package eu.dnetlib.dhp.bioschema

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

class GenerateBioschemaDatasetSpark(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 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'")

    generateBioschemaDataset(sourcePath, exportLinks, 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.text(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 targetPath the targetPath of the result Dataset
    */
  def generateBioschemaDataset(
    sourcePath: String,
    exportLinks: Boolean,
    targetPath: String,
    spark: SparkSession
  ): Unit = {
    require(spark != null)

    implicit val resultEncoder: Encoder[Oaf] = Encoders.kryo(classOf[Oaf])
    CollectionUtils.saveDataset(
      spark.createDataset(
        spark.sparkContext
          .textFile(sourcePath)
          .flatMap(i => BioschemaToOAFTransformation.generateOAF(i, exportLinks))
      ),
      targetPath
    )
  }
}