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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

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.batch

import org.apache.spark.sql.{DataFrame, SparkSession}

import org.apache.griffin.measure.configuration.dqdefinition.DataConnectorParam
import org.apache.griffin.measure.context.TimeRange
import org.apache.griffin.measure.datasource.TimestampStorage
import org.apache.griffin.measure.utils.HdfsUtil
import org.apache.griffin.measure.utils.ParamUtil._

/**
  * batch data connector for directory with text format data in the nth depth sub-directories
  */
case class TextDirBatchDataConnector(@transient sparkSession: SparkSession,
                                     dcParam: DataConnectorParam,
                                     timestampStorage: TimestampStorage
                                    ) extends BatchDataConnector {

  val config = dcParam.getConfig

  val DirPath = "dir.path"
  val DataDirDepth = "data.dir.depth"
  val SuccessFile = "success.file"
  val DoneFile = "done.file"

  val dirPath = config.getString(DirPath, "")
  val dataDirDepth = config.getInt(DataDirDepth, 0)
  val successFile = config.getString(SuccessFile, "_SUCCESS")
  val doneFile = config.getString(DoneFile, "_DONE")

  val ignoreFilePrefix = "_"

  private def dirExist(): Boolean = {
    HdfsUtil.existPath(dirPath)
  }

  def data(ms: Long): (Option[DataFrame], TimeRange) = {
    assert(dirExist(), s"Text dir ${dirPath} is not exists!")
    val dfOpt = {
      val dataDirs = listSubDirs(dirPath :: Nil, dataDirDepth, readable)
      // touch done file for read dirs
      dataDirs.foreach(dir => touchDone(dir))

      val validDataDirs = dataDirs.filter(dir => !emptyDir(dir))

      if (validDataDirs.nonEmpty) {
        val df = sparkSession.read.text(validDataDirs: _*)
        val dfOpt = Some(df)
        val preDfOpt = preProcess(dfOpt, ms)
        preDfOpt
      } else {
        None
      }
    }
    val tmsts = readTmst(ms)
    (dfOpt, TimeRange(ms, tmsts))
  }

  private def listSubDirs(paths: Seq[String],
                          depth: Int,
                          filteFunc: (String) => Boolean): Seq[String] = {
    val subDirs = paths.flatMap { path => HdfsUtil.listSubPathsByType(path, "dir", true) }
    if (depth <= 0) {
      subDirs.filter(filteFunc)
    } else {
      listSubDirs(subDirs, depth - 1, filteFunc)
    }
  }

  private def readable(dir: String): Boolean = isSuccess(dir) && !isDone(dir)
  private def isDone(dir: String): Boolean = HdfsUtil.existFileInDir(dir, doneFile)
  private def isSuccess(dir: String): Boolean = HdfsUtil.existFileInDir(dir, successFile)

  private def touchDone(dir: String): Unit =
    HdfsUtil.createEmptyFile(HdfsUtil.getHdfsFilePath(dir, doneFile))

  private def emptyDir(dir: String): Boolean = {
    HdfsUtil.listSubPathsByType(dir, "file").filter(!_.startsWith(ignoreFilePrefix)).size == 0
  }

//  def metaData(): Try[Iterable[(String, String)]] = {
//    Try {
//      val st = sparkSession.read.format("com.databricks.spark.avro").
  //       load(concreteFileFullPath).schema
//      st.fields.map(f => (f.name, f.dataType.typeName))
//    }
//  }

}