measure/src/main/scala/org/apache/griffin/measure/datasource/connector/DataConnectorFactory.scala

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

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specific language governing permissions and limitations
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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")
    }
  }



}