package eu.dnetlib.dhp.datacite

import com.fasterxml.jackson.databind.ObjectMapper
import eu.dnetlib.dhp.application.AbstractScalaApplication
import eu.dnetlib.dhp.collection.CollectionUtils.fixRelations
import eu.dnetlib.dhp.common.Constants.{MDSTORE_DATA_PATH, MDSTORE_SIZE_PATH}
import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup
import eu.dnetlib.dhp.schema.mdstore.{MDStoreVersion, MetadataRecord}
import eu.dnetlib.dhp.schema.oaf.Oaf
import eu.dnetlib.dhp.utils.DHPUtils.writeHdfsFile
import eu.dnetlib.dhp.utils.ISLookupClientFactory
import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
import org.slf4j.{Logger, LoggerFactory}


class GenerateDataciteDatasetSpark (propertyPath:String, args:Array[String], log:Logger) extends  AbstractScalaApplication(propertyPath, args, log:Logger) {
  /**
   * Here all the spark applications runs this method
   * where the whole logic of the spark node is defined
   */
  override def run(): Unit = {

    val sourcePath = parser.get("sourcePath")
    log.info(s"SourcePath is '$sourcePath'")
    val exportLinks = "true".equalsIgnoreCase(parser.get("exportLinks"))
    log.info(s"exportLinks is '$exportLinks'")
    val isLookupUrl: String = parser.get("isLookupUrl")
    log.info("isLookupUrl: {}", isLookupUrl)

    val isLookupService = ISLookupClientFactory.getLookUpService(isLookupUrl)
    val vocabularies = VocabularyGroup.loadVocsFromIS(isLookupService)
    require(vocabularies != null)

    val mdstoreOutputVersion = parser.get("mdstoreOutputVersion")
    log.info(s"mdstoreOutputVersion is '$mdstoreOutputVersion'")

    val mapper = new ObjectMapper()
    val cleanedMdStoreVersion = mapper.readValue(mdstoreOutputVersion, classOf[MDStoreVersion])
    val outputBasePath = cleanedMdStoreVersion.getHdfsPath
    log.info(s"outputBasePath is '$outputBasePath'")
    val targetPath = s"$outputBasePath/$MDSTORE_DATA_PATH"
    log.info(s"targetPath is '$targetPath'")

    generateDataciteDataset(sourcePath, exportLinks, vocabularies, targetPath, spark)

    reportTotalSize(targetPath, outputBasePath)
  }


  /**
   * For working with MDStore we need to store in a file on hdfs the size of
   * the current dataset
   * @param targetPath
   * @param outputBasePath
   */
  def reportTotalSize( targetPath: String, outputBasePath: String ):Unit = {
    val total_items = spark.read.load(targetPath).count()
    writeHdfsFile(spark.sparkContext.hadoopConfiguration, s"$total_items", outputBasePath + MDSTORE_SIZE_PATH)
  }

  /**
   * Generate the transformed and cleaned OAF Dataset from the native one

   * @param sourcePath  sourcePath of the native Dataset in format JSON/Datacite
   * @param exportLinks If true it generates unresolved links
   * @param vocabularies vocabularies for cleaning
   * @param targetPath the targetPath of the result Dataset
   */
  def generateDataciteDataset(sourcePath: String, exportLinks: Boolean, vocabularies: VocabularyGroup, targetPath: String, spark:SparkSession):Unit = {
    require(spark!= null)
    import spark.implicits._

    implicit val mrEncoder: Encoder[MetadataRecord] = Encoders.kryo[MetadataRecord]

    implicit val resEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
    spark.read.load(sourcePath).as[DataciteType]
      .filter(d => d.isActive)
      .flatMap(d => DataciteToOAFTransformation.generateOAF(d.json, d.timestamp, d.timestamp, vocabularies, exportLinks))
      .filter(d => d != null)
      .flatMap(i => fixRelations(i)).filter(i => i != null)
      .write.mode(SaveMode.Overwrite).save(targetPath)
  }

}


object GenerateDataciteDatasetSpark {

  val log: Logger = LoggerFactory.getLogger(GenerateDataciteDatasetSpark.getClass)

  def main(args: Array[String]): Unit = {
    new GenerateDataciteDatasetSpark("/eu/dnetlib/dhp/datacite/generate_dataset_params.json", args, log).initialize().run()
  }
}