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/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information 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,
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* See the License for the specific language governing permissions and
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package org.apache.griffin.measure.sink
import org.apache.spark.sql.{DataFrame, Row}
import org.apache.spark.sql.types._
import org.scalatest.{FlatSpec, Matchers}
import org.apache.griffin.measure.{Loggable, SparkSuiteBase}
import org.apache.griffin.measure.configuration.dqdefinition.SinkParam
import org.apache.griffin.measure.configuration.enums.ProcessType.BatchProcessType
import org.apache.griffin.measure.context.{ContextId, DQContext}
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)
}
}