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regarding copyright ownership.  The ASF licenses this file
to you under the Apache License, Version 2.0 (the
"License"); you may not use this file except in compliance
with the License.  You may obtain a copy of the License at

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

Unless required by applicable law or agreed to in writing,
software distributed under the License is distributed on an
"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
KIND, either express or implied.  See the License for the
specific language governing permissions and limitations
under the License.
*/
package org.apache.griffin.measure.datasource.connector

import scala.util.Try

import org.apache.spark.sql.SparkSession
import org.apache.spark.streaming.StreamingContext

import org.apache.griffin.measure.Loggable
import org.apache.griffin.measure.configuration.dqdefinition.DataConnectorParam
import org.apache.griffin.measure.datasource.TimestampStorage
import org.apache.griffin.measure.datasource.cache.StreamingCacheClient
import org.apache.griffin.measure.datasource.connector.batch._
import org.apache.griffin.measure.datasource.connector.streaming._


object DataConnectorFactory extends Loggable {

  val HiveRegex = """^(?i)hive$""".r
  val AvroRegex = """^(?i)avro$""".r
  val FileRegex = """^(?i)file$""".r
  val TextDirRegex = """^(?i)text-dir$""".r

  val KafkaRegex = """^(?i)kafka$""".r

  val CustomRegex = """^(?i)custom$""".r

  /**
    * create data connector
    * @param sparkSession     spark env
    * @param ssc              spark streaming env
    * @param dcParam          data connector param
    * @param tmstCache        same tmst cache in one data source
    * @param streamingCacheClientOpt   for streaming cache
    * @return   data connector
    */
  def getDataConnector(sparkSession: SparkSession,
                       ssc: StreamingContext,
                       dcParam: DataConnectorParam,
                       tmstCache: TimestampStorage,
                       streamingCacheClientOpt: Option[StreamingCacheClient]
                      ): Try[DataConnector] = {
    val conType = dcParam.getType
    val version = dcParam.getVersion
    Try {
      conType match {
        case HiveRegex() => HiveBatchDataConnector(sparkSession, dcParam, tmstCache)
        case AvroRegex() => AvroBatchDataConnector(sparkSession, dcParam, tmstCache)
        case FileRegex() => FileBasedDataConnector(sparkSession, dcParam, tmstCache)
        case TextDirRegex() => TextDirBatchDataConnector(sparkSession, dcParam, tmstCache)
        case CustomRegex() => getCustomConnector(sparkSession, ssc, dcParam, tmstCache, streamingCacheClientOpt)
        case KafkaRegex() =>
          getStreamingDataConnector(sparkSession, ssc, dcParam, tmstCache, streamingCacheClientOpt)
        case _ => throw new Exception("connector creation error!")
      }
    }
  }

  private def getStreamingDataConnector(sparkSession: SparkSession,
                                        ssc: StreamingContext,
                                        dcParam: DataConnectorParam,
                                        tmstCache: TimestampStorage,
                                        streamingCacheClientOpt: Option[StreamingCacheClient]
                                       ): StreamingDataConnector = {
    if (ssc == null) throw new Exception("streaming context is null!")
    val conType = dcParam.getType
    val version = dcParam.getVersion
    conType match {
      case KafkaRegex() =>
        getKafkaDataConnector(sparkSession, ssc, dcParam, tmstCache, streamingCacheClientOpt)
      case _ => throw new Exception("streaming connector creation error!")
    }
  }

  private def getCustomConnector(sparkSession: SparkSession,
                                 ssc: StreamingContext,
                                 dcParam: DataConnectorParam,
                                 timestampStorage: TimestampStorage,
                                 streamingCacheClientOpt: Option[StreamingCacheClient]): DataConnector = {
    val className = dcParam.getConfig("class").asInstanceOf[String]
    val cls = Class.forName(className)
    if (classOf[BatchDataConnector].isAssignableFrom(cls)) {
      val method = cls.getDeclaredMethod("apply",
        classOf[SparkSession],
        classOf[DataConnectorParam],
        classOf[TimestampStorage]
      )
      method.invoke(null, sparkSession, dcParam, timestampStorage).asInstanceOf[BatchDataConnector]
    } else if (classOf[StreamingDataConnector].isAssignableFrom(cls)) {
      val method = cls.getDeclaredMethod("apply",
        classOf[SparkSession],
        classOf[StreamingContext],
        classOf[DataConnectorParam],
        classOf[TimestampStorage],
        classOf[Option[StreamingCacheClient]]
      )
      method.invoke(null, sparkSession, ssc, dcParam, timestampStorage, streamingCacheClientOpt)
        .asInstanceOf[StreamingDataConnector]
    } else {
      throw new ClassCastException(s"$className should extend BatchDataConnector or StreamingDataConnector")
    }
  }

  private def getKafkaDataConnector(sparkSession: SparkSession,
                                    ssc: StreamingContext,
                                    dcParam: DataConnectorParam,
                                    tmstCache: TimestampStorage,
                                    streamingCacheClientOpt: Option[StreamingCacheClient]
                                   ): KafkaStreamingDataConnector = {
    val KeyType = "key.type"
    val ValueType = "value.type"
    val config = dcParam.getConfig
    val keyType = config.getOrElse(KeyType, "java.lang.String").toString
    val valueType = config.getOrElse(ValueType, "java.lang.String").toString

    (keyType, valueType) match {
      case ("java.lang.String", "java.lang.String") =>
        KafkaStreamingStringDataConnector(
          sparkSession, ssc, dcParam, tmstCache, streamingCacheClientOpt)
      case _ =>
        throw new Exception("not supported type kafka data connector")
    }
  }


}