package cn.piesat.controller

import java.text.{DecimalFormat, SimpleDateFormat}
import java.util
import java.util.concurrent.{CountDownLatch, Executors, Future}

import ba.common.log.enums.{LogLevel, LogType}
import ba.common.log.utils.LogUtil
import cn.piesat.constants.{HbaseZookeeperConstant, RowkeyConstant}
import cn.piesat.domain._
import cn.piesat.service.impl.{MsgServiceImpl, SparkTaskServiceImpl}
import cn.piesat.thread.HbaseQueryThread
import com.google.gson.Gson
import org.apache.hadoop.hbase.HBaseConfiguration
import org.apache.hadoop.hbase.client.{Result, Scan}
import org.apache.hadoop.hbase.filter.{Filter, FilterList}
import org.apache.hadoop.hbase.mapreduce.TableInputFormat
import org.apache.hadoop.hbase.protobuf.ProtobufUtil
import org.apache.hadoop.hbase.util.{Base64, Bytes}
import org.apache.hadoop.hbase.io.ImmutableBytesWritable
import org.apache.spark.rdd.RDD
import org.apache.spark.{SparkConf, SparkContext}
import pie.storage.db.domain._
import pie.storage.db.enums.{CompareOp, DataBaseType}

/**
  * @author liujie
  *         spark查询hbase的入口类
  */
object HbaseReader {
  val sparkTaskService = new SparkTaskServiceImpl
  val msgService = new MsgServiceImpl
  val sparkAppName = "sparkApp"
  val sparkMaster = "local[6]"
  var taskId = 8
  val serviceNum = 76
  val systemId = 12011
  val systemName = "8888"
  val cf = "cf1"
  val cell = "content"
  val zookeeperHost = "bigdata03,bigdata04,bigdata05"
  val zookeeperPort = "2181"
  val excutor=Executors.newCachedThreadPool()

  def main(args: Array[String]): Unit = {
    try{
      if (args.length > 0) {
        taskId = args(0).toInt
      }
      /**
        * 第一步，获取SparkContext对象
        */
      val sc = getSparkContext
      /**
        * 第二步，获得查询参数集合
        */
      val taskParamList = getTaskParam(taskId, sc)
      /**
        * 第三步，进行hbase数据查询
        */
      val rowkeyRDD = queryHbaseData(taskParamList, sc)

      rowkeyRDD.saveAsTextFile("file://")
      println("rowkeyRDD的数量为：" + rowkeyRDD.count())
      val rowkey = rowkeyRDD.first()
      println("取出的值为："+util.Arrays.toString(rowkey._2.getValue(cf.getBytes(),cell.getBytes())))

      /**
        * 第四步，进行数据解析
        */

      /**
        * 第五步，将结果写入文本，文本地址在第二步中的taskParamList中
        */

    }catch {
      case e:Exception =>{
        e.printStackTrace()
      }
    }finally {
      excutor.shutdown()
    }


    excutor.shutdown()

  }

  /**
    * 获取任务Id
    *
    * @param args
    * @return
    */
  private def getTaskId(args: Array[String]): Int = {
    if (args == null || args.length <= 0) {
      -1;
    } else {
      try {
        args.apply(0).toInt
      } catch {
        case e: Exception =>
          -1
      }
    }
  }

  /**
    * 获取sparkContext
    *
    * @return
    */

  private def getSparkContext(): SparkContext = {
    val sparkConf = new SparkConf().setAppName(sparkAppName).setMaster(sparkMaster)
    sparkConf.set("spark.broadcast.factory", "org.apache.spark.broadcast.HttpBroadcastFactory")
    sparkConf.set("spark.network.timeout", "300")
    sparkConf.set("spark.streaming.unpersist", "true")
    sparkConf.set("spark.scheduler.listenerbus.eventqueue.size", "100000")
    sparkConf.set("spark.storage.memoryFraction", "0.5")
    sparkConf.set("spark.shuffle.consolidateFiles", "true")
    sparkConf.set("spark.shuffle.file.buffer", "64")
    sparkConf.set("spark.shuffle.memoryFraction", "0.3")
    sparkConf.set("spark.reducer.maxSizeInFlight", "24")
    sparkConf.set("spark.shuffle.io.maxRetries", "60")
    sparkConf.set("spark.shuffle.io.retryWait", "60")
    sparkConf.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
    new SparkContext(sparkConf)
  }

