package eu.dnetlib.dhp.oa.graph.hostedbymap

import com.fasterxml.jackson.databind.ObjectMapper
import eu.dnetlib.dhp.application.ArgumentApplicationParser
import eu.dnetlib.dhp.oa.graph.hostedbymap.model.{DatasourceInfo, EntityInfo}

import eu.dnetlib.dhp.schema.oaf.{Journal, Publication}
import org.apache.commons.io.IOUtils
import org.apache.spark.SparkConf
import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
import org.json4s
import org.json4s.DefaultFormats
import org.json4s.jackson.JsonMethods.parse
import org.slf4j.{Logger, LoggerFactory}



object SparkPrepareHostedByInfoToApply {


  implicit val mapEncoderDSInfo: Encoder[DatasourceInfo] = Encoders.bean(classOf[DatasourceInfo])
  implicit val mapEncoderPInfo: Encoder[EntityInfo] = Encoders.bean(classOf[EntityInfo])

  def getList(id: String, j: Journal, name: String ) : List[EntityInfo] = {
    var lst:List[EntityInfo] = List()


    if (j.getIssnLinking != null && !j.getIssnLinking.equals("")){
      lst = EntityInfo.newInstance(id, j.getIssnLinking, name) :: lst
    }
    if (j.getIssnOnline != null && !j.getIssnOnline.equals("")){
      lst = EntityInfo.newInstance(id, j.getIssnOnline, name) :: lst
    }
    if (j.getIssnPrinted != null && !j.getIssnPrinted.equals("")){
      lst = EntityInfo.newInstance(id, j.getIssnPrinted, name) :: lst
    }
    lst
  }

  def prepareResultInfo(spark:SparkSession, publicationPath:String) : Dataset[EntityInfo] = {
    implicit val mapEncoderPubs: Encoder[Publication] = Encoders.bean(classOf[Publication])

    val mapper = new ObjectMapper()

    val dd : Dataset[Publication] = spark.read.textFile(publicationPath)
      .map(r => mapper.readValue(r, classOf[Publication]))

    dd.filter(p => p.getJournal != null ).flatMap(p => getList(p.getId, p.getJournal, ""))

  }


  def toEntityInfo(input:String): EntityInfo = {
    implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats

    lazy val json: json4s.JValue = parse(input)
    val c :Map[String,HostedByItemType] = json.extract[Map[String, HostedByItemType]]
    toEntityItem(c.keys.head, c.values.head)
  }

  def explodeJournalInfo(input: DatasourceInfo): List[EntityInfo] = {
    var lst : List[EntityInfo] = List()
    if (input.getEissn != null && !input.getEissn.equals("")){
      lst = EntityInfo.newInstance(input.getId, input.getEissn, input.getOfficialname, input.getOpenAccess) :: lst
    }
    if (input.getLissn != null && !input.getLissn.equals("")){
      lst = EntityInfo.newInstance(input.getId, input.getLissn, input.getOfficialname, input.getOpenAccess) :: lst
    }
    if (input.getIssn != null && !input.getIssn.equals("")){
      lst = EntityInfo.newInstance(input.getId, input.getIssn, input.getOfficialname, input.getOpenAccess) :: lst
    }

    lst
  }

  def joinDsandHBM(left:Dataset[DatasourceInfo], right:Dataset[HostedByItemType]): Dataset[EntityInfo] = {
    left.joinWith(right,
      left.col("id").equalTo(right.col("id")), "left")
      .map(t2 => {
        val dsi : DatasourceInfo = t2._1
        if(t2._2 != null){
          val hbi : HostedByItemType = t2._2
          dsi.setOpenAccess(hbi.openAccess)
        }
        dsi
      }).flatMap(explodeJournalInfo)
  }

  def toEntityItem(journal_id: String , hbi: HostedByItemType): EntityInfo = {

    EntityInfo.newInstance(hbi.id, journal_id, hbi.officialname, hbi.openAccess)

  }

  def joinResHBM(res: Dataset[EntityInfo], hbm: Dataset[EntityInfo]): Dataset[EntityInfo] = {
    Aggregators.resultToSingleId(res.joinWith(hbm, res.col("journal_id").equalTo(hbm.col("journal_id")), "left")
      .map(t2 => {
        val res: EntityInfo = t2._1
        if(t2._2 != null ){
          val ds = t2._2
          res.setHb_id(ds.getId)
          res.setOpenaccess(ds.getOpenaccess)
          res.setName(ds.getName)
        }
        res
      }))
  }

  def main(args: Array[String]): Unit = {


    val logger: Logger = LoggerFactory.getLogger(getClass)
    val conf: SparkConf = new SparkConf()
    val parser = new ArgumentApplicationParser(IOUtils.toString(getClass.getResourceAsStream("/eu/dnetlib/dhp/oa/graph/hostedbymap/hostedby_prepare_params.json")))
    parser.parseArgument(args)
    val spark: SparkSession =
      SparkSession
        .builder()
        .config(conf)
        .appName(getClass.getSimpleName)
        .master(parser.get("master")).getOrCreate()


    val graphPath = parser.get("graphPath")

    val outputPath = parser.get("outputPath")
    val hostedByMapPath = parser.get("hostedByMapPath")


    implicit val formats = DefaultFormats


    logger.info("Getting the Datasources")

    import spark.implicits._


    //STEP1: leggere la hostedbymap e trasformarla in entity info
    val hostedByInfo:Dataset[EntityInfo] = spark.createDataset(spark.sparkContext.textFile(hostedByMapPath)).map(toEntityInfo)

   //STEP2: creare la mappa publication id issn, eissn, lissn esplosa
    val resultInfoDataset:Dataset[EntityInfo] = prepareResultInfo(spark, "$graphPath/publication")

    //STEP3: join resultInfo con hostedByInfo sul journal_id dal result con left
    // e riduzione di tutti i result con lo stesso id in una unica entry con aggiunto l'id della datasource
    joinResHBM(resultInfoDataset, hostedByInfo)
      .write.mode(SaveMode.Overwrite).option("compression", "gzip").json(outputPath)


  }


}