package io.prediction.algorithms.scalding.itemrec.generic

import com.twitter.scalding._

import io.prediction.commons.scalding.appdata.{ Items, U2iActions }
import io.prediction.commons.filepath.DataFile

/**
 * Source: appdata DB (items, u2iActions)
 * Sink: selectedItems.tsv, ratings.tsv
 * Descripton:
 *   Generic data preparator. Read from appdata DB and store selected items
 *   and ratings into a file.
 *   (appdata store -> DataPreparator -> HDFS)
 *
 * Required args:
 * --dbType: <string> (eg. mongodb) (see --dbHost, --dbPort)
 * --dbName: <string> appdata database name. (eg predictionio_appdata, or predictionio_training_appdata)
 *
 * --hdfsRoot: <string>. Root directory of the HDFS
 *
 * --appid: <int>
 * --engineid: <int>
 * --algoid: <int>
 *
 * --viewParam: <string>. (number 1 to 5, or "ignore")
 * --likeParam: <string>
 * --dislikeParam: <string>
 * --conversionParam: <string>
 * --conflictParam: <string>. (latest/highest/lowest)
 *
 * Optional args:
 * --dbHost: <string> (eg. "127.0.0.1")
 * --dbPort: <int> (eg. 27017)
 *
 * --itypes: <string separated by white space>. eg "--itypes type1 type2". If no --itypes specified, then ALL itypes will be used.
 * --evalid: <int>. Offline Evaluation if evalid is specified
 * --debug: <String>. "test" - for testing purpose
 *
 * Example:
 * Batch:
 * scald.rb --hdfs-local io.prediction.algorithms.scalding.itemrec.generic.DataPreparator --dbType mongodb --dbName appdata --dbHost 127.0.0.1 --dbPort 27017 --hdfsRoot hdfs/predictionio/ --appid 34 --engineid 3 --algoid 9 --itypes t2 --viewParam 2 --likeParam 5 --dislikeParam 1 --conversionParam 4 --conflictParam latest
 *
 * Offline Eval:
 * scald.rb --hdfs-local io.prediction.algorithms.scalding.itemrec.generic.DataPreparator --dbType mongodb --dbName training_appdata --dbHost 127.0.0.1 --dbPort 27017 --hdfsRoot hdfs/predictionio/ --appid 34 --engineid 3 --algoid 9 --itypes t2 --viewParam 2 --likeParam 5 --dislikeParam 1 --conversionParam 4 --conflictParam latest --evalid 15
 *
 */
class DataPreparator(args: Args) extends Job(args) {

  /**
   * parse arguments
   */
  val dbTypeArg = args("dbType")
  val dbNameArg = args("dbName")
  val dbHostArg = args.optional("dbHost")
  val dbPortArg = args.optional("dbPort") map (x => x.toInt) // becomes Option[Int]

  val hdfsRootArg = args("hdfsRoot")

  val appidArg = args("appid").toInt
  val engineidArg = args("engineid").toInt
  val algoidArg = args("algoid").toInt
  val evalidArg = args.optional("evalid") map (x => x.toInt)
  val OFFLINE_EVAL = (evalidArg != None) // offline eval mode

  val preItypesArg = args.list("itypes")
  val itypesArg: Option[List[String]] = if (preItypesArg.mkString(",").length == 0) None else Option(preItypesArg)

  // determine how to map actions to rating values
  def getActionParam(name: String): Option[Int] = {
    val actionParam: Option[Int] = args(name) match {
      case "ignore" => None
      case x => Some(x.toInt)
    }
    actionParam
  }

  val viewParamArg: Option[Int] = getActionParam("viewParam")
  val likeParamArg: Option[Int] = getActionParam("likeParam")
  val dislikeParamArg: Option[Int] = getActionParam("dislikeParam")
  val conversionParamArg: Option[Int] = getActionParam("conversionParam")

  // When there are conflicting actions, e.g. a user gives an item a rating 5 but later dislikes it, 
  // determine which action will be considered as final preference.
  final val CONFLICT_LATEST: String = "latest" // use latest action
  final val CONFLICT_HIGHEST: String = "highest" // use the one with highest score
  final val CONFLICT_LOWEST: String = "lowest" // use the one with lowest score

  val conflictParamArg: String = args("conflictParam")

  // check if the conflictParam is valid
  require(List(CONFLICT_LATEST, CONFLICT_HIGHEST, CONFLICT_LOWEST).contains(conflictParamArg), "conflict param " + conflictParamArg + " is not valid.")

  val debugArg = args.list("debug")
  val DEBUG_TEST = debugArg.contains("test") // test mode

