merged manually changes on stable_id for doiboost into master

This commit is contained in:
Sandro La Bruzzo 2021-05-05 10:23:32 +02:00
parent a801999e75
commit 1adfc41d23
11 changed files with 321 additions and 239 deletions

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@ -6,7 +6,7 @@
<groupId>eu.dnetlib.dhp</groupId> <groupId>eu.dnetlib.dhp</groupId>
<artifactId>dhp</artifactId> <artifactId>dhp</artifactId>
<version>1.2.4-SNAPSHOT</version> <version>1.2.4-SNAPSHOT</version>
<relativePath>../</relativePath> <relativePath>../pom.xml</relativePath>
</parent> </parent>
<artifactId>dhp-common</artifactId> <artifactId>dhp-common</artifactId>

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@ -1,5 +1,6 @@
package eu.dnetlib.doiboost.crossref package eu.dnetlib.doiboost.crossref
import eu.dnetlib.dhp.schema.common.ModelConstants
import eu.dnetlib.dhp.schema.oaf._ import eu.dnetlib.dhp.schema.oaf._
import eu.dnetlib.dhp.utils.DHPUtils import eu.dnetlib.dhp.utils.DHPUtils
import eu.dnetlib.doiboost.DoiBoostMappingUtil._ import eu.dnetlib.doiboost.DoiBoostMappingUtil._
@ -13,12 +14,13 @@ import org.slf4j.{Logger, LoggerFactory}
import scala.collection.JavaConverters._ import scala.collection.JavaConverters._
import scala.collection.mutable import scala.collection.mutable
import scala.util.matching.Regex import scala.util.matching.Regex
import eu.dnetlib.dhp.schema.scholexplorer.OafUtils
case class CrossrefDT(doi: String, json:String, timestamp: Long) {} case class CrossrefDT(doi: String, json:String, timestamp: Long) {}
case class mappingAffiliation(name: String) {} case class mappingAffiliation(name: String) {}
case class mappingAuthor(given: Option[String], family: String, ORCID: Option[String], affiliation: Option[mappingAffiliation]) {} case class mappingAuthor(given: Option[String], family: String, sequence:Option[String], ORCID: Option[String], affiliation: Option[mappingAffiliation]) {}
case class mappingFunder(name: String, DOI: Option[String], award: Option[List[String]]) {} case class mappingFunder(name: String, DOI: Option[String], award: Option[List[String]]) {}
@ -154,7 +156,12 @@ case object Crossref2Oaf {
//Mapping Author //Mapping Author
val authorList: List[mappingAuthor] = (json \ "author").extractOrElse[List[mappingAuthor]](List()) 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)
val sorted_list = authorList.sortWith((a:mappingAuthor, b:mappingAuthor) => a.sequence.isDefined && a.sequence.get.equalsIgnoreCase("first"))
result.setAuthor(sorted_list.zipWithIndex.map{case (a, index) => generateAuhtor(a.given.orNull, a.family, a.ORCID.orNull, index)}.asJava)
// Mapping instance // Mapping instance
val instance = new Instance() val instance = new Instance()
@ -170,14 +177,14 @@ case object Crossref2Oaf {
if(has_review != JNothing) { if(has_review != JNothing) {
instance.setRefereed( instance.setRefereed(
createQualifier("0001", "peerReviewed", "dnet:review_levels", "dnet:review_levels")) OafUtils.createQualifier("0001", "peerReviewed", ModelConstants.DNET_REVIEW_LEVELS, ModelConstants.DNET_REVIEW_LEVELS))
} }
instance.setAccessright(getRestrictedQualifier()) instance.setAccessright(getRestrictedQualifier())
result.setInstance(List(instance).asJava) result.setInstance(List(instance).asJava)
instance.setInstancetype(createQualifier(cobjCategory.substring(0, 4), cobjCategory.substring(5), "dnet:publication_resource", "dnet:publication_resource")) instance.setInstancetype(OafUtils.createQualifier(cobjCategory.substring(0, 4), cobjCategory.substring(5), ModelConstants.DNET_PUBLICATION_RESOURCE, ModelConstants.DNET_PUBLICATION_RESOURCE))
result.setResourcetype(createQualifier(cobjCategory.substring(0, 4),"dnet:dataCite_resource")) result.setResourcetype(OafUtils.createQualifier(cobjCategory.substring(0, 4),"dnet:dataCite_resource"))
instance.setCollectedfrom(createCrossrefCollectedFrom()) instance.setCollectedfrom(createCrossrefCollectedFrom())
if (StringUtils.isNotBlank(issuedDate)) { if (StringUtils.isNotBlank(issuedDate)) {
@ -194,13 +201,14 @@ case object Crossref2Oaf {
} }
def generateAuhtor(given: String, family: String, orcid: String): Author = { def generateAuhtor(given: String, family: String, orcid: String, index:Int): Author = {
val a = new Author val a = new Author
a.setName(given) a.setName(given)
a.setSurname(family) a.setSurname(family)
a.setFullname(s"$given $family") a.setFullname(s"$given $family")
a.setRank(index+1)
if (StringUtils.isNotBlank(orcid)) if (StringUtils.isNotBlank(orcid))
a.setPid(List(createSP(orcid, ORCID_PENDING, PID_TYPES, generateDataInfo())).asJava) a.setPid(List(createSP(orcid, ModelConstants.ORCID_PENDING, ModelConstants.DNET_PID_TYPES, generateDataInfo())).asJava)
a a
} }
@ -221,7 +229,7 @@ case object Crossref2Oaf {
val result = generateItemFromType(objectType, objectSubType) val result = generateItemFromType(objectType, objectSubType)
if (result == null) if (result == null)
return List() return List()
val cOBJCategory = mappingCrossrefSubType.getOrElse(objectType, mappingCrossrefSubType.getOrElse(objectSubType, "0038 Other literature type")); val cOBJCategory = mappingCrossrefSubType.getOrElse(objectType, mappingCrossrefSubType.getOrElse(objectSubType, "0038 Other literature type"))
mappingResult(result, json, cOBJCategory) mappingResult(result, json, cOBJCategory)
