String Length Check

README.md

@@ -240,6 +240,17 @@ Takes 2 - 4 parameters, described below. If the value in the column doesn't fall
 
 **Note:** To specify another column in the table, you must prefix the column name with a **`** (backtick).
 
+#### `stringLengthCheck`
+
+Takes 2 or 3 parameters, described in the table below. If the length of the string in the column doesn't fall within the range specified by (`minValue`, `maxValue`), both inclusive, the check will fail.
+At least one of `minValue` or `maxValue` must be specified. The data type of `column` must be String.
+
+| Arg | Type | Description |
+|-----|------|-------------|
+| `column` | String | Table column to be checked. The DataType of the column must be a String
+| `minValue` | Integer | Lower bound of the length of the string, inclusive.
+| `maxValue` | Integer | Upper bound of the length of the string, inclusive.
+
 #### `rowCount`
 
 The minimum number of rows a table must have to pass the validator.
@@ -324,6 +335,12 @@ tables:
       # nullCheck - checks if the column is null, counts number of rows with null for this column.
       - type: nullCheck
         column: occupation
+
+      # stringLengthCheck - checks if the length of the string in the column falls within the specified range, counts number of rows in which the length of the string is outside the specified range.
+            - type: stringLengthCheck
+              column: occupation
+              minValue: 1
+              maxValue: 5
 ```
 
 ## Working with OOZIE Workflows
@@ -470,4 +487,4 @@ tables:
 
       - type: nullCheck
         column: nullCol
-```
+```

src/main/scala/com/target/data_validator/validator/JsonDecoders.scala

@@ -15,6 +15,7 @@ object JsonDecoders extends LazyLogging {
       case "columnMaxCheck" => c.as[ColumnMaxCheck]
       case "rangeCheck" => RangeCheck.fromJson(c)
       case "uniqueCheck" => UniqueCheck.fromJson(c)
+      case "stringLengthCheck" => StringLengthCheck.fromJson(c)
       case x => logger.error(s"Unknown Check `$x` in config!")
         throw new RuntimeException(s"Unknown Check in config `$x`")
     }

src/main/scala/com/target/data_validator/validator/StringLengthCheck.scala

@@ -0,0 +1,126 @@
+package com.target.data_validator.validator
+
+import com.target.data_validator.{JsonEncoders, ValidatorError, VarSubstitution}
+import com.target.data_validator.JsonUtils.debugJson
+import com.target.data_validator.validator.ValidatorBase._
+import com.typesafe.scalalogging.LazyLogging
+import io.circe.{DecodingFailure, HCursor, Json}
+import io.circe.syntax._
+import org.apache.spark.sql.DataFrame
+import org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.types.{IntegerType, StringType, StructType}
+
+case class StringLengthCheck(
+                       column: String,
+                       minValue: Option[Json],
+                       maxValue: Option[Json]
+                     ) extends RowBased {
+
+  override def substituteVariables(dict: VarSubstitution): ValidatorBase = {
+
+    val ret = StringLengthCheck(
+                                  getVarSub(column, "column", dict),
+                                  minValue.map(getVarSubJson(_, "minValue", dict)),
+                                  maxValue.map(getVarSubJson(_, "maxValue", dict))
+                               )
+    getEvents.foreach(ret.addEvent)
+    ret
+  }
+
+  private def cmpExpr(colExpr: Expression,
+                      value: Option[Json],
+                      cmp: (Expression, Expression) => Expression
+                     ): Option[Expression] = {
+    value.map { v => cmp(colExpr, createLiteralOrUnresolvedAttribute(IntegerType, v)) }
+  }
+
+  override def colTest(schema: StructType, dict: VarSubstitution): Expression = {
+
+    val colExp = Length(UnresolvedAttribute(column))
+
+    val minValueExpression = cmpExpr(colExp, minValue, LessThan)
+    val maxValueExpression = cmpExpr(colExp, maxValue, GreaterThan)
+
+    val ret = (minValueExpression, maxValueExpression) match {
+      case (Some(x), None) => x
+      case (None, Some(y)) => y
+      case (Some(x), Some(y)) => Or(x, y)
+      case _ => throw new RuntimeException("Must define min or max value.")
+    }
+    logger.debug(s"Expr: $ret")
+    ret
+  }
+
+  private def checkMinLessThanOrEqualToMax(values: List[Json]): Unit = {
+
+    if (values.forall(_.isNumber)) {
+        values.flatMap(_.asNumber) match {
+          case mv :: xv :: Nil if mv.toDouble > xv.toDouble =>
+            addEvent(ValidatorError(s"min: ${minValue.get} must be less than or equal to max: ${maxValue.get}"))
+          case _ =>
+        }
+    } else if (values.forall(_.isString)) {
+        values.flatMap(_.asString) match {
+          case mv :: xv :: Nil if mv == xv =>
+            addEvent(ValidatorError(s"Min[String]: $mv must be less than max[String]: $xv"))
+          case _ =>
+        }
+    } else {
+        // Not Strings or Numbers
+        addEvent(ValidatorError(s"Unsupported type in ${values.map(debugJson).mkString(", ")}"))
+    }
+  }
+
+  override def configCheck(df: DataFrame): Boolean = {
+
+    // Verify if at least one of min or max is specified.
+    val values = (minValue::maxValue::Nil).flatten
+    if (values.isEmpty) {
+      addEvent(ValidatorError("Must define minValue or maxValue or both."))
+    }
+
+    // Verify that min is less than max
+    checkMinLessThanOrEqualToMax(values)
+
+    // Verify that the data type of the specified column is a String.
+    val colType = findColumnInDataFrame(df, column)
+    if (colType.isDefined) {
+      val dataType = colType.get.dataType
+      if (!(dataType.isInstanceOf[StringType])) {
+        addEvent(ValidatorError(s"Data type of column '$column' must be String, but was found to be $dataType"))
+      }
+    }
+
+    failed
+  }
+
+  override def toJson: Json = {
+    import JsonEncoders.eventEncoder
+    val fields = Seq(
+      ("type", Json.fromString("stringLengthCheck")),
+      ("column", Json.fromString(column))
+    ) ++
+      minValue.map(mv => ("minValue", mv)) ++
+      maxValue.map(mv => ("maxValue", mv)) ++
+      Seq(
+        ("events", getEvents.asJson)
+      )
+    Json.obj(fields: _*)
+  }
+}
+
+object StringLengthCheck extends LazyLogging {
+  def fromJson(c: HCursor): Either[DecodingFailure, ValidatorBase] = {
+    val column = c.downField("column").as[String].right.get
+    val minValueJ = c.downField("minValue").as[Json].right.toOption
+    val maxValueJ = c.downField("maxValue").as[Json].right.toOption
+
+    logger.debug(s"column: $column")
+    logger.debug(s"minValue: $minValueJ type: ${minValueJ.getClass.getCanonicalName}")
+    logger.debug(s"maxValue: $maxValueJ type: ${maxValueJ.getClass.getCanonicalName}")
+
+    c.focus.foreach {f => logger.info(s"StringLengthCheckJson: ${f.spaces2}")}
+    scala.util.Right(StringLengthCheck(column, minValueJ, maxValueJ))
+  }
+}