Github user concretevitamin commented on a diff in the pull request:
https://github.com/apache/spark/pull/1055#discussion_r13683959
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/predicates.scala
---
@@ -202,3 +203,139 @@ case class If(predicate: Expression, trueValue:
Expression, falseValue: Expressi
override def toString = s"if ($predicate) $trueValue else $falseValue"
}
+
+// scalastyle:off
+/**
+ * Case statements of the form "CASE WHEN a THEN b [WHEN c THEN d]* [ELSE
e] END".
+ * Refer to this link for the corresponding semantics:
+ *
https://cwiki.apache.org/confluence/display/Hive/LanguageManual+UDF#LanguageManualUDF-ConditionalFunctions
+ *
+ * Note that branches are considered in consecutive pairs (cond, val), and
the optional last element
+ * is the val for the default catch-all case (if provided). Hence,
`branches` consist of at least
+ * two elements, and can have an odd or even length.
+ */
+// scalastyle:on
+case class CaseWhen(branches: Seq[Expression]) extends Expression {
+ type EvaluatedType = Any
+ def children = branches
+ def references = children.flatMap(_.references).toSet
+ def dataType = {
+ if (!resolved) {
+ throw new UnresolvedException(this, "cannot resolve due to differing
types in some branches")
+ }
+ branches(1).dataType
+ }
+
+ override def nullable = branches.sliding(2, 2).map {
+ case Seq(cond, value) => value.nullable
+ case Seq(elseValue) => elseValue.nullable
+ }.reduce(_ || _)
+
+ override lazy val resolved = {
+ lazy val allCondBooleans = branches.sliding(2, 2).map {
+ case Seq(cond, value) => cond.dataType == BooleanType
+ case _ => true
+ }.reduce(_ && _)
+ lazy val dataTypes = branches.sliding(2, 2).map {
+ case Seq(cond, value) => value.dataType
+ case Seq(elseValue) => elseValue.dataType
+ }.toSeq
+ lazy val dataTypesEqual =
+ if (dataTypes.size <= 1) true else dataTypes.drop(1).map(_ ==
dataTypes(0)).reduce(_ && _)
+ if (!childrenResolved) false else allCondBooleans && dataTypesEqual
+ }
+
+ /** Written in imperative fashion for performance considerations. Same
for CaseKeyWhen. */
+ override def eval(input: Row): Any = {
+ val branchesArr = branches.toArray
+ val len = branchesArr.length
+ var i = 0
+ // If all branches fail and an elseVal is not provided, the whole
statement
+ // defaults to null, according to Hive's semantics.
+ var res: Any = null
+ while (i < len - 1) {
+ if (branches(i).eval(input) == true) {
+ res = branches(i + 1).eval(input)
+ return res
+ }
+ i += 2
+ }
+ if (i == len - 1) {
+ res = branches(i).eval(input)
+ }
+ res
+ }
+
+ override def toString = {
+ val firstBranch = s"if (${branches(0)} == true) { ${branches(1)} }"
+ val otherBranches = branches.sliding(2, 2).drop(1).map {
+ case Seq(cond, value) => s" else if ($cond == true) { $value }"
+ case Seq(elseValue) => s" else { $elseValue }"
+ }.mkString
+ firstBranch ++ otherBranches
+ }
+}
+
+/**
+ * Case statements of the form "CASE a WHEN b THEN c [WHEN d THEN e]*
[ELSE f] END". This type
+ * of case statements is separated out from the other type mainly due to
performance reason: this
+ * approach avoids branching (based on whether or not the key is provided)
in eval().
+ */
+case class CaseKeyWhen(key: Expression, branches: Seq[Expression]) extends
Expression {
--- End diff --
I have to admit there are a lot of code duplication here. Directly
subclassing a case class is prohibited, so we need some other ways to achieve
code reuse without paying too much performance penalty (e.g., as discussed
before we don't want to have a single case class that carries a field like
`key: Option[Expression]`). Any suggestions are welcomed!
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