@ -299,77 +307,77 @@ case object Crossref2Oaf {
if (funders != null) if (funders != null)
funders.foreach(funder => { funders.foreach(funder => {
if (funder.DOI.isDefined && funder.DOI.get.nonEmpty) { if (funder.DOI.isDefined && funder.DOI.get.nonEmpty) {
funder.DOI.get match { funder.DOI.get match {
case "10.13039/100010663" | case "10.13039/100010663" |
"10.13039/100010661" | "10.13039/100010661" |
"10.13039/501100007601" | "10.13039/501100007601" |
"10.13039/501100000780" | "10.13039/501100000780" |
"10.13039/100010665" => generateSimpleRelationFromAward(funder, "corda__h2020", extractECAward) "10.13039/100010665" => generateSimpleRelationFromAward(funder, "corda__h2020", extractECAward)
case "10.13039/100011199" | case "10.13039/100011199" |
"10.13039/100004431" | "10.13039/100004431" |
"10.13039/501100004963" | "10.13039/501100004963" |
"10.13039/501100000780" => generateSimpleRelationFromAward(funder, "corda_______", extractECAward) "10.13039/501100000780" => generateSimpleRelationFromAward(funder, "corda_______", extractECAward)
case "10.13039/501100000781" => generateSimpleRelationFromAward(funder, "corda_______", extractECAward) case "10.13039/501100000781" => generateSimpleRelationFromAward(funder, "corda_______", extractECAward)
generateSimpleRelationFromAward(funder, "corda__h2020", extractECAward) generateSimpleRelationFromAward(funder, "corda__h2020", extractECAward)
case "10.13039/100000001" => generateSimpleRelationFromAward(funder, "nsf_________", a => a) case "10.13039/100000001" => generateSimpleRelationFromAward(funder, "nsf_________", a => a)
case "10.13039/501100001665" => generateSimpleRelationFromAward(funder, "anr_________", a => a) case "10.13039/501100001665" => generateSimpleRelationFromAward(funder, "anr_________", a => a)
case "10.13039/501100002341" => generateSimpleRelationFromAward(funder, "aka_________", a => a) case "10.13039/501100002341" => generateSimpleRelationFromAward(funder, "aka_________", a => a)
case "10.13039/501100001602" => generateSimpleRelationFromAward(funder, "aka_________", a => a.replace("SFI", "")) case "10.13039/501100001602" => generateSimpleRelationFromAward(funder, "aka_________", a => a.replace("SFI", ""))
case "10.13039/501100000923" => generateSimpleRelationFromAward(funder, "arc_________", a => a) case "10.13039/501100000923" => generateSimpleRelationFromAward(funder, "arc_________", a => a)
case "10.13039/501100000038"=> val targetId = getProjectId("nserc_______" , "1e5e62235d094afd01cd56e65112fc63") case "10.13039/501100000038"=> val targetId = getProjectId("nserc_______" , "1e5e62235d094afd01cd56e65112fc63")
queue += generateRelation(sourceId, targetId, "isProducedBy" ) queue += generateRelation(sourceId, targetId, "isProducedBy" )
queue += generateRelation(targetId, sourceId, "produces" ) queue += generateRelation(targetId, sourceId, "produces" )
case "10.13039/501100000155"=> val targetId = getProjectId("sshrc_______" , "1e5e62235d094afd01cd56e65112fc63") case "10.13039/501100000155"=> val targetId = getProjectId("sshrc_______" , "1e5e62235d094afd01cd56e65112fc63")
queue += generateRelation(sourceId,targetId, "isProducedBy" ) queue += generateRelation(sourceId,targetId, "isProducedBy" )
queue += generateRelation(targetId,sourceId, "produces" ) queue += generateRelation(targetId,sourceId, "produces" )
case "10.13039/501100000024"=> val targetId = getProjectId("cihr________" , "1e5e62235d094afd01cd56e65112fc63") case "10.13039/501100000024"=> val targetId = getProjectId("cihr________" , "1e5e62235d094afd01cd56e65112fc63")
queue += generateRelation(sourceId,targetId, "isProducedBy" ) queue += generateRelation(sourceId,targetId, "isProducedBy" )
queue += generateRelation(targetId,sourceId, "produces" ) queue += generateRelation(targetId,sourceId, "produces" )
case "10.13039/501100002848" => generateSimpleRelationFromAward(funder, "conicytf____", a => a) case "10.13039/501100002848" => generateSimpleRelationFromAward(funder, "conicytf____", a => a)
case "10.13039/501100003448" => generateSimpleRelationFromAward(funder, "gsrt________", extractECAward) case "10.13039/501100003448" => generateSimpleRelationFromAward(funder, "gsrt________", extractECAward)
case "10.13039/501100010198" => generateSimpleRelationFromAward(funder, "sgov________", a=>a) case "10.13039/501100010198" => generateSimpleRelationFromAward(funder, "sgov________", a=>a)
case "10.13039/501100004564" => generateSimpleRelationFromAward(funder, "mestd_______", extractECAward) case "10.13039/501100004564" => generateSimpleRelationFromAward(funder, "mestd_______", extractECAward)
case "10.13039/501100003407" => generateSimpleRelationFromAward(funder, "miur________", a=>a) case "10.13039/501100003407" => generateSimpleRelationFromAward(funder, "miur________", a=>a)
val targetId = getProjectId("miur________" , "1e5e62235d094afd01cd56e65112fc63") val targetId = getProjectId("miur________" , "1e5e62235d094afd01cd56e65112fc63")
queue += generateRelation(sourceId,targetId, "isProducedBy" ) queue += generateRelation(sourceId,targetId, "isProducedBy" )
queue += generateRelation(targetId,sourceId, "produces" ) queue += generateRelation(targetId,sourceId, "produces" )
case "10.13039/501100006588" | case "10.13039/501100006588" |