  /**
   * constants
   */

  final val ACTION_RATE = "rate"
  final val ACTION_LIKE = "like"
  final val ACTION_DISLIKE = "dislike"
  final val ACTION_VIEW = "view"
  //final val ACTION_VIEWDETAILS = "viewDetails"
  final val ACTION_CONVERSION = "conversion"

  /**
   * source
   */
  // get appdata
  // NOTE: if OFFLINE_EVAL, read from training set, and use evalid as appid when read Items and U2iActions
  val trainingAppid = if (OFFLINE_EVAL) evalidArg.get else appidArg

  // get items data
  val items = Items(appId = trainingAppid, itypes = itypesArg,
    dbType = dbTypeArg, dbName = dbNameArg, dbHost = dbHostArg, dbPort = dbPortArg).readData('iidx, 'itypes)

  val u2i = U2iActions(appId = trainingAppid,
    dbType = dbTypeArg, dbName = dbNameArg, dbHost = dbHostArg, dbPort = dbPortArg).readData('action, 'uid, 'iid, 't, 'v)

  /**
   * sink
   */

  // write ratings to a file
  val ratingsSink = Tsv(DataFile(hdfsRootArg, appidArg, engineidArg, algoidArg, evalidArg, "ratings.tsv"))

  val selectedItemsSink = Tsv(DataFile(hdfsRootArg, appidArg, engineidArg, algoidArg, evalidArg, "selectedItems.tsv"))

  /**
   * computation
   */
  u2i.joinWithSmaller('iid -> 'iidx, items) // only select actions of these items
    .filter('action, 'v) { fields: (String, String) =>
      val (action, v) = fields

      val keepThis: Boolean = action match {
        case ACTION_RATE => true
        case ACTION_LIKE => (likeParamArg != None)
        case ACTION_DISLIKE => (dislikeParamArg != None)
        case ACTION_VIEW => (viewParamArg != None)
        case ACTION_CONVERSION => (conversionParamArg != None)
        case _ => {
          assert(false, "Action type " + action + " in u2iActions appdata is not supported!")
          false // all other unsupported actions
        }
      }
      keepThis
    }
    .map(('action, 'v, 't) -> ('rating, 'tLong)) { fields: (String, String, String) =>
      val (action, v, t) = fields

      // convert actions into rating value based on "action" and "v" fields
      val rating: Int = action match {
        case ACTION_RATE => v.toInt
        case ACTION_LIKE => likeParamArg.getOrElse {
          assert(false, "Action type " + action + " should have been filtered out!")
          1
        }
        case ACTION_DISLIKE => dislikeParamArg.getOrElse {
          assert(false, "Action type " + action + " should have been filtered out!")
          1
        }
        case ACTION_VIEW => viewParamArg.getOrElse {
          assert(false, "Action type " + action + " should have been filtered out!")
          1
        }
        case ACTION_CONVERSION => conversionParamArg.getOrElse {
          assert(false, "Action type " + action + " should have been filtered out!")
          1
        }
        case _ => { // all other unsupported actions
          assert(false, "Action type " + action + " in u2iActions appdata is not supported!")
          1
        }
      }

      (rating, t.toLong)
    }
    .then(resolveConflict('uid, 'iid, 'tLong, 'rating, conflictParamArg) _)
    .project('uid, 'iid, 'rating)
    .write(ratingsSink)

  // Also store the selected items into DataFile for later model construction usage.
  items.mapTo(('iidx, 'itypes) -> ('iidx, 'itypes)) { fields: (String, List[String]) =>
    val (iidx, itypes) = fields

    (iidx, itypes.mkString(",")) // NOTE: convert List[String] into comma-separated String
  }.write(selectedItemsSink)

  /**
   * function to resolve conflicting actions of same uid-iid pair.
   */
  def resolveConflict(uidField: Symbol, iidField: Symbol, tfield: Symbol, ratingField: Symbol, conflictSolution: String)(p: RichPipe): RichPipe = {

    // NOTE: sortBy() sort from smallest to largest. use reverse to pick the largest one.
    val dataPipe = conflictSolution match {
      case CONFLICT_LATEST => p.groupBy(uidField, iidField) { _.sortBy(tfield).reverse.take(1) } // take latest one (largest t)
      case CONFLICT_HIGHEST => p.groupBy(uidField, iidField) { _.sortBy(ratingField).reverse.take(1) } // take highest rating
      case CONFLICT_LOWEST => p.groupBy(uidField, iidField) { _.sortBy(ratingField).take(1) } // take lowest rating
    }

    dataPipe
  }

}