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code refactor, created and moved scala code on the correct maven folder under src/main/scala and src/test/scala

This commit is contained in:
Sandro La Bruzzo 2021-11-17 11:35:22 +01:00
parent 60ae874dcb
commit 2fd9ceac13
25 changed files with 69 additions and 95 deletions

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

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

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

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

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

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

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

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@ -5,19 +5,16 @@ import eu.dnetlib.dhp.schema.oaf.Publication
import eu.dnetlib.doiboost.DoiBoostMappingUtil
import org.apache.commons.io.IOUtils
import org.apache.spark.SparkConf
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.functions._
import org.apache.spark.sql.functions.{col, collect_list, struct}
import org.apache.spark.sql._
import org.slf4j.{Logger, LoggerFactory}
import scala.collection.JavaConverters._
object SparkProcessMAG {
def getDistinctResults (d:Dataset[MagPapers]):Dataset[MagPapers]={
def getDistinctResults(d: Dataset[MagPapers]): Dataset[MagPapers] = {
d.where(col("Doi").isNotNull)
.groupByKey(mp => DoiBoostMappingUtil.normalizeDoi(mp.Doi))(Encoders.STRING)
.reduceGroups((p1:MagPapers,p2:MagPapers) => ConversionUtil.choiceLatestMagArtitcle(p1,p2))
.reduceGroups((p1: MagPapers, p2: MagPapers) => ConversionUtil.choiceLatestMagArtitcle(p1, p2))
.map(_._2)(Encoders.product[MagPapers])
.map(mp => {
new MagPapers(mp.PaperId, mp.Rank, DoiBoostMappingUtil.normalizeDoi(mp.Doi),
@ -98,13 +95,13 @@ object SparkProcessMAG {
var magPubs: Dataset[(String, Publication)] =
spark.read.load(s"$workingPath/merge_step_2").as[Publication]
.map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p)).as[(String, Publication)]
.map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p)).as[(String, Publication)]
val conference = spark.read.load(s"$sourcePath/ConferenceInstances")
.select($"ConferenceInstanceId".as("ci"), $"DisplayName", $"Location", $"StartDate",$"EndDate" )
.select($"ConferenceInstanceId".as("ci"), $"DisplayName", $"Location", $"StartDate", $"EndDate")
val conferenceInstance = conference.joinWith(papers, papers("ConferenceInstanceId").equalTo(conference("ci")))
.select($"_1.ci", $"_1.DisplayName", $"_1.Location", $"_1.StartDate",$"_1.EndDate", $"_2.PaperId").as[MagConferenceInstance]
.select($"_1.ci", $"_1.DisplayName", $"_1.Location", $"_1.StartDate", $"_1.EndDate", $"_2.PaperId").as[MagConferenceInstance]
magPubs.joinWith(conferenceInstance, col("_1").equalTo(conferenceInstance("PaperId")), "left")
@ -122,7 +119,7 @@ object SparkProcessMAG {
magPubs.joinWith(paperAbstract, col("_1").equalTo(paperAbstract("PaperId")), "left")
.map(item => ConversionUtil.updatePubsWithDescription(item)
).write.mode(SaveMode.Overwrite).save(s"$workingPath/merge_step_4")
).write.mode(SaveMode.Overwrite).save(s"$workingPath/merge_step_4")
logger.info("Phase 7) Enrich Publication with FieldOfStudy")
@ -148,11 +145,10 @@ object SparkProcessMAG {
spark.read.load(s"$workingPath/mag_publication").as[Publication]
.filter(p => p.getId == null)
.groupByKey(p => p.getId)
.reduceGroups((a:Publication, b:Publication) => ConversionUtil.mergePublication(a,b))
.reduceGroups((a: Publication, b: Publication) => ConversionUtil.mergePublication(a, b))
.map(_._2)
.write.mode(SaveMode.Overwrite).save(s"$targetPath/magPublication")
}
}

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

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@ -11,10 +11,10 @@ object SparkConvertORCIDToOAF {
val logger: Logger = LoggerFactory.getLogger(SparkConvertORCIDToOAF.getClass)
def run(spark:SparkSession, workingPath:String, targetPath:String) :Unit = {
def run(spark: SparkSession, workingPath: String, targetPath: String): Unit = {
implicit val mapEncoderPubs: Encoder[Publication] = Encoders.kryo[Publication]
import spark.implicits._
val dataset: Dataset[ORCIDItem] =spark.read.load(s"$workingPath/orcidworksWithAuthor").as[ORCIDItem]
val dataset: Dataset[ORCIDItem] = spark.read.load(s"$workingPath/orcidworksWithAuthor").as[ORCIDItem]
logger.info("Converting ORCID to OAF")
dataset.map(o => ORCIDToOAF.convertTOOAF(o)).write.mode(SaveMode.Overwrite).save(targetPath)
@ -35,8 +35,8 @@ object SparkConvertORCIDToOAF {
val workingPath = parser.get("workingPath")
val targetPath = parser.get("targetPath")
run(spark,workingPath, targetPath)
run(spark, workingPath, targetPath)
}
}
}