"10.13039/501100004488" => generateSimpleRelationFromAward(funder, "irb_hr______", a=>a.replaceAll("Project No.", "").replaceAll("HRZZ-","") ) "10.13039/501100004488" => generateSimpleRelationFromAward(funder, "irb_hr______", a=>a.replaceAll("Project No.", "").replaceAll("HRZZ-","") )
case "10.13039/501100006769"=> generateSimpleRelationFromAward(funder, "rsf_________", a=>a) case "10.13039/501100006769"=> generateSimpleRelationFromAward(funder, "rsf_________", a=>a)
case "10.13039/501100001711"=> generateSimpleRelationFromAward(funder, "snsf________", snsfRule) case "10.13039/501100001711"=> generateSimpleRelationFromAward(funder, "snsf________", snsfRule)
case "10.13039/501100004410"=> generateSimpleRelationFromAward(funder, "tubitakf____", a =>a) case "10.13039/501100004410"=> generateSimpleRelationFromAward(funder, "tubitakf____", a =>a)
case "10.10.13039/100004440"=> generateSimpleRelationFromAward(funder, "wt__________", a =>a) case "10.10.13039/100004440"=> generateSimpleRelationFromAward(funder, "wt__________", a =>a)
case "10.13039/100004440"=> val targetId = getProjectId("wt__________" , "1e5e62235d094afd01cd56e65112fc63") case "10.13039/100004440"=> val targetId = getProjectId("wt__________" , "1e5e62235d094afd01cd56e65112fc63")
queue += generateRelation(sourceId,targetId, "isProducedBy" ) queue += generateRelation(sourceId,targetId, "isProducedBy" )
queue += generateRelation(targetId,sourceId, "produces" ) queue += generateRelation(targetId,sourceId, "produces" )
case _ => logger.debug("no match for "+funder.DOI.get ) case _ => logger.debug("no match for "+funder.DOI.get )
}
} else {
funder.name match {
case "European Unions Horizon 2020 research and innovation program" => generateSimpleRelationFromAward(funder, "corda__h2020", extractECAward)
case "European Union's" =>
generateSimpleRelationFromAward(funder, "corda__h2020", extractECAward)
generateSimpleRelationFromAward(funder, "corda_______", extractECAward)
case "The French National Research Agency (ANR)" |
"The French National Research Agency" => generateSimpleRelationFromAward(funder, "anr_________", a => a)
case "CONICYT, Programa de Formación de Capital Humano Avanzado" => generateSimpleRelationFromAward(funder, "conicytf____", extractECAward)
case "Wellcome Trust Masters Fellowship" => val targetId = getProjectId("wt__________", "1e5e62235d094afd01cd56e65112fc63")
queue += generateRelation(sourceId, targetId, "isProducedBy" )
queue += generateRelation(targetId, sourceId, "produces" )
case _ => logger.debug("no match for "+funder.name )
}
} }
} else {
funder.name match {
case "European Unions Horizon 2020 research and innovation program" => generateSimpleRelationFromAward(funder, "corda__h2020", extractECAward)
case "European Union's" =>
generateSimpleRelationFromAward(funder, "corda__h2020", extractECAward)
generateSimpleRelationFromAward(funder, "corda_______", extractECAward)
case "The French National Research Agency (ANR)" |
"The French National Research Agency" => generateSimpleRelationFromAward(funder, "anr_________", a => a)
case "CONICYT, Programa de Formación de Capital Humano Avanzado" => generateSimpleRelationFromAward(funder, "conicytf____", extractECAward)
case "Wellcome Trust Masters Fellowship" => val targetId = getProjectId("wt__________", "1e5e62235d094afd01cd56e65112fc63")
queue += generateRelation(sourceId, targetId, "isProducedBy" )
queue += generateRelation(targetId, sourceId, "produces" )
case _ => logger.debug("no match for "+funder.name )
}
} }
)
}
)
queue.toList queue.toList
} }
@ -465,4 +473,4 @@ case object Crossref2Oaf {
null null
} }
} }

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@ -96,4 +96,4 @@ object CrossrefDataset {
} }
} }

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@ -52,4 +52,4 @@ object SparkMapDumpIntoOAF {
} }
} }

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@ -1,6 +1,7 @@
package eu.dnetlib.doiboost.mag package eu.dnetlib.doiboost.mag
import eu.dnetlib.dhp.schema.common.ModelConstants
import eu.dnetlib.dhp.schema.oaf.{Instance, Journal, Publication, StructuredProperty} 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
@ -31,11 +32,11 @@ case class MagAffiliation(AffiliationId: Long, Rank: Int, NormalizedName: String
case class MagPaperAuthorAffiliation(PaperId: Long, AuthorId: Long, AffiliationId: Option[Long], AuthorSequenceNumber: Int, OriginalAuthor: String, OriginalAffiliation: String) {} case class MagPaperAuthorAffiliation(PaperId: Long, AuthorId: Long, AffiliationId: Option[Long], AuthorSequenceNumber: Int, OriginalAuthor: String, OriginalAffiliation: String) {}
case class MagAuthorAffiliation(author: MagAuthor, affiliation:String) case class MagAuthorAffiliation(author: MagAuthor, affiliation:String, sequenceNumber:Int)
case class MagPaperWithAuthorList(PaperId: Long, authors: List[MagAuthorAffiliation]) {} case class MagPaperWithAuthorList(PaperId: Long, authors: List[MagAuthorAffiliation]) {}
case class MagPaperAuthorDenormalized(PaperId: Long, author: MagAuthor, affiliation:String) {} case class MagPaperAuthorDenormalized(PaperId: Long, author: MagAuthor, affiliation:String, sequenceNumber:Int) {}
case class MagPaperUrl(PaperId: Long, SourceType: Option[Int], SourceUrl: Option[String], LanguageCode: Option[String]) {} case class MagPaperUrl(PaperId: Long, SourceType: Option[Int], SourceUrl: Option[String], LanguageCode: Option[String]) {}
