forked from D-Net/dnet-hadoop
126 lines
6.9 KiB
Scala
126 lines
6.9 KiB
Scala
package eu.dnetlib.doiboost
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import eu.dnetlib.dhp.application.ArgumentApplicationParser
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import eu.dnetlib.dhp.schema.oaf.{Publication, Relation, Dataset => OafDataset}
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import eu.dnetlib.doiboost.mag.ConversionUtil
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import org.apache.commons.io.IOUtils
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import org.apache.spark.SparkConf
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import org.apache.spark.sql.functions.col
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import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
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import org.slf4j.{Logger, LoggerFactory}
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import scala.collection.JavaConverters._
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object SparkGenerateDoiBoost {
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def main(args: Array[String]): Unit = {
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val logger: Logger = LoggerFactory.getLogger(getClass)
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val conf: SparkConf = new SparkConf()
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val parser = new ArgumentApplicationParser(IOUtils.toString(getClass.getResourceAsStream("/eu/dnetlib/dhp/doiboost/generate_doiboost_params.json")))
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parser.parseArgument(args)
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val spark: SparkSession =
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SparkSession
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.builder()
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.config(conf)
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.appName(getClass.getSimpleName)
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.master(parser.get("master")).getOrCreate()
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import spark.implicits._
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val crossrefPublicationPath = parser.get("crossrefPublicationPath")
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val crossrefDatasetPath = parser.get("crossrefDatasetPath")
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val uwPublicationPath = parser.get("uwPublicationPath")
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val magPublicationPath = parser.get("magPublicationPath")
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val orcidPublicationPath = parser.get("orcidPublicationPath")
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val workingDirPath = parser.get("workingDirPath")
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// logger.info("Phase 1) repartition and move all the dataset in a same working folder")
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// spark.read.load(crossrefPublicationPath).as(Encoders.bean(classOf[Publication])).map(s => s)(Encoders.kryo[Publication]).write.mode(SaveMode.Overwrite).save(s"$workingDirPath/crossrefPublication")
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// spark.read.load(crossrefDatasetPath).as(Encoders.bean(classOf[OafDataset])).map(s => s)(Encoders.kryo[OafDataset]).write.mode(SaveMode.Overwrite).save(s"$workingDirPath/crossrefDataset")
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// spark.read.load(uwPublicationPath).as(Encoders.bean(classOf[Publication])).map(s => s)(Encoders.kryo[Publication]).write.mode(SaveMode.Overwrite).save(s"$workingDirPath/uwPublication")
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// spark.read.load(orcidPublicationPath).as(Encoders.bean(classOf[Publication])).map(s => s)(Encoders.kryo[Publication]).write.mode(SaveMode.Overwrite).save(s"$workingDirPath/orcidPublication")
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// spark.read.load(magPublicationPath).as(Encoders.bean(classOf[Publication])).map(s => s)(Encoders.kryo[Publication]).write.mode(SaveMode.Overwrite).save(s"$workingDirPath/magPublication")
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implicit val mapEncoderPub: Encoder[Publication] = Encoders.kryo[Publication]
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implicit val mapEncoderDataset: Encoder[OafDataset] = Encoders.kryo[OafDataset]
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implicit val tupleForJoinEncoder: Encoder[(String, Publication)] = Encoders.tuple(Encoders.STRING, mapEncoderPub)
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implicit val mapEncoderRel: Encoder[Relation] = Encoders.kryo[Relation]
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logger.info("Phase 2) Join Crossref with UnpayWall")
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val crossrefPublication: Dataset[(String, Publication)] = spark.read.load(s"$workingDirPath/crossrefPublication").as[Publication].map(p => (p.getId, p))
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val uwPublication: Dataset[(String, Publication)] = spark.read.load(s"$workingDirPath/uwPublication").as[Publication].map(p => (p.getId, p))
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def applyMerge(item:((String, Publication), (String, Publication))) : Publication =
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{
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val crossrefPub = item._1._2
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if (item._2!= null) {
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val otherPub = item._2._2
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if (otherPub != null) {
