Added similar logic to RowLevelConstraint as well

Skipped RowLevelGroupedConstraint because only UniqueValueRatio/Uniqueness use it, and they don't use preconditions.
awslabs · Dec 17, 2024 · 2e7b2d8 · 2e7b2d8
1 parent ddc0942
commit 2e7b2d8
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Showing 2 changed files with 46 additions and 19 deletions.
diff --git a/src/main/scala/com/amazon/deequ/VerificationResult.scala b/src/main/scala/com/amazon/deequ/VerificationResult.scala
@@ -147,7 +147,7 @@ object VerificationResult {
       case asserted: RowLevelAssertedConstraint =>
         constraintResult.metric.flatMap(metricToColumn).map(asserted.assertion(_)).orElse(Some(lit(false)))
       case _: RowLevelConstraint =>
-        constraintResult.metric.flatMap(metricToColumn)
+        constraintResult.metric.flatMap(metricToColumn).orElse(Some(lit(false)))
       case _: RowLevelGroupedConstraint =>
         constraintResult.metric.flatMap(metricToColumn)
       case _ => None

diff --git a/src/test/scala/com/amazon/deequ/VerificationSuiteTest.scala b/src/test/scala/com/amazon/deequ/VerificationSuiteTest.scala
@@ -2005,24 +2005,51 @@ class VerificationSuiteTest extends WordSpec with Matchers with SparkContextSpec
         ("4", 4, "red"),
         ("5", 5, "purple")
       ).toDF("id", "id2", "color")
-      val invalidColumn = "id"
-      val validColumn = "id2"
-      val checkOnInvalidColumnDescription = s"check on $invalidColumn"
-      val checkOnValidColumnDescription = s"check on $validColumn"
-      val checkOnInvalidColumn = Check(CheckLevel.Error, checkOnInvalidColumnDescription)
-        .hasMin(invalidColumn, _ >= 3)
-        .isComplete(invalidColumn)
-      val checkOnValidColumn = Check(CheckLevel.Error, checkOnValidColumnDescription)
-        .hasMin(validColumn, _ >= 3)
-        .isComplete(validColumn)
-      val verificationResult =
-        VerificationSuite().onData(df).addChecks(Seq(checkOnInvalidColumn, checkOnValidColumn)).run()
-      val rowLevelResults =
-        VerificationResult.rowLevelResultsAsDataFrame(sparkSession, verificationResult, df).collect()
-      val invalidColumnCheckRowLevelResults = rowLevelResults.map(_.getAs[Boolean](checkOnInvalidColumnDescription))
-      val validColumnCheckRowLevelResults = rowLevelResults.map(_.getAs[Boolean](checkOnValidColumnDescription))
-      invalidColumnCheckRowLevelResults shouldBe Seq(false, false, false, false, false)
-      validColumnCheckRowLevelResults shouldBe Seq(false, false, true, true, true)
+
+      val idColumn = "id"
+      val id2Column = "id2"
+
+      val minCheckOnInvalidColumnDescription = s"min check on $idColumn"
+      val minCheckOnValidColumnDescription = s"min check on $id2Column"
+      val patternMatchCheckOnInvalidColumnDescription = s"pattern check on $id2Column"
+      val patternMatchCheckOnValidColumnDescription = s"pattern check on $idColumn"
+
+      val minCheckOnInvalidColumn = Check(CheckLevel.Error, minCheckOnInvalidColumnDescription)
+        .hasMin(idColumn, _ >= 3)
+        .isComplete(idColumn)
+      val minCheckOnValidColumn = Check(CheckLevel.Error, minCheckOnValidColumnDescription)
+        .hasMin(id2Column, _ >= 3)
+        .isComplete(id2Column)
+
+      val patternMatchCheckOnInvalidColumn = Check(CheckLevel.Error, patternMatchCheckOnInvalidColumnDescription)
+        .hasPattern(id2Column, "[0-3]+".r)
+      val patternMatchCheckOnValidColumn = Check(CheckLevel.Error, patternMatchCheckOnValidColumnDescription)
+        .hasPattern(idColumn, "[0-3]+".r)
+
+      val checks = Seq(
+        minCheckOnInvalidColumn,
+        minCheckOnValidColumn,
+        patternMatchCheckOnInvalidColumn,
+        patternMatchCheckOnValidColumn
+      )
+
+      val verificationResult = VerificationSuite().onData(df).addChecks(checks).run()
+      val rowLevelResultsDF = VerificationResult.rowLevelResultsAsDataFrame(sparkSession, verificationResult, df)
+      val rowLevelResults = rowLevelResultsDF.collect()
+
+      val minCheckOnInvalidColumnRowLevelResults =
+        rowLevelResults.map(_.getAs[Boolean](minCheckOnInvalidColumnDescription))
+      val minCheckOnValidColumnRowLevelResults =
+        rowLevelResults.map(_.getAs[Boolean](minCheckOnValidColumnDescription))
+      val patternMatchCheckOnInvalidColumnRowLevelResults =
+        rowLevelResults.map(_.getAs[Boolean](patternMatchCheckOnInvalidColumnDescription))
+      val patternMatchCheckOnValidColumnRowLevelResults =
+        rowLevelResults.map(_.getAs[Boolean](patternMatchCheckOnValidColumnDescription))
+
+      minCheckOnInvalidColumnRowLevelResults shouldBe Seq(false, false, false, false, false)
+      minCheckOnValidColumnRowLevelResults shouldBe Seq(false, false, true, true, true)
+      patternMatchCheckOnInvalidColumnRowLevelResults shouldBe Seq(false, false, false, false, false)
+      patternMatchCheckOnValidColumnRowLevelResults shouldBe Seq(true, true, true, false, false)
     }
 
     "yield correct results for satisfies check" in withSparkSession { sparkSession =>