@ -202,12 +203,12 @@ case object ConversionUtil {
val authorsOAF = authors.authors.map { f: MagAuthorAffiliation => val authorsOAF = authors.authors.map { f: MagAuthorAffiliation =>
val a: eu.dnetlib.dhp.schema.oaf.Author = new eu.dnetlib.dhp.schema.oaf.Author val a: eu.dnetlib.dhp.schema.oaf.Author = new eu.dnetlib.dhp.schema.oaf.Author
a.setRank(f.sequenceNumber)
a.setFullname(f.author.DisplayName.get) if (f.author.DisplayName.isDefined)
a.setFullname(f.author.DisplayName.get)
if(f.affiliation!= null) if(f.affiliation!= null)
a.setAffiliation(List(asField(f.affiliation)).asJava) a.setAffiliation(List(asField(f.affiliation)).asJava)
a.setPid(List(createSP(s"https://academic.microsoft.com/#/detail/${f.author.AuthorId}", "URL", PID_TYPES)).asJava) a.setPid(List(createSP(s"https://academic.microsoft.com/#/detail/${f.author.AuthorId}", "URL", ModelConstants.DNET_PID_TYPES)).asJava)
a a
} }
pub.setAuthor(authorsOAF.asJava) pub.setAuthor(authorsOAF.asJava)
@ -274,7 +275,7 @@ case object ConversionUtil {
a.setAffiliation(List(asField(f.affiliation)).asJava) a.setAffiliation(List(asField(f.affiliation)).asJava)
a.setPid(List(createSP(s"https://academic.microsoft.com/#/detail/${f.author.AuthorId}", "URL", PID_TYPES)).asJava) a.setPid(List(createSP(s"https://academic.microsoft.com/#/detail/${f.author.AuthorId}", "URL", ModelConstants.DNET_PID_TYPES)).asJava)
a a
@ -305,12 +306,12 @@ case object ConversionUtil {
for {(k: String, v: List[Int]) <- iid} { for {(k: String, v: List[Int]) <- iid} {
v.foreach(item => res(item) = k) v.foreach(item => res(item) = k)
} }
(0 until idl).foreach(i => { (0 until idl).foreach(i => {
if (res(i) == null) if (res(i) == null)
res(i) = "" res(i) = ""
}) })
return res.mkString(" ") return res.mkString(" ")
} }
"" ""
} }
} }

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@ -6,10 +6,10 @@ import org.apache.spark.SparkConf
import org.apache.spark.sql.{SaveMode, SparkSession} import org.apache.spark.sql.{SaveMode, SparkSession}
import org.apache.spark.sql.types._ import org.apache.spark.sql.types._
import org.slf4j.{Logger, LoggerFactory} import org.slf4j.{Logger, LoggerFactory}
import org.apache.spark.sql.functions._
object SparkImportMagIntoDataset { object SparkImportMagIntoDataset {
val datatypedict = Map( val datatypedict = Map(
"bool" -> BooleanType,
"int" -> IntegerType, "int" -> IntegerType,
"uint" -> IntegerType, "uint" -> IntegerType,
"long" -> LongType, "long" -> LongType,
@ -25,11 +25,10 @@ object SparkImportMagIntoDataset {
"AuthorExtendedAttributes" -> Tuple2("mag/AuthorExtendedAttributes.txt", Seq("AuthorId:long", "AttributeType:int", "AttributeValue:string")), "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")), "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", "CitationCount:long", "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")), "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")), "FieldOfStudyChildren" -> Tuple2("advanced/FieldOfStudyChildren.txt", Seq("FieldOfStudyId:long", "ChildFieldOfStudyId:long")),
"FieldOfStudyExtendedAttributes" -> Tuple2("advanced/FieldOfStudyExtendedAttributes.txt", Seq("FieldOfStudyId:long", "AttributeType:int", "AttributeValue:string")), "FieldOfStudyExtendedAttributes" -> Tuple2("advanced/FieldOfStudyExtendedAttributes.txt", Seq("FieldOfStudyId:long", "AttributeType:int", "AttributeValue:string")),
// ['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")), "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")), "PaperAbstractsInvertedIndex" -> Tuple2("nlp/PaperAbstractsInvertedIndex.txt.*", Seq("PaperId:long", "IndexedAbstract:string")),
@ -37,6 +36,7 @@ object SparkImportMagIntoDataset {
"PaperCitationContexts" -> Tuple2("nlp/PaperCitationContexts.txt", Seq("PaperId:long", "PaperReferenceId:long", "CitationContext: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")), "PaperExtendedAttributes" -> Tuple2("mag/PaperExtendedAttributes.txt", Seq("PaperId:long", "AttributeType:int", "AttributeValue:string")),
"PaperFieldsOfStudy" -> Tuple2("advanced/PaperFieldsOfStudy.txt", Seq("PaperId:long", "FieldOfStudyId:long", "Score:float")), "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")), "PaperRecommendations" -> Tuple2("advanced/PaperRecommendations.txt", Seq("PaperId:long", "RecommendedPaperId:long", "Score:float")),
"PaperReferences" -> Tuple2("mag/PaperReferences.txt", Seq("PaperId:long", "PaperReferenceId:long")), "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")), "PaperResources" -> Tuple2("mag/PaperResources.txt", Seq("PaperId:long", "ResourceType:int", "ResourceUrl:string", "SourceUrl:string", "RelationshipType:int")),
@ -91,4 +91,4 @@ object SparkImportMagIntoDataset {
} }
} }

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@ -58,16 +58,16 @@ object SparkProcessMAG {
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"))) 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, a.AuthorSequenceNumber)) }
.joinWith(affiliation, affiliation("AffiliationId").equalTo(col("_1")), "left") .joinWith(affiliation, affiliation("AffiliationId").equalTo(col("_1")), "left")
.map(s => { .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, mpa.sequenceNumber)
} else } else
mpa mpa