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crossrefPub.mergeFrom(otherPub)
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}
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}
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crossrefPub
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}
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crossrefPublication.joinWith(uwPublication, crossrefPublication("_1").equalTo(uwPublication("_1")), "left").map(applyMerge).write.mode(SaveMode.Overwrite).save(s"$workingDirPath/firstJoin")
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logger.info("Phase 3) Join Result with ORCID")
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val fj: Dataset[(String, Publication)] = spark.read.load(s"$workingDirPath/firstJoin").as[Publication].map(p => (p.getId, p))
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val orcidPublication: Dataset[(String, Publication)] = spark.read.load(s"$workingDirPath/orcidPublication").as[Publication].map(p => (p.getId, p))
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fj.joinWith(orcidPublication, fj("_1").equalTo(orcidPublication("_1")), "left").map(applyMerge).write.mode(SaveMode.Overwrite).save(s"$workingDirPath/secondJoin")
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logger.info("Phase 3) Join Result with MAG")
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val sj: Dataset[(String, Publication)] = spark.read.load(s"$workingDirPath/secondJoin").as[Publication].map(p => (p.getId, p))
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val magPublication: Dataset[(String, Publication)] = spark.read.load(s"$workingDirPath/magPublication").as[Publication].map(p => (p.getId, p))
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sj.joinWith(magPublication, sj("_1").equalTo(magPublication("_1")), "left").map(applyMerge).write.mode(SaveMode.Overwrite).save(s"$workingDirPath/doiBoostPublication")
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val doiBoostPublication: Dataset[Publication] = spark.read.load(s"$workingDirPath/doiBoostPublication").as[Publication]
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val map = DoiBoostMappingUtil.retrieveHostedByMap()
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doiBoostPublication.filter(p=>DoiBoostMappingUtil.filterPublication(p)).map(p => DoiBoostMappingUtil.fixPublication(p, map)).write.mode(SaveMode.Overwrite).save(s"$workingDirPath/doiBoostPublicationFiltered")
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val affiliationPath = parser.get("affiliationPath")
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val paperAffiliationPath = parser.get("paperAffiliationPath")
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val affiliation = spark.read.load(affiliationPath).where(col("GridId").isNotNull).select(col("AffiliationId"), col("GridId"))
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val paperAffiliation = spark.read.load(paperAffiliationPath).select(col("AffiliationId").alias("affId"), col("PaperId"))
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val a:Dataset[DoiBoostAffiliation] = paperAffiliation
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.joinWith(affiliation, paperAffiliation("affId").equalTo(affiliation("AffiliationId"))).select(col("_1.PaperId"), col("_2.AffiliationId"), col("_2.GridId")).as[DoiBoostAffiliation]
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val magPubs:Dataset[(String,Publication)]= spark.read.load(s"$workingDirPath/doiBoostPublicationFiltered").as[Publication]
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.map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p))(tupleForJoinEncoder).filter(s =>s._1!= null )
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magPubs.joinWith(a,magPubs("_1").equalTo(a("PaperId"))).flatMap(item => {
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val pub:Publication = item._1._2
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val affiliation = item._2
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val r:Relation = new Relation
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r.setSource(pub.getId)
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r.setTarget(DoiBoostMappingUtil.generateGridAffiliationId(affiliation.GridId))
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r.setRelType("resultOrganization")
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r.setRelClass("hasAuthorInstitution")
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r.setSubRelType("affiliation")
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r.setDataInfo(pub.getDataInfo)
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r.setCollectedfrom(pub.getCollectedfrom)
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val r1:Relation = new Relation
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r1.setTarget(pub.getId)
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r1.setSource(DoiBoostMappingUtil.generateGridAffiliationId(affiliation.GridId))
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r1.setRelType("resultOrganization")
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r1.setRelClass("isAuthorInstitutionOf")
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r1.setSubRelType("affiliation")
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r1.setDataInfo(pub.getDataInfo)
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r1.setCollectedfrom(pub.getCollectedfrom)
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List(r, r1)
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})(mapEncoderRel).write.mode(SaveMode.Overwrite).save(s"$workingDirPath/doiBoostPublicationAffiliation")
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}
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}
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