Merge branch 'doiboost' of https://code-repo.d4science.org/D-Net/dnet-hadoop into doiboost

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

@@ -21,11 +21,15 @@ object DoiBoostMappingUtil {
 
 
   def generateDataInfo(): DataInfo = {
+    generateDataInfo("0.9")
+  }
+
+  def generateDataInfo(trust:String): DataInfo = {
     val di = new DataInfo
     di.setDeletedbyinference(false)
     di.setInferred(false)
     di.setInvisible(false)
-    di.setTrust("0.9")
+    di.setTrust(trust)
     di.setProvenanceaction(createQualifier("sysimport:actionset", "dnet:provenanceActions"))
     di
   }

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

@@ -137,9 +137,21 @@ case object Crossref2Oaf {
     if (StringUtils.isNotBlank(issuedDate)) {
       result.setDateofacceptance(asField(issuedDate))
     }
+    else {
+      result.setDateofacceptance(asField(createdDate.getValue))
+    }
     result.setRelevantdate(List(createdDate, postedDate, acceptedDate, publishedOnlineDate, publishedPrintDate).filter(p => p != null).asJava)
 
 
+    //Mapping Subject
+    val subjectList:List[String] = (json \ "subject").extractOrElse[List[String]](List())
+
+    if (subjectList.nonEmpty) {
+      result.setSubject(subjectList.map(s=> createSP(s, "keywords", "dnet:subject_classification_typologies")).asJava)
+    }
+
+
+
     //Mapping AUthor
     val authorList: List[mappingAuthor] = (json \ "author").extractOrElse[List[mappingAuthor]](List())
     result.setAuthor(authorList.map(a => generateAuhtor(a.given.orNull, a.family, a.ORCID.orNull)).asJava)
@@ -224,6 +236,16 @@ case object Crossref2Oaf {
     val queue = new mutable.Queue[Relation]
 
 
+    def snfRule(award:String): String = {
+      var tmp1 = StringUtils.substringAfter(award,"_")
+      val tmp2 = StringUtils.substringBefore(tmp1,"/")
+      logger.debug(s"From $award to $tmp2")
+      tmp2
+
+
+    }
+
+
     def extractECAward(award: String): String = {
       val awardECRegex: Regex = "[0-9]{4,9}".r
       if (awardECRegex.findAllIn(award).hasNext)
@@ -289,7 +311,7 @@ case object Crossref2Oaf {
           case "10.13039/501100006588" |
                 "10.13039/501100004488" =>  generateSimpleRelationFromAward(funder, "irb_hr______", a=>a.replaceAll("Project No.", "").replaceAll("HRZZ-","") )
           case "10.13039/501100006769"=>    generateSimpleRelationFromAward(funder, "rsf_________", a=>a)
-          case "10.13039/501100001711"=>    generateSimpleRelationFromAward(funder, "snsf________", extractECAward)
+          case "10.13039/501100001711"=>    generateSimpleRelationFromAward(funder, "snsf________", snfRule)
           case "10.13039/501100004410"=>    generateSimpleRelationFromAward(funder, "tubitakf____", a =>a)
           case "10.10.13039/100004440"=>    generateSimpleRelationFromAward(funder, "wt__________", a =>a)
           case "10.13039/100004440"=>       queue += generateRelation(sourceId,"1e5e62235d094afd01cd56e65112fc63", "wt__________" )

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

@@ -40,6 +40,9 @@ case class MagPaperUrl(PaperId: Long, SourceType: Option[Int], SourceUrl: Option
 
 case class MagUrl(PaperId: Long, instances: List[String])
 
+case class MagSubject(FieldOfStudyId:Long, DisplayName:String, MainType:Option[String], Score:Float){}
+
+case class MagFieldOfStudy(PaperId:Long, subjects:List[MagSubject]) {}
 
 case class MagJournal(JournalId: Long, Rank: Option[Int], NormalizedName: Option[String], DisplayName: Option[String], Issn: Option[String], Publisher: Option[String], Webpage: Option[String], PaperCount: Option[Long], CitationCount: Option[Long], CreatedDate: Option[java.sql.Timestamp]) {}
 