}).groupBy("PaperId").agg(collect_list(struct($"author", $"affiliation")).as("authors")) }).groupBy("PaperId").agg(collect_list(struct($"author", $"affiliation", $"sequenceNumber")).as("authors"))
.write.mode(SaveMode.Overwrite).save(s"$workingPath/merge_step_1_paper_authors") .write.mode(SaveMode.Overwrite).save(s"$workingPath/merge_step_1_paper_authors")
logger.info("Phase 4) create First Version of publication Entity with Paper Journal and Authors") logger.info("Phase 4) create First Version of publication Entity with Paper Journal and Authors")
@ -86,7 +86,7 @@ object SparkProcessMAG {
var magPubs: Dataset[(String, Publication)] = var magPubs: Dataset[(String, Publication)] =
spark.read.load(s"$workingPath/merge_step_2").as[Publication] spark.read.load(s"$workingPath/merge_step_2").as[Publication]
.map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p)).as[(String, Publication)] .map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p)).as[(String, Publication)]
val conference = spark.read.load(s"$sourcePath/ConferenceInstances") val conference = spark.read.load(s"$sourcePath/ConferenceInstances")
@ -115,10 +115,9 @@ object SparkProcessMAG {
.save(s"$workingPath/merge_step_3") .save(s"$workingPath/merge_step_3")
// logger.info("Phase 6) Enrich Publication with description") // logger.info("Phase 6) Enrich Publication with description")
// val pa = spark.read.load(s"${parser.get("sourcePath")}/PaperAbstractsInvertedIndex").as[MagPaperAbstract] // 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") // pa.map(ConversionUtil.transformPaperAbstract).write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/PaperAbstract")
val paperAbstract = spark.read.load((s"$workingPath/PaperAbstract")).as[MagPaperAbstract] val paperAbstract = spark.read.load((s"$workingPath/PaperAbstract")).as[MagPaperAbstract]
@ -127,7 +126,7 @@ object SparkProcessMAG {
magPubs.joinWith(paperAbstract, col("_1").equalTo(paperAbstract("PaperId")), "left") magPubs.joinWith(paperAbstract, col("_1").equalTo(paperAbstract("PaperId")), "left")
.map(item => ConversionUtil.updatePubsWithDescription(item) .map(item => ConversionUtil.updatePubsWithDescription(item)
).write.mode(SaveMode.Overwrite).save(s"$workingPath/merge_step_4") ).write.mode(SaveMode.Overwrite).save(s"$workingPath/merge_step_4")
logger.info("Phase 7) Enrich Publication with FieldOfStudy") logger.info("Phase 7) Enrich Publication with FieldOfStudy")
@ -153,9 +152,9 @@ object SparkProcessMAG {
val s:RDD[Publication] = spark.read.load(s"$workingPath/mag_publication").as[Publication] val s:RDD[Publication] = spark.read.load(s"$workingPath/mag_publication").as[Publication]
.map(p=>Tuple2(p.getId, p)).rdd.reduceByKey((a:Publication, b:Publication) => ConversionUtil.mergePublication(a,b)) .map(p=>Tuple2(p.getId, p)).rdd.reduceByKey((a:Publication, b:Publication) => ConversionUtil.mergePublication(a,b))
.map(_._2) .map(_._2)
spark.createDataset(s).as[Publication].write.mode(SaveMode.Overwrite).save(s"$targetPath/magPublication") spark.createDataset(s).as[Publication].write.mode(SaveMode.Overwrite).save(s"$targetPath/magPublication")
} }
} }

View File

@ -1,17 +1,25 @@
package eu.dnetlib.doiboost.orcid package eu.dnetlib.doiboost.orcid
import com.fasterxml.jackson.databind.ObjectMapper import com.fasterxml.jackson.databind.ObjectMapper
import eu.dnetlib.dhp.schema.common.ModelConstants
import eu.dnetlib.dhp.schema.oaf.{Author, DataInfo, Publication} import eu.dnetlib.dhp.schema.oaf.{Author, DataInfo, Publication}
import eu.dnetlib.dhp.schema.orcid.OrcidDOI import eu.dnetlib.dhp.schema.orcid.{AuthorData, OrcidDOI}
import eu.dnetlib.doiboost.DoiBoostMappingUtil import eu.dnetlib.doiboost.DoiBoostMappingUtil
import eu.dnetlib.doiboost.DoiBoostMappingUtil.{ORCID, PID_TYPES, createSP, generateDataInfo, generateIdentifier} import eu.dnetlib.doiboost.DoiBoostMappingUtil.{createSP, generateDataInfo}
import org.apache.commons.lang.StringUtils import org.apache.commons.lang.StringUtils
import org.slf4j.{Logger, LoggerFactory} import org.slf4j.{Logger, LoggerFactory}
import scala.collection.JavaConverters._ import scala.collection.JavaConverters._
import org.json4s
import org.json4s.DefaultFormats
import org.json4s.JsonAST._
import org.json4s.jackson.JsonMethods._
case class ORCIDItem(oid:String,name:String,surname:String,creditName:String,errorCode:String){} case class ORCIDItem(doi:String, authors:List[OrcidAuthor]){}
case class OrcidAuthor(oid:String, name:Option[String], surname:Option[String], creditName:Option[String], otherNames:Option[List[String]], errorCode:Option[String]){}
case class OrcidWork(oid:String, doi:String)
@ -44,17 +52,65 @@ object ORCIDToOAF {
} }
def convertTOOAF(input:OrcidDOI) :Publication = { def strValid(s:Option[String]) : Boolean = {
val doi = input.getDoi s.isDefined && s.get.nonEmpty
}
def authorValid(author:OrcidAuthor): Boolean ={
if (strValid(author.name) && strValid(author.surname)) {
return true
}
if (strValid(author.surname)) {
return true
}
if (strValid(author.creditName)) {
return true
}
false
}
def extractDOIWorks(input:String): List[OrcidWork] = {
implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
lazy val json: json4s.JValue = parse(input)
val oid = (json \ "workDetail" \"oid").extractOrElse[String](null)
if (oid == null)
return List()
val doi:List[(String, String)] = for {
JObject(extIds) <- json \ "workDetail" \"extIds"
