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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.sink

import org.apache.spark.sql.DataFrame
import org.apache.spark.sql.Row
import org.apache.spark.sql.types._
import org.scalatest.FlatSpec
import org.scalatest.Matchers

import org.apache.griffin.measure.Loggable
import org.apache.griffin.measure.configuration.dqdefinition.SinkParam
import org.apache.griffin.measure.configuration.enums.BatchProcessType
import org.apache.griffin.measure.context.{ContextId, DQContext}
import org.apache.griffin.measure.SparkSuiteBase

trait SinkTestBase extends FlatSpec with Matchers with SparkSuiteBase with Loggable {

  var sinkParams: Seq[SinkParam]

  def getDqContext(name: String = "test-context"): DQContext = {
    DQContext(
      ContextId(System.currentTimeMillis),
      name,
      Nil,
      sinkParams,
      BatchProcessType
    )(spark)
  }


  def createDataFrame(arr: Seq[Int]): DataFrame = {
    val schema = StructType(Array(
      StructField("id", LongType),
      StructField("name", StringType),
      StructField("sex", StringType),
      StructField("age", IntegerType)
    ))
    val rows = arr.map { i =>
      Row(i.toLong, s"name_$i", if (i % 2 == 0) "man" else "women", i + 15)
    }
    val rowRdd = spark.sparkContext.parallelize(rows)
    spark.createDataFrame(rowRdd, schema)
  }
}