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regarding copyright ownership.  The ASF licenses this file
to you under the Apache License, Version 2.0 (the
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with the License.  You may obtain a copy of the License at

  http://www.apache.org/licenses/LICENSE-2.0

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*/
package org.apache.griffin.measure.launch.batch

import java.util.Date

import scala.util.Try

import org.apache.spark.SparkConf
import org.apache.spark.sql.SparkSession

import org.apache.griffin.measure.configuration.dqdefinition._
import org.apache.griffin.measure.configuration.enums._
import org.apache.griffin.measure.context._
import org.apache.griffin.measure.datasource.DataSourceFactory
import org.apache.griffin.measure.job.builder.DQJobBuilder
import org.apache.griffin.measure.launch.DQApp
import org.apache.griffin.measure.step.builder.udf.GriffinUDFAgent


case class BatchDQApp(allParam: GriffinConfig) extends DQApp {

  val envParam: EnvConfig = allParam.getEnvConfig
  val dqParam: DQConfig = allParam.getDqConfig

  val sparkParam = envParam.getSparkParam
  val metricName = dqParam.getName
  val sinkParams = getSinkParams

  var dqContext: DQContext = _

  def retryable: Boolean = false

  def init: Try[_] = Try {
    // build spark 2.0+ application context
    val conf = new SparkConf().setAppName(metricName)
    conf.setAll(sparkParam.getConfig)
    conf.set("spark.sql.crossJoin.enabled", "true")
    sparkSession = SparkSession.builder().config(conf).enableHiveSupport().getOrCreate()
    val logLevel = getGriffinLogLevel()
    sparkSession.sparkContext.setLogLevel(sparkParam.getLogLevel)
    griffinLogger.setLevel(logLevel)

    // register udf
    GriffinUDFAgent.register(sparkSession)
  }

  def run: Try[Boolean] = Try {
    // start time
    val startTime = new Date().getTime

    val measureTime = getMeasureTime
    val contextId = ContextId(measureTime)

    // get data sources
    val dataSources = DataSourceFactory.getDataSources(sparkSession, null, dqParam.getDataSources)
    dataSources.foreach(_.init)

    // create dq context
    dqContext = DQContext(
      contextId, metricName, dataSources, sinkParams, BatchProcessType
    )(sparkSession)

    // start id
    val applicationId = sparkSession.sparkContext.applicationId
    dqContext.getSink().start(applicationId)

    // build job
    val dqJob = DQJobBuilder.buildDQJob(dqContext, dqParam.getEvaluateRule)

    // dq job execute
    val result = dqJob.execute(dqContext)

    // end time
    val endTime = new Date().getTime
    dqContext.getSink().log(endTime, s"process using time: ${endTime - startTime} ms")

    // clean context
    dqContext.clean()

    // finish
    dqContext.getSink().finish()

    result
  }

  def close: Try[_] = Try {
    sparkSession.close()
    sparkSession.stop()
  }

}