JField("type", JString(typeValue)) <- extIds
JField("value", JString(value)) <- extIds
if "doi".equalsIgnoreCase(typeValue)
} yield (typeValue, value)
if (doi.nonEmpty) {
return doi.map(l =>OrcidWork(oid, l._2))
}
List()
}
def convertORCIDAuthor(input:String): OrcidAuthor = {
implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
lazy val json: json4s.JValue = parse(input)
(json \"authorData" ).extractOrElse[OrcidAuthor](null)
}
def convertTOOAF(input:ORCIDItem) :Publication = {
val doi = input.doi
val pub:Publication = new Publication val pub:Publication = new Publication
pub.setPid(List(createSP(doi.toLowerCase, "doi", PID_TYPES)).asJava) pub.setPid(List(createSP(doi.toLowerCase, "doi", ModelConstants.DNET_PID_TYPES)).asJava)
pub.setDataInfo(generateDataInfo()) pub.setDataInfo(generateDataInfo())
pub.setId(generateIdentifier(pub, doi.toLowerCase))
pub.setId(DoiBoostMappingUtil.generateIdentifier(pub, doi.toLowerCase))
try{ try{
val l:List[Author]= input.getAuthors.asScala.map(a=> { val l:List[Author]= input.authors.map(a=> {
generateAuthor(a.getName, a.getSurname, a.getCreditName, a.getOid) generateAuthor(a)
})(collection.breakOut) })(collection.breakOut)
pub.setAuthor(l.asJava) pub.setAuthor(l.asJava)
pub.setCollectedfrom(List(DoiBoostMappingUtil.createORIDCollectedFrom()).asJava) pub.setCollectedfrom(List(DoiBoostMappingUtil.createORIDCollectedFrom()).asJava)
@ -74,19 +130,23 @@ object ORCIDToOAF {
di di
} }
def generateAuthor(given: String, family: String, fullName:String, orcid: String): Author = { def generateAuthor(o : OrcidAuthor): Author = {
val a = new Author val a = new Author
a.setName(given) if (strValid(o.name)) {
a.setSurname(family) a.setName(o.name.get.capitalize)
if (fullName!= null && fullName.nonEmpty) }
a.setFullname(fullName) if (strValid(o.surname)) {
else a.setSurname(o.surname.get.capitalize)
a.setFullname(s"$given $family") }
if (StringUtils.isNotBlank(orcid)) if(strValid(o.name) && strValid(o.surname))
a.setPid(List(createSP(orcid, ORCID, PID_TYPES, generateOricPIDDatainfo())).asJava) a.setFullname(s"${o.name.get.capitalize} ${o.surname.get.capitalize}")
else if (strValid(o.creditName))
a.setFullname(o.creditName.get)
if (StringUtils.isNotBlank(o.oid))
a.setPid(List(createSP(o.oid, ModelConstants.ORCID, ModelConstants.DNET_PID_TYPES, generateOricPIDDatainfo())).asJava)
a a
} }
} }

View File

@ -1,72 +1,49 @@
package eu.dnetlib.doiboost.orcid package eu.dnetlib.doiboost.orcid
import com.fasterxml.jackson.databind.{DeserializationFeature, ObjectMapper}
import eu.dnetlib.dhp.application.ArgumentApplicationParser 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.oaf.Publication
import eu.dnetlib.dhp.schema.orcid.OrcidDOI
import eu.dnetlib.doiboost.mag.ConversionUtil
import org.apache.commons.io.IOUtils import org.apache.commons.io.IOUtils
import org.apache.spark.SparkConf import org.apache.spark.SparkConf
import org.apache.spark.rdd.RDD import org.apache.spark.rdd.RDD
import org.apache.spark.sql.expressions.Aggregator import org.apache.spark.sql.functions._
import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession} import org.apache.spark.sql._
import org.slf4j.{Logger, LoggerFactory} import org.slf4j.{Logger, LoggerFactory}
object SparkConvertORCIDToOAF { object SparkConvertORCIDToOAF {
val logger: Logger = LoggerFactory.getLogger(SparkConvertORCIDToOAF.getClass) val logger: Logger = LoggerFactory.getLogger(SparkConvertORCIDToOAF.getClass)
def getPublicationAggregator(): Aggregator[(String, Publication), Publication, Publication] = new Aggregator[(String, Publication), Publication, Publication]{ def run(spark:SparkSession,sourcePath:String,workingPath:String, targetPath:String):Unit = {
import spark.implicits._
implicit val mapEncoderPubs: Encoder[Publication] = Encoders.kryo[Publication]
override def zero: Publication = new Publication() val inputRDD:RDD[OrcidAuthor] = spark.sparkContext.textFile(s"$sourcePath/authors").map(s => ORCIDToOAF.convertORCIDAuthor(s)).filter(s => s!= null).filter(s => ORCIDToOAF.authorValid(s))
override def reduce(b: Publication, a: (String, Publication)): Publication = { spark.createDataset(inputRDD).as[OrcidAuthor].write.mode(SaveMode.Overwrite).save(s"$workingPath/author")
b.mergeFrom(a._2)
b.setAuthor(AuthorMerger.mergeAuthor(a._2.getAuthor, b.getAuthor))
if (b.getId == null)
b.setId(a._2.getId)
b
}
val res = spark.sparkContext.textFile(s"$sourcePath/works").flatMap(s => ORCIDToOAF.extractDOIWorks(s)).filter(s => s!= null)
override def merge(wx: Publication, wy: Publication): Publication = { spark.createDataset(res).as[OrcidWork].write.mode(SaveMode.Overwrite).save(s"$workingPath/works")
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] = val authors :Dataset[OrcidAuthor] = spark.read.load(s"$workingPath/author").as[OrcidAuthor]
Encoders.kryo(classOf[Publication])
override def outputEncoder: Encoder[Publication] = val works :Dataset[OrcidWork] = spark.read.load(s"$workingPath/works").as[OrcidWork]
Encoders.kryo(classOf[Publication])
works.joinWith(authors, authors("oid").equalTo(works("oid")))
.map(i =>{
val doi = i._1.doi
val author = i._2
(doi, author)
}).groupBy(col("_1").alias("doi"))
.agg(collect_list(col("_2")).alias("authors"))
.write.mode(SaveMode.Overwrite).save(s"$workingPath/orcidworksWithAuthor")