  /**
    * 获取sparkTask的任务参数集合
    *
    * @param taskId
    * @return
    */
  private def getTaskParam(taskId: Int, sc: SparkContext): List[Tuple4[String, String, String, util.List[Filter]]] = {
    var list: List[Tuple4[String, String, String, util.List[Filter]]] = List()
    val sparkTask = sparkTaskService.getSparkTaskByTaskId(taskId)
    val params = sparkTask.getQueryParam
    val gson = new Gson
    val sparkQueryParams = gson.fromJson(params, classOf[SparkQueryParams])
    try {
      //1.**
      val systemId = sparkQueryParams.getSystemId
      //2.开始时间
      val startTime = sparkQueryParams.getStartTime
      //3.结束时间
      val endTime = sparkQueryParams.getEndTime
      //4.**
      val stationId = sparkQueryParams.getStationId
      val paramList = sparkQueryParams.getParams
      for (i <- 0 until paramList.size()) {
        val param = paramList.get(i)
        //5.**
        val msgId = param.getMsgId
        //6.**
        val sinkId = param.getSinkId
        //7.**
        val sourceId = param.getSourceId
        //8.表名
        val tableName = msgService.getTieYuanMsgTableNameById(msgId);
        for (num <- 0 until serviceNum) {
          val rowkeyAndFilters = getRowkeyAndFilters(num, systemId, startTime, endTime, stationId, msgId, sinkId, sourceId, tableName)
          list = rowkeyAndFilters :: list
        }
      }
      list
    } catch {
      case e: Exception =>
        LogUtil.writeLog(systemId, LogLevel.ERROR, LogType.NORMAL_LOG, systemName + " Error Info:任务参数异常。" + e)
        null
    }
  }

  /**
    * hbase数据查询
    */
  private def queryHbaseData(taskParamList: List[(String, String, String, util.List[Filter])], sc: SparkContext): RDD[(ImmutableBytesWritable, Result)] = {
    var rdd: RDD[(ImmutableBytesWritable, Result)] = null
    val latch:CountDownLatch=new CountDownLatch(taskParamList.length)
    val list: util.List[Future[RDD[Tuple2[ImmutableBytesWritable, Result]]]]=new util.ArrayList[Future[RDD[Tuple2[ImmutableBytesWritable, Result]]]]()
    for (taskParam <- taskParamList) {
      list.add(excutor.submit(new HbaseQueryThread(taskParam,sc,latch)))
    }
    import scala.collection.JavaConversions._
    for(li <- list){
      if(rdd==null){
        rdd=li.get()
      }else{
        rdd=rdd.++(li.get())
      }
    }
    latch.await()
    rdd
  }


  /**
    * 获取
    *
    * @param num
    * @param systemId
    * @param startTime
    * @param endTime
    * @param stationId
    * @param msgId
    * @param sinkId
    * @param sourceId
    * @return
    */
  private def getRowkeyAndFilters(num: Int, systemId: Int, startTime: String,
                                  endTime: String, stationId: Int, msgId: Int,
                                  sinkId: Int, sourceId: Int,
                                  tableName: String): Tuple4[String, String, String, util.List[Filter]]