@@ -135,6 +138,8 @@ case object ConversionUtil {
         j.setIssnPrinted(journal.Issn.get)
       pub.setJournal(j)
     }
+    pub.setCollectedfrom(List(createMAGCollectedFrom()).asJava)
+    pub.setDataInfo(generateDataInfo())
     pub
   }
 

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

@@ -1,20 +1,18 @@
 package eu.dnetlib.doiboost.mag
 
 import eu.dnetlib.dhp.application.ArgumentApplicationParser
-import eu.dnetlib.dhp.schema.oaf.Publication
+import eu.dnetlib.dhp.schema.oaf.{Publication, StructuredProperty}
-import eu.dnetlib.doiboost.DoiBoostMappingUtil.asField
+import eu.dnetlib.doiboost.DoiBoostMappingUtil
+import eu.dnetlib.doiboost.DoiBoostMappingUtil.{asField, createSP}
 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.slf4j.{Logger, LoggerFactory}
 import org.apache.spark.sql.functions._
-
 import scala.collection.JavaConverters._
 
 object SparkPreProcessMAG {
-
-
   def main(args: Array[String]): Unit = {
 
     val logger: Logger = LoggerFactory.getLogger(getClass)
@@ -31,15 +29,11 @@ object SparkPreProcessMAG {
     val sourcePath = parser.get("sourcePath")
     import spark.implicits._
     implicit val mapEncoderPubs: Encoder[Publication] = org.apache.spark.sql.Encoders.kryo[Publication]
-    implicit val tupleForJoinEncoder = Encoders.tuple(Encoders.STRING, mapEncoderPubs)
+    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]
 
-
     // 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).rdd.map { p: MagPapers => Tuple2(p.Doi, p) }.reduceByKey { case (p1: MagPapers, p2: MagPapers) =>
       var r = if (p1 == null) p2 else p1
@@ -56,6 +50,8 @@ object SparkPreProcessMAG {
       r
     }.map(_._2)
 
+
+
     val distinctPaper: Dataset[MagPapers] = spark.createDataset(result)
     distinctPaper.write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/Papers_distinct")
     logger.info(s"Total number of element: ${result.count()}")
@@ -63,44 +59,36 @@ object SparkPreProcessMAG {
     logger.info("Phase 3) Group Author by PaperId")
     val authors = spark.read.load(s"$sourcePath/Authors").as[MagAuthor]
 
-    val affiliation =spark.read.load(s"$sourcePath/Affiliations").as[MagAffiliation]
+    val affiliation = spark.read.load(s"$sourcePath/Affiliations").as[MagAffiliation]
-
+    val paperAuthorAffiliation = spark.read.load(s"$sourcePath/PaperAuthorAffiliations").as[MagPaperAuthorAffiliation]
-    val paperAuthorAffiliation =spark.read.load(s"$sourcePath/PaperAuthorAffiliations").as[MagPaperAuthorAffiliation]
-
 
     paperAuthorAffiliation.joinWith(authors, paperAuthorAffiliation("AuthorId").equalTo(authors("AuthorId")))
-      .map{case (a:MagPaperAuthorAffiliation,b:MagAuthor )=>  (a.AffiliationId,MagPaperAuthorDenormalized(a.PaperId, b, null)) }
+      .map { case (a: MagPaperAuthorAffiliation, b: MagAuthor) => (a.AffiliationId, MagPaperAuthorDenormalized(a.PaperId, b, null)) }
       .joinWith(affiliation, affiliation("AffiliationId").equalTo(col("_1")), "left")
       .map(s => {
-          val mpa = s._1._2
+        val mpa = s._1._2
-          val af = s._2
+        val af = s._2
-          if (af!= null) {
+        if (af != null) {
-            MagPaperAuthorDenormalized(mpa.PaperId, mpa.author, af.DisplayName)
+          MagPaperAuthorDenormalized(mpa.PaperId, mpa.author, af.DisplayName)
-          } else
+        } else
-            mpa
+          mpa
-        }).groupBy("PaperId").agg(collect_list(struct($"author", $"affiliation")).as("authors"))
+      }).groupBy("PaperId").agg(collect_list(struct($"author", $"affiliation")).as("authors"))
       .write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/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"${parser.get("targetPath")}/Papers_distinct")).as[MagPapers]
+    val papers = spark.read.load((s"${parser.get("targetPath")}/Papers_distinct")).as[MagPapers]
 
     val paperWithAuthors = spark.read.load(s"${parser.get("targetPath")}/merge_step_1_paper_authors").as[MagPaperWithAuthorList]
 
