dnet-hadoop/dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/collection/mag/MagUtility.scala

446 lines
13 KiB
Scala

package eu.dnetlib.dhp.collection.mag
import eu.dnetlib.dhp.schema.common.ModelConstants
import eu.dnetlib.dhp.schema.oaf.{Author, Journal, Publication}
import eu.dnetlib.dhp.schema.oaf.utils.{IdentifierFactory, PidType}
import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils._
import org.apache.spark.sql.types._
import org.apache.spark.sql.{Dataset, Row, SparkSession}
import org.json4s
import org.json4s.DefaultFormats
import org.json4s.jackson.JsonMethods.parse
import scala.collection.JavaConverters._
case class MAGPaper(
paperId: Option[Long],
doi: Option[String],
docType: Option[String],
paperTitle: Option[String],
originalTitle: Option[String],
bookTitle: Option[String],
year: Option[Int],
date: Option[String],
onlineDate: Option[String],
publisher: Option[String],
// Journal or Conference information (one will be populated)
journalId: Option[Long],
journalName: Option[String],
journalIssn: Option[String],
journalPublisher: Option[String],
conferenceSeriesId: Option[Long],
conferenceInstanceId: Option[Long],
conferenceName: Option[String],
conferenceLocation: Option[String],
conferenceStartDate: Option[String],
conferenceEndDate: Option[String],
volume: Option[String],
issue: Option[String],
firstPage: Option[String],
lastPage: Option[String],
referenceCount: Option[Long],
citationCount: Option[Long],
estimatedCitation: Option[Long],
originalVenue: Option[String],
familyId: Option[Long],
familyRank: Option[Int],
docSubTypes: Option[String],
createdDate: Option[String],
abstractText: Option[String],
// List of authors
authors: Option[List[MAGAuthor]],
urls: Option[List[String]]
)
case class MAGAuthor(
AffiliationId: Option[Long],
AuthorSequenceNumber: Option[Int],
AffiliationName: Option[String],
AuthorName: Option[String],
AuthorId: Option[Long],
GridId: Option[String]
)
object MagUtility extends Serializable {
val datatypedict = Map(
"bool" -> BooleanType,
"int" -> IntegerType,
"uint" -> IntegerType,
"long" -> LongType,
"ulong" -> LongType,
"float" -> FloatType,
"string" -> StringType,
"DateTime" -> DateType
)
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",
"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",
"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"
)
),
"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")
),
"PaperExtendedAttributes" -> Tuple2(
"mag/PaperExtendedAttributes.txt",
Seq("PaperId:long", "AttributeType:int", "AttributeValue:string")
),
"PaperFieldsOfStudy" -> Tuple2(
"advanced/PaperFieldsOfStudy.txt",
Seq("PaperId:long", "FieldOfStudyId:long", "Score:float")
),
"PaperMeSH" -> Tuple2(
"advanced/PaperMeSH.txt",
Seq(
"PaperId:long",
"DescriptorUI:string",
"DescriptorName:string",
"QualifierUI:string",
"QualifierName:string",
"IsMajorTopic:bool"
)
),
"PaperRecommendations" -> Tuple2(
"advanced/PaperRecommendations.txt",
Seq("PaperId:long", "RecommendedPaperId:long", "Score:float")
),
"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?",
"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?",
"DocSubTypes:string",
"CreatedDate:DateTime"
)
),
"RelatedFieldOfStudy" -> Tuple2(
"advanced/RelatedFieldOfStudy.txt",
Seq(
"FieldOfStudyId1:long",
"Type1:string",
"FieldOfStudyId2:long",
"Type2:string",
"Rank:float"
)
)
)
def getSchema(streamName: String): StructType = {
var schema = new StructType()
val d: Seq[String] = stream(streamName)._2
d.foreach { case t =>
val currentType = t.split(":")
val fieldName: String = currentType.head
var fieldType: String = currentType.last
val nullable: Boolean = fieldType.endsWith("?")