  = {
    //线程非安全,因此每次调用时创建新的对象
    val simpleDateFormat1 = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss:SSS")
    val simpleDateFormat2 = new SimpleDateFormat("yyyyMMddHHmmssSSS")
    val decimalFormat = new DecimalFormat("00")
    val queryDef = new QueryDef
    //1.设置数据库
    queryDef.setDataBaseType(DataBaseType.HBASE)
    //2.设置表名
    queryDef.setTableName(tableName)
    //3.设置请求参数集合
    //3.1设置**Id参数
    val systemIdParam = new QueryParam
    systemIdParam.setField(new Field(new FieldInfo(RowkeyConstant.SYSTEM_ID), new FieldValue(systemId)))
    systemIdParam.setCompareOp(CompareOp.EQUAL)
    //3.2设置**
    val msgIdParam = new QueryParam
    msgIdParam.setField(new Field(new FieldInfo(RowkeyConstant.MSG_ID), new FieldValue(msgId)))
    msgIdParam.setCompareOp(CompareOp.EQUAL)
    //3.3设置开始时间参数
    val startTimeParam = new QueryParam
    val startTimeFormat = simpleDateFormat2.format(simpleDateFormat1.parse(startTime))
    startTimeParam.setField(new Field(new FieldInfo(RowkeyConstant.TIME), new FieldValue(startTimeFormat)))
    startTimeParam.setCompareOp(CompareOp.GREATER)
    //3.4设置结束时间参数
    val endTimeParam = new QueryParam
    val endTimeFormat = simpleDateFormat2.format(simpleDateFormat1.parse(endTime))
    endTimeParam.setField(new Field(new FieldInfo(RowkeyConstant.TIME), new FieldValue(endTimeFormat)))
    endTimeParam.setCompareOp(CompareOp.LESS)
    //3.5设置**
    val sourceParam = new QueryParam
    sourceParam.setField(new Field(new FieldInfo(RowkeyConstant.SINK_ID), new FieldValue(sinkId)))
    sourceParam.setCompareOp(CompareOp.EQUAL)
    //3.6设置**
    val sinkParam = new QueryParam
    sinkParam.setField(new Field(new FieldInfo(RowkeyConstant.SOURCE_ID), new FieldValue(sourceId)))
    sinkParam.setCompareOp(CompareOp.EQUAL)
    val queryParamList = util.Arrays.asList(systemIdParam, msgIdParam, startTimeParam, endTimeParam, sourceParam, sinkParam)
    queryDef.setListQueryParam(queryParamList)
    val startRowkey = decimalFormat.format(num) + queryDef.getStartRowKey(classOf[String])
    val endRowkey = decimalFormat.format(num) + queryDef.getStopRowKey(classOf[String])
    val filters = queryDef.getFilters(2, num, classOf[String])
    new Tuple4(tableName, startRowkey, endRowkey, filters)
  }

  /**
    * 进行hbase查询
    *
    * @param taskParam
    * @param sc
    */
  def getHbaseQueryRDD(taskParam: (String, String, String, util.List[Filter]), sc: SparkContext): RDD[(ImmutableBytesWritable, Result)] = {
    val hbaseConf = HBaseConfiguration.create()
    hbaseConf.set(HbaseZookeeperConstant.HBASE_ZOOKEEPER_QUORUM, zookeeperHost)
    hbaseConf.set(HbaseZookeeperConstant.HBASE_ZOOKEEPER_PROPERTY_CLIENTPORT, zookeeperPort)
    hbaseConf.set(TableInputFormat.INPUT_TABLE, taskParam._1)
    val scan = new Scan()
    scan.setStartRow(Bytes.toBytes(taskParam._2))
    scan.setStopRow(Bytes.toBytes(taskParam._3))
    val filterList = new FilterList(FilterList.Operator.MUST_PASS_ALL, taskParam._4)
    scan.setFilter(filterList)
    hbaseConf.set(TableInputFormat.SCAN, convertScanToString(scan))
    val rs = sc.newAPIHadoopRDD(
      hbaseConf,
      classOf[TableInputFormat],
      classOf[org.apache.hadoop.hbase.io.ImmutableBytesWritable],
      classOf[org.apache.hadoop.hbase.client.Result])
    //todo 解析
    rs
//   rs.map(tuple2=>{
//     val result=tuple2._2
//     result.
//   })
  }

  private def convertScanToString(scan: Scan) = {
    val proto = ProtobufUtil.toScan(scan)
    Base64.encodeBytes(proto.toByteArray)
  }
}