-
+    val firstJoin = papers.joinWith(journals, papers("JournalId").equalTo(journals("JournalId")), "left")
-
-    val firstJoin =papers.joinWith(journals, papers("JournalId").equalTo(journals("JournalId")),"left")
     firstJoin.joinWith(paperWithAuthors, firstJoin("_1.PaperId").equalTo(paperWithAuthors("PaperId")), "left")
       .map { a: ((MagPapers, MagJournal), MagPaperWithAuthorList) => ConversionUtil.createOAFFromJournalAuthorPaper(a) }.write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/merge_step_2")
 
 
-
+    var magPubs: Dataset[(String, Publication)] = spark.read.load(s"${parser.get("targetPath")}/merge_step_2").as[Publication].map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p)).as[(String, Publication)]
-    var magPubs:Dataset[(String,Publication)] = spark.read.load(s"${parser.get("targetPath")}/merge_step_2").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]
 
@@ -108,33 +96,69 @@ object SparkPreProcessMAG {
     logger.info("Phase 5) enrich publication with URL and Instances")
 
     magPubs.joinWith(paperUrlDataset, col("_1").equalTo(paperUrlDataset("PaperId")), "left")
-      .map{a:((String,Publication), MagUrl) => ConversionUtil.addInstances((a._1._2, a._2))}
+      .map { a: ((String, Publication), MagUrl) => ConversionUtil.addInstances((a._1._2, a._2)) }
       .write.mode(SaveMode.Overwrite)
       .save(s"${parser.get("targetPath")}/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"${parser.get("targetPath")}/PaperAbstract")).as[MagPaperAbstract]
+    val paperAbstract = spark.read.load((s"${parser.get("targetPath")}/PaperAbstract")).as[MagPaperAbstract]
 
 
-    magPubs = spark.read.load(s"${parser.get("targetPath")}/merge_step_3").as[Publication].map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p)).as[(String,Publication)]
+    magPubs = spark.read.load(s"${parser.get("targetPath")}/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(p=>
+    magPubs.joinWith(paperAbstract, col("_1").equalTo(paperAbstract("PaperId")), "left").map(p => {
-      {
+      val pub = p._1._2
-        val pub = p._1._2
+      val abst = p._2
-        val abst = p._2
+      if (abst != null) {
-        if (abst!= null) {
+        pub.setDescription(List(asField(abst.IndexedAbstract)).asJava)
-          pub.setDescription(List(asField(abst.IndexedAbstract)).asJava)
+      }
+      pub
+    }
+    ).write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/merge_step_4")
+
+
+    logger.info("Phase 7) Enrich Publication with FieldOfStudy")
+
+    magPubs = spark.read.load(s"${parser.get("targetPath")}/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", $"MainType")
+
+    val pfos = spark.read.load(s"$sourcePath/PaperFieldsOfStudy")
+
+    val paperField = pfos.joinWith(fos, fos("fos").equalTo(pfos("FieldOfStudyId")))
+      .select($"_1.FieldOfStudyId", $"_2.DisplayName", $"_2.MainType", $"_1.PaperId", $"_1.Score")
+      .groupBy($"PaperId").agg(collect_list(struct($"FieldOfStudyId", $"DisplayName", $"MainType", $"Score")).as("subjects"))
+      .as[MagFieldOfStudy]
+
+    magPubs.joinWith(paperField, col("_1").equalTo(paperField("PaperId")), "left").
+      map(item => {
+        val publication = item._1._2
+        val fieldOfStudy = item._2
+        if (fieldOfStudy != null && fieldOfStudy.subjects != null && fieldOfStudy.subjects.nonEmpty) {
+          val p: List[StructuredProperty] = fieldOfStudy.subjects.flatMap(s => {
+            val s1 = createSP(s.DisplayName, "keywords", "dnet:subject_classification_typologies")
+            val di = DoiBoostMappingUtil.generateDataInfo(s.Score.toString)
+            var resList: List[StructuredProperty] = List(s1)
+            if (s.MainType.isDefined) {
+              val maintp = s.MainType.get
+              val s2 = createSP(s.MainType.get, "keywords", "dnet:subject_classification_typologies")
+              s2.setDataInfo(di)
+              resList = resList ::: List(s2)
+              if (maintp.contains(".")) {
+                val s3 = createSP(maintp.split("\\.").head, "keywords", "dnet:subject_classification_typologies")
+                s3.setDataInfo(di)
+                resList = resList ::: List(s3)
+              }
+            }
+            resList
+          })
+          publication.setSubject(p.asJava)
         }
-        pub
+        publication
-        }
+      }).map{s:Publication => s}(Encoders.bean(classOf[Publication])).write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/mag_publication")
-       ).write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/merge_step_4")
-
   }
-
-
 }

