package mobvista.dmp.datasource.taobao

import java.net.URI

import mobvista.dmp.common.CommonSparkJob
import mobvista.dmp.format.TextMultipleOutputFormat
import org.apache.commons.cli.Options
import org.apache.hadoop.fs.{FileSystem, Path}
import org.apache.hadoop.io.Text
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.{Row, SparkSession}

import scala.collection.mutable
import scala.collection.mutable.ArrayBuffer

class AlipayLaHuoDaily extends CommonSparkJob with Serializable  {


  override protected def buildOptions(): Options = {
    val options = new Options
    options.addOption("imeioutput", true, "[must] imeioutput")
    options.addOption("today", true, "[must] today")
    options.addOption("last_req_day", true, "[must] last_req_day")
    options.addOption("dt_after_one_day", true, "[must] dt_after_one_day")
    options.addOption("input_one_day", true, "[must] input_one_day")
    options.addOption("input_two_day", true, "[must] input_two_day")
    options.addOption("input_three_day", true, "[must] input_three_day")
    options.addOption("input_four_day", true, "[must] input_four_day")
    options
  }

  override protected def run(args: Array[String]): Int = {
    val commandLine = commParser.parse(options, args)
    if (!checkMustOption(commandLine)) {
      printUsage(options)
      return -1
    } else printOptions(commandLine)

    val imeioutput = commandLine.getOptionValue("imeioutput")
    val today = commandLine.getOptionValue("today")
    val last_req_day = commandLine.getOptionValue("last_req_day")
    val dt_after_one_day = commandLine.getOptionValue("dt_after_one_day")
    val input_one_day = commandLine.getOptionValue("input_one_day")
    val input_two_day = commandLine.getOptionValue("input_two_day")
    val input_three_day = commandLine.getOptionValue("input_three_day")
    val input_four_day = commandLine.getOptionValue("input_four_day")


    val spark = SparkSession.builder()
      .appName("AlipayLaHuoDaily")
      .config("spark.rdd.compress", "true")
      .config("spark.io.compression.codec", "snappy")
      .config("spark.sql.orc.filterPushdown", "true")
      .config("spark.sql.warehouse.dir", "s3://mob-emr-test/spark-warehouse")
      .config("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
      .enableHiveSupport()
      .getOrCreate()

    FileSystem.get(new URI(s"s3://mob-emr-test"), spark.sparkContext.hadoopConfiguration).delete(new Path(imeioutput), true)
    import spark.implicits._

    try {

      val sql1=
        s"""
           |select XX.device_id_md5
           |FROM (select X.device_id_md5,X.device_id,X.device_type,
           |row_number() over(partition by X.device_id_md5 order by X.device_type asc) rk
           |from ( select device_id,device_type,
           |case when device_type = 'imei' then MD5(device_id) when device_type = 'imeimd5' then device_id end as device_id_md5
           |from dwh.ods_dmp_user_info where dt ='${today}'
           | and device_type in ('imei','imeimd5')
           | and last_req_day >='${last_req_day}'
           | and  upper(country) = 'CN' ) X ) XX
           | WHERE XX.rk= 1
        """.stripMargin

//      val sql2=
//        s"""
//          |select distinct device_id from dwh.etl_alipay_activation_daily where dt='${dt_after_one_day}'  and business in ('alipay_activation') and package_name in ('com.alipay.foractivation')
//          |""".stripMargin
//
//      val yesterday_success_data = spark.sql(sql2).repartition(500).rdd.map(_.mkString)
//      val num_yesterday_success_data: Int = yesterday_success_data.count().toInt
//
//      val oldData = spark.sparkContext.textFile(input_one_day).flatMap(_.split(",")).subtract(yesterday_success_data)

//      val subtractRdd: RDD[String] = spark.sql(sql1).repartition(500).rdd.map(_.mkString).subtract(yesterday_success_data).subtract(oldData)

      val subtractRdd: RDD[String] = spark.sql(sql1).repartition(500).rdd.map(_.mkString)
      var resultRdd: RDD[String] = spark.sparkContext.emptyRDD[String]
      val lahuo_data_size =300000000
      resultRdd=subtractRdd.toDF.limit(lahuo_data_size).rdd.map(_.mkString)

//      val num: Int = subtractRdd.count().toInt
//      val lahuo_data_size =300000000 - num_yesterday_success_data
//      if(num>=lahuo_data_size){
//        println("number is enough, number is "+num)
//        resultRdd=subtractRdd.toDF.limit(lahuo_data_size).rdd.map(_.mkString)
//      }else{
//        println("number is not enough,after deduplication number is "+num)
//        resultRdd=subtractRdd
//          .union(oldData.distinct().toDF.limit(lahuo_data_size-num).rdd.map(_.mkString))
//      }
//      resultRdd=resultRdd.union(yesterday_success_data)
//      println("resultRdd.getNumPartitions=========="+resultRdd.getNumPartitions)

      resultRdd.repartition(500).mapPartitions(rs => {
        val array = new ArrayBuffer[String]()
        var devidSet = new mutable.HashSet[String]()
        while (rs.hasNext) {
          devidSet.add(rs.next())
          if (devidSet.size == 5) {
            array += devidSet.mkString(",")
            devidSet = new mutable.HashSet[String]()
          } else if (devidSet.size < 5 && !rs.hasNext) {
            array += devidSet.mkString(",")
          }
        }
        array.iterator
      }).map(device_ids => Tuple2(new Text( "0"+ (1+scala.util.Random.nextInt(4)).toString+", "), new Text(device_ids))).saveAsNewAPIHadoopFile(s"${imeioutput}", classOf[Text], classOf[Text], classOf[TextMultipleOutputFormat], spark.sparkContext.hadoopConfiguration)

//      yesterday_success_data.repartition(500).mapPartitions(rs => {
//        val array = new ArrayBuffer[String]()
//        var devidSet = new mutable.HashSet[String]()
//        while (rs.hasNext) {
//          devidSet.add(rs.next())
//          if (devidSet.size == 5) {
//            array += devidSet.mkString(",")
//            devidSet = new mutable.HashSet[String]()
//          } else if (devidSet.size < 5 && !rs.hasNext) {
//            array += devidSet.mkString(",")
//          }
//        }
//        array.iterator
//      }).saveAsTextFile(imeioutput+"/01")

    } finally {
      spark.stop()
    }
    0
  }
}

object AlipayLaHuoDaily {
  def main(args: Array[String]): Unit = {
    new AlipayLaHuoDaily().run(args)
  }
}