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VerificationResult.scala
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VerificationResult.scala
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/**
* Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License"). You may not
* use this file except in compliance with the License. A copy of the License
* is located at
*
* http://aws.amazon.com/apache2.0/
*
* or in the "license" file accompanying this file. This file 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 com.amazon.deequ
import com.amazon.deequ.analyzers.Analyzer
import com.amazon.deequ.analyzers.runners.AnalyzerContext
import com.amazon.deequ.checks.{Check, CheckResult, CheckStatus}
import com.amazon.deequ.metrics.Metric
import com.amazon.deequ.repository.SimpleResultSerde
import org.apache.spark.sql.{DataFrame, SparkSession}
/**
* The result returned from the VerificationSuite
*
* @param status The overall status of the Verification run
* @param checkResults Checks and their CheckResults
* @param metrics Analyzers and their Metric results
*/
case class VerificationResult(
status: CheckStatus.Value,
checkResults: Map[Check, CheckResult],
metrics: Map[Analyzer[_, Metric[_]], Metric[_]])
object VerificationResult {
def successMetricsAsDataFrame(
sparkSession: SparkSession,
verificationResult: VerificationResult,
forAnalyzers: Seq[Analyzer[_, Metric[_]]] = Seq.empty)
: DataFrame = {
val metricsAsAnalyzerContext = AnalyzerContext(verificationResult.metrics)
AnalyzerContext.successMetricsAsDataFrame(sparkSession, metricsAsAnalyzerContext, forAnalyzers)
}
def successMetricsAsJson(verificationResult: VerificationResult,
forAnalyzers: Seq[Analyzer[_, Metric[_]]] = Seq.empty): String = {
val metricsAsAnalyzerContext = AnalyzerContext(verificationResult.metrics)
AnalyzerContext.successMetricsAsJson(metricsAsAnalyzerContext, forAnalyzers)
}
def checkResultsAsDataFrame(
sparkSession: SparkSession,
verificationResult: VerificationResult,
forChecks: Seq[Check] = Seq.empty)
: DataFrame = {
val simplifiedCheckResults = getSimplifiedCheckResultOutput(verificationResult)
import sparkSession.implicits._
simplifiedCheckResults.toDF("check", "check_level", "check_status", "constraint",
"constraint_status", "constraint_message")
}
def checkResultsAsJson(verificationResult: VerificationResult,
forChecks: Seq[Check] = Seq.empty): String = {
val simplifiedCheckResults = getSimplifiedCheckResultOutput(verificationResult)
val checkResults = simplifiedCheckResults
.map { simpleCheckResultOutput =>
Map(
"check" -> simpleCheckResultOutput.checkDescription,
"check_level" -> simpleCheckResultOutput.checkLevel,
"check_status" -> simpleCheckResultOutput.checkStatus,
"constraint" -> simpleCheckResultOutput.constraint,
"constraint_status" -> simpleCheckResultOutput.constraintStatus,
"constraint_message" -> simpleCheckResultOutput.constraintMessage
)
}
SimpleResultSerde.serialize(checkResults)
}
private[this] def getSimplifiedCheckResultOutput(
verificationResult: VerificationResult)
: Seq[SimpleCheckResultOutput] = {
val selectedCheckResults = verificationResult.checkResults
.values
.toSeq
selectedCheckResults
.flatMap { checkResult =>
checkResult.constraintResults.map { constraintResult =>
SimpleCheckResultOutput(
checkResult.check.description,
checkResult.check.level.toString,
checkResult.status.toString,
constraintResult.constraint.toString,
constraintResult.status.toString,
constraintResult.message.getOrElse("")
)
}
}
}
private[this] case class SimpleCheckResultOutput(checkDescription: String, checkLevel: String,
checkStatus: String, constraint: String, constraintStatus: String, constraintMessage: String)
}