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

@@ -22,7 +22,7 @@
         </property>
     </parameters>
 
-    <start to="ResetWorkingPath"/>
+    <start to="PreprocessMag"/>
 
 
     <kill name="Kill">

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

@@ -90,9 +90,9 @@ class CrossrefMappingTest {
     val rels:List[Relation] = resultList.filter(p => p.isInstanceOf[Relation]).map(r=> r.asInstanceOf[Relation])
 
 
-    assertEquals(rels.size, 4)
-    rels.foreach(s => logger.info(s.getTarget))
 
+    rels.foreach(s => logger.info(s.getTarget))
+    assertEquals(rels.size, 3 )
 
 
   }

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

@@ -24,47 +24,21 @@ class MAGMappingTest {
   val mapper = new ObjectMapper()
 
 
+
+
   @Test
-  def testMAGCSV(): Unit = {
+  def testSplitter():Unit = {
-    // SparkPreProcessMAG.main("-m local[*] -s /data/doiboost/mag/datasets -t /data/doiboost/mag/datasets/preprocess".split(" "))
+    val s = "sports.team"
-
-    val sparkConf: SparkConf = new SparkConf
-
-    val spark: SparkSession = SparkSession.builder()
-      .config(sparkConf)
-      .appName(getClass.getSimpleName)
-      .master("local[*]")
-      .getOrCreate()
-
-    import spark.implicits._
 
 
-    implicit val mapEncoderPubs: Encoder[Publication] = org.apache.spark.sql.Encoders.kryo[Publication]
+    if (s.contains(".")) {
-    implicit val longBarEncoder = Encoders.tuple(Encoders.STRING, mapEncoderPubs)
+      println(s.split("\\.")head)
-
+    }
-    val sourcePath = "/data/doiboost/mag/input"
-
-    mapper.getSerializationConfig.enable(SerializationConfig.Feature.INDENT_OUTPUT)
-
-
-   val magOAF = spark.read.load("$sourcePath/merge_step_4").as[Publication]
-
-   println(magOAF.first().getOriginalId)
-
-
-   magOAF.map(k => (ConversionUtil.extractMagIdentifier(k.getOriginalId.asScala),k)).as[(String,Publication)].show()
-
-
-    println((ConversionUtil.extractMagIdentifier(magOAF.first().getOriginalId.asScala)))
-
-    val magIDRegex: Regex = "^[0-9]+$".r
-
-
-    println(magIDRegex.findFirstMatchIn("suca").isDefined)
 
   }
 
 
+
   @Test
   def buildInvertedIndexTest(): Unit = {
     val json_input = Source.fromInputStream(getClass.getResourceAsStream("invertedIndex.json")).mkString

dhp-workflows/dhp-doiboost/src/test/resources/eu/dnetlib/doiboost/awardTest.json

@@ -179,12 +179,13 @@
   ],
   "funder": [
     {
+      "DOI": "10.13039/501100001711",
+      "name": "Swiss National Science Foundation (Schweizerische Nationalfonds)",
       "doi-asserted-by": "publisher",
-      "DOI": "10.13039/501100000781",
-      "name": "European Research Council",
       "award": [
-        "284236-REPCOLLAB",
+        "CR32I3_156724",
-        "FP7/2007-2013"
+        "31003A_173281/1",
+        "200021_165850"
       ]
     }
   ],