fs>
-            <delete path='${workingDirPath}'/>
-            <mkdir path='${workingDirPath}'/>
-        </fs>
-        <ok to="CreateDOIBoost"/>
-        <error to="Kill"/>
-    </action>
+
 
     <action name="CreateDOIBoost">
         <spark xmlns="uri:oozie:spark-action:0.2">

dhp-workflows/dhp-doiboost/src/main/resources/eu/dnetlib/dhp/doiboost/mag/oozie_app/workflow.xml

@@ -8,6 +8,10 @@
             <name>targetPath</name>
             <description>the working dir base path</description>
         </property>
+        <property>
+            <name>workingPath</name>
+            <description>the working dir base path</description>
+        </property>
         <property>
             <name>sparkDriverMemory</name>
             <description>memory for driver process</description>
@@ -31,10 +35,10 @@
 
     <action name="ResetWorkingPath">
         <fs>
-            <delete path='${targetPath}'/>
-            <mkdir path='${targetPath}'/>
+            <delete path='${workingPath}'/>
+            <mkdir path='${workingPath}'/>
         </fs>
-        <ok to="PreprocessMag"/>
+        <ok to="ConvertMagToDataset"/>
         <error to="Kill"/>
     </action>
 
@@ -52,10 +56,10 @@
                 ${sparkExtraOPT}
             </spark-opts>
             <arg>--sourcePath</arg><arg>${sourcePath}</arg>
-            <arg>--targetPath</arg><arg>${targetPath}</arg>
+            <arg>--targetPath</arg><arg>${workingPath}</arg>
             <arg>--master</arg><arg>yarn-cluster</arg>
         </spark>
-        <ok to="End"/>
+        <ok to="PreprocessMag"/>
         <error to="Kill"/>
     </action>
 
@@ -65,7 +69,7 @@
         <spark xmlns="uri:oozie:spark-action:0.2">
             <master>yarn-cluster</master>
             <mode>cluster</mode>
-            <name>Convert Mag to Dataset</name>
+            <name>Convert Mag to OAF Dataset</name>
             <class>eu.dnetlib.doiboost.mag.SparkPreProcessMAG</class>
             <jar>dhp-doiboost-${projectVersion}.jar</jar>
             <spark-opts>
@@ -75,7 +79,8 @@
                 --conf spark.sql.shuffle.partitions=3840
                 ${sparkExtraOPT}
             </spark-opts>
-            <arg>--sourcePath</arg><arg>${sourcePath}</arg>
+            <arg>--sourcePath</arg><arg>${workingPath}</arg>
+            <arg>--workingPath</arg><arg>${workingPath}/process</arg>
             <arg>--targetPath</arg><arg>${targetPath}</arg>
             <arg>--master</arg><arg>yarn-cluster</arg>
         </spark>

dhp-workflows/dhp-doiboost/src/main/resources/eu/dnetlib/dhp/doiboost/mag/preprocess_mag_params.json

@@ -1,6 +1,7 @@
 [
   {"paramName":"s",   "paramLongName":"sourcePath", "paramDescription": "the base path of MAG input",  "paramRequired": true},
-  {"paramName":"t",   "paramLongName":"targetPath", "paramDescription": "the working dir path",                      "paramRequired": true},
+  {"paramName":"t",   "paramLongName":"targetPath", "paramDescription": "the target dir path",                      "paramRequired": true},
+  {"paramName":"w",   "paramLongName":"workingPath", "paramDescription": "the working dir path",                      "paramRequired": true},
   {"paramName":"m",   "paramLongName":"master",     "paramDescription": "the master name",                          "paramRequired": true}
 
 ]

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

@@ -1,5 +1,8 @@
 package eu.dnetlib.doiboost.orcid
 
+import eu.dnetlib.dhp.schema.oaf.Publication
+import eu.dnetlib.doiboost.orcid.SparkConvertORCIDToOAF.getClass
+import org.apache.spark.sql.{Encoder, Encoders, SparkSession}
 import org.codehaus.jackson.map.ObjectMapper
 import org.junit.jupiter.api.Assertions._
 import org.junit.jupiter.api.Test
@@ -21,6 +24,30 @@ class MappingORCIDToOAFTest {
     })
   }
 
+//  @Test
+//  def testOAFConvert():Unit ={
+//
+//    val spark: SparkSession =
+//      SparkSession
+//        .builder()
+//        .appName(getClass.getSimpleName)
+//        .master("local[*]").getOrCreate()
+//
+//
+//    SparkConvertORCIDToOAF.run( spark,"/Users/sandro/Downloads/orcid", "/Users/sandro/Downloads/orcid_oaf")
+//    implicit val mapEncoderPubs: Encoder[Publication] = Encoders.kryo[Publication]
+//
+//    val df = spark.read.load("/Users/sandro/Downloads/orcid_oaf").as[Publication]
+//    println(df.first.getId)
+//    println(mapper.writeValueAsString(df.first()))
+//
+//
+//
+//
+//  }
+
+
+