val dataset: Dataset[ORCIDItem] =spark.read.load(s"$workingPath/orcidworksWithAuthor").as[ORCIDItem]
logger.info("Converting ORCID to OAF")
dataset.map(o => ORCIDToOAF.convertTOOAF(o)).write.mode(SaveMode.Overwrite).save(targetPath)
} }
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 = { def main(args: Array[String]): Unit = {
val conf: SparkConf = new SparkConf() val conf: SparkConf = new SparkConf()
val parser = new ArgumentApplicationParser(IOUtils.toString(SparkConvertORCIDToOAF.getClass.getResourceAsStream("/eu/dnetlib/dhp/doiboost/convert_map_to_oaf_params.json"))) val parser = new ArgumentApplicationParser(IOUtils.toString(SparkConvertORCIDToOAF.getClass.getResourceAsStream("/eu/dnetlib/dhp/doiboost/convert_map_to_oaf_params.json")))
parser.parseArgument(args) parser.parseArgument(args)
@ -78,11 +55,11 @@ def run(spark:SparkSession,sourcePath:String, targetPath:String):Unit = {
.master(parser.get("master")).getOrCreate() .master(parser.get("master")).getOrCreate()
val sourcePath = parser.get("sourcePath") val sourcePath = parser.get("sourcePath")
val workingPath = parser.get("workingPath")
val targetPath = parser.get("targetPath") val targetPath = parser.get("targetPath")
run(spark, sourcePath, targetPath) run(spark, sourcePath, workingPath, targetPath)
} }
} }

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@ -40,4 +40,4 @@ object SparkMapUnpayWallToOAF {
d.write.mode(SaveMode.Overwrite).save(targetPath) d.write.mode(SaveMode.Overwrite).save(targetPath)
} }
} }

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@ -54,6 +54,11 @@
</property> </property>
<!-- MAG Parameters --> <!-- MAG Parameters -->
<property>
<name>MAGDumpPath</name>
<description>the MAG dump working path</description>
</property>
<property> <property>
<name>inputPathMAG</name> <name>inputPathMAG</name>
<description>the MAG working path</description> <description>the MAG working path</description>
@ -69,6 +74,11 @@
<!-- ORCID Parameters --> <!-- ORCID Parameters -->
<property> <property>
<name>inputPathOrcid</name> <name>inputPathOrcid</name>
<description>the ORCID input path</description>
</property>
<property>
<name>workingPathOrcid</name>
<description>the ORCID working path</description> <description>the ORCID working path</description>
</property> </property>
@ -121,24 +131,27 @@
<!-- CROSSREF SECTION --> <!-- CROSSREF SECTION -->
<action name="GenerateCrossrefDataset"> <action name="GenerateCrossrefDataset">
<spark xmlns="uri:oozie:spark-action:0.2"> <spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn-cluster</master> <master>yarn-cluster</master>
<mode>cluster</mode> <mode>cluster</mode>
<name>GenerateCrossrefDataset</name> <name>GenerateCrossrefDataset</name>
<class>eu.dnetlib.doiboost.crossref.CrossrefDataset</class> <class>eu.dnetlib.doiboost.crossref.CrossrefDataset</class>
<jar>dhp-doiboost-${projectVersion}.jar</jar> <jar>dhp-doiboost-${projectVersion}.jar</jar>
<spark-opts> <spark-opts>
--executor-memory=${sparkExecutorMemory} --executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores} --executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory} --driver-memory=${sparkDriverMemory}
--conf spark.sql.shuffle.partitions=3840 --conf spark.sql.shuffle.partitions=3840
${sparkExtraOPT} --conf spark.extraListeners=${spark2ExtraListeners}
</spark-opts> --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
<arg>--workingPath</arg><arg>${inputPathCrossref}</arg> --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
<arg>--master</arg><arg>yarn-cluster</arg> --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark> </spark-opts>
<ok to="RenameDataset"/> <arg>--workingPath</arg><arg>${inputPathCrossref}</arg>
<error to="Kill"/> <arg>--master</arg><arg>yarn-cluster</arg>
</spark>
<ok to="RenameDataset"/>
<error to="Kill"/>
</action> </action>
<action name="RenameDataset"> <action name="RenameDataset">
@ -147,6 +160,43 @@
<move source="${inputPathCrossref}/crossref_ds_updated" <move source="${inputPathCrossref}/crossref_ds_updated"
target="${inputPathCrossref}/crossref_ds"/> target="${inputPathCrossref}/crossref_ds"/>
</fs> </fs>
<ok to="ResetMagWorkingPath"/>
<error to="Kill"/>
</action>
<!-- MAG SECTION -->
<action name="ResetMagWorkingPath">
<fs>
<delete path="${inputPathMAG}/dataset"/>
<delete path="${inputPathMAG}/process"/>
</fs>
<ok to="ConvertMagToDataset"/>
<error to="Kill"/>
</action>
<action name="ConvertMagToDataset">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>Convert Mag to Dataset</name>
<class>eu.dnetlib.doiboost.mag.SparkImportMagIntoDataset</class>
<jar>dhp-doiboost-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.sql.shuffle.partitions=3840
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts>
<arg>--sourcePath</arg><arg>${MAGDumpPath}</arg>
<arg>--targetPath</arg><arg>${inputPathMAG}/dataset</arg>
<arg>--master</arg><arg>yarn-cluster</arg>
</spark>
<ok to="ConvertCrossrefToOAF"/> <ok to="ConvertCrossrefToOAF"/>
<error to="Kill"/> <error to="Kill"/>
</action> </action>
@ -164,46 +214,15 @@
--executor-cores=${sparkExecutorCores} --executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory} --driver-memory=${sparkDriverMemory}
--conf spark.sql.shuffle.partitions=3840 --conf spark.sql.shuffle.partitions=3840
${sparkExtraOPT} --conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts> </spark-opts>