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@ -1,48 +1,45 @@
package eu.dnetlib.doiboost.orcid
import com.fasterxml.jackson.databind.{DeserializationFeature, ObjectMapper}
import eu.dnetlib.dhp.application.ArgumentApplicationParser
import eu.dnetlib.dhp.oa.merge.AuthorMerger
import eu.dnetlib.dhp.schema.oaf.Publication
import eu.dnetlib.dhp.schema.orcid.OrcidDOI
import org.apache.commons.io.IOUtils
import org.apache.spark.SparkConf
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.functions._
import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
import org.apache.spark.sql.functions.{col, collect_list}
import org.apache.spark.sql._
import org.slf4j.{Logger, LoggerFactory}
object SparkPreprocessORCID {
val logger: Logger = LoggerFactory.getLogger(SparkConvertORCIDToOAF.getClass)
def fixORCIDItem(item :ORCIDItem):ORCIDItem = {
ORCIDItem(item.doi, item.authors.groupBy(_.oid).map(_._2.head).toList)
def fixORCIDItem(item: ORCIDItem): ORCIDItem = {
ORCIDItem(item.doi, item.authors.groupBy(_.oid).map(_._2.head).toList)
}
def run(spark:SparkSession,sourcePath:String,workingPath:String):Unit = {
def run(spark: SparkSession, sourcePath: String, workingPath: String): Unit = {
import spark.implicits._
implicit val mapEncoderPubs: Encoder[Publication] = Encoders.kryo[Publication]
val inputRDD:RDD[OrcidAuthor] = spark.sparkContext.textFile(s"$sourcePath/authors").map(s => ORCIDToOAF.convertORCIDAuthor(s)).filter(s => s!= null).filter(s => ORCIDToOAF.authorValid(s))
val inputRDD: RDD[OrcidAuthor] = spark.sparkContext.textFile(s"$sourcePath/authors").map(s => ORCIDToOAF.convertORCIDAuthor(s)).filter(s => s != null).filter(s => ORCIDToOAF.authorValid(s))
spark.createDataset(inputRDD).as[OrcidAuthor].write.mode(SaveMode.Overwrite).save(s"$workingPath/author")
val res = spark.sparkContext.textFile(s"$sourcePath/works").flatMap(s => ORCIDToOAF.extractDOIWorks(s)).filter(s => s!= null)
val res = spark.sparkContext.textFile(s"$sourcePath/works").flatMap(s => ORCIDToOAF.extractDOIWorks(s)).filter(s => s != null)
spark.createDataset(res).as[OrcidWork].write.mode(SaveMode.Overwrite).save(s"$workingPath/works")
val authors :Dataset[OrcidAuthor] = spark.read.load(s"$workingPath/author").as[OrcidAuthor]
val authors: Dataset[OrcidAuthor] = spark.read.load(s"$workingPath/author").as[OrcidAuthor]
val works :Dataset[OrcidWork] = spark.read.load(s"$workingPath/works").as[OrcidWork]
val works: Dataset[OrcidWork] = spark.read.load(s"$workingPath/works").as[OrcidWork]
works.joinWith(authors, authors("oid").equalTo(works("oid")))
.map(i =>{
.map(i => {
val doi = i._1.doi
val author = i._2
(doi, author)
}).groupBy(col("_1").alias("doi"))
(doi, author)
}).groupBy(col("_1").alias("doi"))
.agg(collect_list(col("_2")).alias("authors")).as[ORCIDItem]
.map(s => fixORCIDItem(s))
.write.mode(SaveMode.Overwrite).save(s"$workingPath/orcidworksWithAuthor")
@ -67,4 +64,4 @@ object SparkPreprocessORCID {
}
}
}

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

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

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@ -1,4 +1,4 @@
package eu.dnetlib.dhp.doiboost
package eu.dnetlib.doiboost
import eu.dnetlib.dhp.schema.oaf.{Publication, Dataset => OafDataset}
import eu.dnetlib.doiboost.{DoiBoostMappingUtil, HostedByItemType}

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@ -1,4 +1,4 @@
package eu.dnetlib.dhp.doiboost
package eu.dnetlib.doiboost
import eu.dnetlib.doiboost.DoiBoostMappingUtil
import org.junit.jupiter.api.Test

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@ -3,9 +3,9 @@ package eu.dnetlib.doiboost.mag
import org.apache.spark.SparkConf
import org.apache.spark.sql.{Dataset, SparkSession}
import org.codehaus.jackson.map.ObjectMapper
import org.json4s.DefaultFormats
import org.junit.jupiter.api.Assertions._
import org.junit.jupiter.api.Test
import org.json4s.DefaultFormats
import org.slf4j.{Logger, LoggerFactory}
import java.sql.Timestamp

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@ -10,9 +10,8 @@ import org.junit.jupiter.api.io.TempDir
import org.slf4j.{Logger, LoggerFactory}
import java.nio.file.Path
import scala.io.Source
import scala.collection.JavaConversions._
import scala.io.Source
class MappingORCIDToOAFTest {
val logger: Logger = LoggerFactory.getLogger(ORCIDToOAF.getClass)

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@ -3,11 +3,11 @@ package eu.dnetlib.doiboost.uw
import com.fasterxml.jackson.databind.ObjectMapper
import eu.dnetlib.dhp.schema.oaf.OpenAccessRoute
import org.junit.jupiter.api.Assertions._
import org.junit.jupiter.api.Test
import org.slf4j.{Logger, LoggerFactory}
import scala.io.Source
import org.junit.jupiter.api.Assertions._
import org.slf4j.{Logger, LoggerFactory}
class UnpayWallMappingTest {