107 lines
4.1 KiB
Scala
107 lines
4.1 KiB
Scala
package eu.dnetlib.dhp.oa.graph.resolution
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import com.fasterxml.jackson.databind.ObjectMapper
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import eu.dnetlib.dhp.application.ArgumentApplicationParser
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import eu.dnetlib.dhp.common.HdfsSupport
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import eu.dnetlib.dhp.schema.common.EntityType
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import eu.dnetlib.dhp.schema.oaf.{OtherResearchProduct, Publication, Result, Software, Dataset => OafDataset}
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import org.apache.commons.io.IOUtils
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import org.apache.hadoop.fs.{FileSystem, Path}
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import org.apache.spark.SparkConf
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import org.apache.spark.sql._
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import org.slf4j.{Logger, LoggerFactory}
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object SparkResolveEntities {
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val mapper = new ObjectMapper()
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val entities = List(EntityType.dataset, EntityType.publication, EntityType.software, EntityType.otherresearchproduct)
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def main(args: Array[String]): Unit = {
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val log: 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/oa/graph/resolution/resolve_entities_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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val graphBasePath = parser.get("graphBasePath")
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log.info(s"graphBasePath -> $graphBasePath")
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val workingPath = parser.get("workingPath")
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log.info(s"workingPath -> $workingPath")
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val unresolvedPath = parser.get("unresolvedPath")
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log.info(s"unresolvedPath -> $unresolvedPath")
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val targetPath = parser.get("targetPath")
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log.info(s"targetPath -> $targetPath")
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val fs = FileSystem.get(spark.sparkContext.hadoopConfiguration)
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fs.mkdirs(new Path(workingPath))
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resolveEntities(spark, workingPath, unresolvedPath)
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generateResolvedEntities(spark, workingPath, graphBasePath, targetPath)
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}
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def resolveEntities(spark: SparkSession, workingPath: String, unresolvedPath: String) = {
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implicit val resEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
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import spark.implicits._
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val rPid: Dataset[(String, String)] = spark.read.load(s"$workingPath/relationResolvedPid").as[(String, String)]
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val up: Dataset[(String, Result)] = spark.read.text(unresolvedPath).as[String].map(s => mapper.readValue(s, classOf[Result])).map(r => (r.getId, r))(Encoders.tuple(Encoders.STRING, resEncoder))
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rPid.joinWith(up, rPid("_2").equalTo(up("_1")), "inner").map {
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r =>
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val result = r._2._2
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val dnetId = r._1._1
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result.setId(dnetId)
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result
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}.write.mode(SaveMode.Overwrite).save(s"$workingPath/resolvedEntities")
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}
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def deserializeObject(input: String, entity: EntityType): Result = {
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entity match {
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case EntityType.publication => mapper.readValue(input, classOf[Publication])
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case EntityType.dataset => mapper.readValue(input, classOf[OafDataset])
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case EntityType.software => mapper.readValue(input, classOf[Software])
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case EntityType.otherresearchproduct => mapper.readValue(input, classOf[OtherResearchProduct])
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}
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}
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def generateResolvedEntities(spark: SparkSession, workingPath: String, graphBasePath: String, targetPath:String) = {
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implicit val resEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
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import spark.implicits._
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val re: Dataset[(String, Result)] = spark.read.load(s"$workingPath/resolvedEntities").as[Result].map(r => (r.getId, r))(Encoders.tuple(Encoders.STRING, resEncoder))
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entities.foreach {
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e => {
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val currentEntityDataset: Dataset[(String, Result)] = spark.read.text(s"$graphBasePath/$e").as[String].map(s => deserializeObject(s, e)).map(r => (r.getId, r))(Encoders.tuple(Encoders.STRING, resEncoder))
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currentEntityDataset.joinWith(re, currentEntityDataset("_1").equalTo(re("_1")), "left").map(k => {
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val a = k._1
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val b = k._2
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if (b == null)
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a._2
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else {
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a._2.mergeFrom(b._2)
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a._2
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}
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}).map(r => mapper.writeValueAsString(r))(Encoders.STRING)
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.write.mode(SaveMode.Overwrite).option("compression", "gzip").text(s"$targetPath/$e")
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}
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}
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}
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}
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