<arg>--sourcePath</arg><arg>${inputPathCrossref}/crossref_ds</arg> <arg>--sourcePath</arg><arg>${inputPathCrossref}/crossref_ds</arg>
<arg>--targetPath</arg><arg>${workingPath}</arg> <arg>--targetPath</arg><arg>${workingPath}</arg>
<arg>--master</arg><arg>yarn-cluster</arg> <arg>--master</arg><arg>yarn-cluster</arg>
</spark> </spark>
<ok to="ResetMagWorkingPath"/>
<error to="Kill"/>
</action>
<!-- MAG SECTION -->
<action name="ResetMagWorkingPath">
<fs>
<delete path="${inputPathMAG}/dataset"/>
<delete path="${inputPathMAG}/process"/>
<delete path="${inputPathMAG}/dataset"/>
</fs>
<ok to="ConvertMagToDataset"/>
<error to="Kill"/>
</action>
<action name="ConvertMagToDataset">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>Convert Mag to Dataset</name>
<class>eu.dnetlib.doiboost.mag.SparkImportMagIntoDataset</class>
<jar>dhp-doiboost-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
${sparkExtraOPT}
</spark-opts>
<arg>--sourcePath</arg><arg>${inputPathMAG}/input</arg>
<arg>--targetPath</arg><arg>${inputPathMAG}/dataset</arg>
<arg>--master</arg><arg>yarn-cluster</arg>
</spark>
<ok to="ProcessMAG"/> <ok to="ProcessMAG"/>
<error to="Kill"/> <error to="Kill"/>
</action> </action>
@ -216,11 +235,14 @@
<class>eu.dnetlib.doiboost.mag.SparkProcessMAG</class> <class>eu.dnetlib.doiboost.mag.SparkProcessMAG</class>
<jar>dhp-doiboost-${projectVersion}.jar</jar> <jar>dhp-doiboost-${projectVersion}.jar</jar>
<spark-opts> <spark-opts>
--executor-memory=${sparkExecutorMemory} --executor-memory=${sparkExecutorIntersectionMemory}
--executor-cores=${sparkExecutorCores} --executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory} --driver-memory=${sparkDriverMemory}
--conf spark.sql.shuffle.partitions=3840 --conf spark.sql.shuffle.partitions=3840
${sparkExtraOPT} --conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts> </spark-opts>
<arg>--sourcePath</arg><arg>${inputPathMAG}/dataset</arg> <arg>--sourcePath</arg><arg>${inputPathMAG}/dataset</arg>
<arg>--workingPath</arg><arg>${inputPathMAG}/process</arg> <arg>--workingPath</arg><arg>${inputPathMAG}/process</arg>
@ -245,10 +267,14 @@
--executor-cores=${sparkExecutorCores} --executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory} --driver-memory=${sparkDriverMemory}
--conf spark.sql.shuffle.partitions=3840 --conf spark.sql.shuffle.partitions=3840
${sparkExtraOPT} --conf spark.sql.shuffle.partitions=3840
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts> </spark-opts>
<arg>--sourcePath</arg><arg>${inputPathUnpayWall}/uw_extracted</arg> <arg>--sourcePath</arg><arg>${inputPathUnpayWall}/uw_extracted</arg>
<arg>--targetPath</arg><arg>${workingPath}</arg> <arg>--targetPath</arg><arg>${workingPath}/uwPublication</arg>
<arg>--master</arg><arg>yarn-cluster</arg> <arg>--master</arg><arg>yarn-cluster</arg>
</spark> </spark>
<ok to="ProcessORCID"/> <ok to="ProcessORCID"/>
@ -268,10 +294,14 @@
--executor-cores=${sparkExecutorCores} --executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory} --driver-memory=${sparkDriverMemory}
--conf spark.sql.shuffle.partitions=3840 --conf spark.sql.shuffle.partitions=3840
${sparkExtraOPT} --conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts> </spark-opts>
<arg>--sourcePath</arg><arg>${inputPathOrcid}</arg> <arg>--sourcePath</arg><arg>${inputPathOrcid}</arg>
<arg>--targetPath</arg><arg>${workingPath}</arg> <arg>--workingPath</arg><arg>${workingPathOrcid}</arg>
<arg>--targetPath</arg><arg>${workingPath}/orcidPublication</arg>
<arg>--master</arg><arg>yarn-cluster</arg> <arg>--master</arg><arg>yarn-cluster</arg>
</spark> </spark>
<ok to="CreateDOIBoost"/> <ok to="CreateDOIBoost"/>
@ -291,11 +321,15 @@
--executor-cores=${sparkExecutorCores} --executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory} --driver-memory=${sparkDriverMemory}
--conf spark.sql.shuffle.partitions=3840 --conf spark.sql.shuffle.partitions=3840
${sparkExtraOPT} --conf spark.sql.shuffle.partitions=3840
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts> </spark-opts>
<arg>--hostedByMapPath</arg><arg>${hostedByMapPath}</arg> <arg>--hostedByMapPath</arg><arg>${hostedByMapPath}</arg>
<arg>--affiliationPath</arg><arg>${inputPathMAG}/process/Affiliations</arg> <arg>--affiliationPath</arg><arg>${inputPathMAG}/dataset/Affiliations</arg>
<arg>--paperAffiliationPath</arg><arg>${inputPathMAG}/process/PaperAuthorAffiliations</arg> <arg>--paperAffiliationPath</arg><arg>${inputPathMAG}/dataset/PaperAuthorAffiliations</arg>
<arg>--workingPath</arg><arg>${workingPath}</arg> <arg>--workingPath</arg><arg>${workingPath}</arg>
<arg>--master</arg><arg>yarn-cluster</arg> <arg>--master</arg><arg>yarn-cluster</arg>
</spark> </spark>
@ -316,7 +350,10 @@
--executor-cores=${sparkExecutorCores} --executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory} --driver-memory=${sparkDriverMemory}
--conf spark.sql.shuffle.partitions=3840 --conf spark.sql.shuffle.partitions=3840
${sparkExtraOPT} --conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts> </spark-opts>
<arg>--dbPublicationPath</arg><arg>${workingPath}/doiBoostPublicationFiltered</arg> <arg>--dbPublicationPath</arg><arg>${workingPath}/doiBoostPublicationFiltered</arg>
<arg>--dbDatasetPath</arg><arg>${workingPath}/crossrefDataset</arg> <arg>--dbDatasetPath</arg><arg>${workingPath}/crossrefDataset</arg>