if (nullable)
fieldType = fieldType.replace("?", "")
schema = schema.add(StructField(fieldName, datatypedict(fieldType), nullable))
}
schema
}
def loadMagEntity(spark: SparkSession, entity: String, basePath: String): Dataset[Row] = {
if (stream.contains(entity)) {
val s = getSchema(entity)
val pt = stream(entity)._1
spark.read
.option("header", "false")
.option("charset", "UTF8")
.option("delimiter", "\t")
.schema(s)
.csv(s"$basePath/$pt")
} else
null
}
def convertMAGtoOAF(paper: MAGPaper): Publication = {
if (paper.doi.isDefined) {
val pub = new Publication
pub.setPid(
List(
structuredProperty(
paper.doi.get,
qualifier(
PidType.doi.toString,
PidType.doi.toString,
ModelConstants.DNET_PID_TYPES,
ModelConstants.DNET_PID_TYPES
),
null
)
).asJava
)
pub.setOriginalId(List(paper.paperId.get.toString, paper.doi.get).asJava)
//IMPORTANT
//The old method result.setId(generateIdentifier(result, doi))
//will be replaced using IdentifierFactory
pub.setId(IdentifierFactory.createDOIBoostIdentifier(pub))
val mainTitles = structuredProperty(paper.originalTitle.get, ModelConstants.MAIN_TITLE_QUALIFIER, null)
val originalTitles = structuredProperty(paper.paperTitle.get, ModelConstants.ALTERNATIVE_TITLE_QUALIFIER, null)
pub.setTitle(List(mainTitles, originalTitles).asJava)
if (paper.bookTitle.isDefined)
pub.setSource(List(field[String](paper.bookTitle.get, null)).asJava)
if (paper.abstractText.isDefined)
pub.setDescription(List(field(paper.abstractText.get, null)).asJava)
if (paper.authors.isDefined && paper.authors.get.nonEmpty) {
pub.setAuthor(
paper.authors.get
.filter(a => a.AuthorName.isDefined)
.map(a => {
val author = new Author
author.setFullname(a.AuthorName.get)
if (a.AffiliationName.isDefined)
author.setAffiliation(List(field(a.AffiliationName.get, null)).asJava)
author.setPid(
List(
structuredProperty(
s"https://academic.microsoft.com/#/detail/${a.AuthorId.get}",
qualifier("url", "url", ModelConstants.DNET_PID_TYPES, ModelConstants.DNET_PID_TYPES),
null
)
).asJava
)
author
})
.asJava
)
}
if (paper.date.isDefined)
pub.setDateofacceptance(field(paper.date.get, null))
if (paper.publisher.isDefined)
pub.setPublisher(field(paper.publisher.get, null))
if (paper.journalId.isDefined && paper.journalName.isDefined) {
val j = new Journal
j.setName(paper.journalName.get)
j.setSp(paper.firstPage.orNull)
j.setEp(paper.lastPage.orNull)
if (paper.publisher.isDefined)
pub.setPublisher(field(paper.publisher.get, null))
j.setIssnPrinted(paper.journalIssn.orNull)
j.setVol(paper.volume.orNull)
j.setIss(paper.issue.orNull)
j.setConferenceplace(paper.conferenceLocation.orNull)
j.setEdition(paper.conferenceName.orNull)
pub.setJournal(j)
}
pub
} else {
null
}
}
def convertInvertedIndexString(json_input: String): String = {
implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
lazy val json: json4s.JValue = parse(json_input)
val idl = (json \ "IndexLength").extract[Int]
if (idl > 0) {
val res = Array.ofDim[String](idl)
val iid = (json \ "InvertedIndex").extract[Map[String, List[Int]]]
for { (k: String, v: List[Int]) <- iid } {
v.foreach(item => res(item) = k)
}
(0 until idl).foreach(i => {
if (res(i) == null)
res(i) = ""
})
return res.mkString(" ")
}
""
}
}