Github user chenghao-intel commented on a diff in the pull request:
https://github.com/apache/spark/pull/224#discussion_r11007057
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringOperations.scala
---
@@ -19,11 +19,113 @@ package org.apache.spark.sql
package catalyst
package expressions
+import java.util.regex.Pattern
+
+import org.apache.spark.sql.catalyst.types.DataType
+import org.apache.spark.sql.catalyst.types.StringType
import org.apache.spark.sql.catalyst.types.BooleanType
+import org.apache.spark.sql.catalyst.trees.TreeNode
+import org.apache.spark.sql.catalyst.errors.`package`.TreeNodeException
+
+
+/**
+ * Thrown when an invalid RegEx string is found.
+ */
+class InvalidRegExException[TreeType <: TreeNode[_]](tree: TreeType,
reason: String) extends
+ errors.TreeNodeException(tree, s"$reason", null)
+
+trait StringRegexExpression {
+ self: BinaryExpression =>
+
+ type EvaluatedType = Any
+
+ def escape(v: String): String
+ def nullable: Boolean = true
+ def dataType: DataType = BooleanType
+
+ // try cache the pattern for Literal
+ private lazy val cache: Pattern = right match {
+ case x @ Literal(value: String, StringType) => compile(value)
+ case _ => null
+ }
+
+ protected def compile(str: Any): Pattern = str match {
+ // TODO or let it be null if couldn't compile the regex?
+ case x: String if(x != null) => Pattern.compile(escape(x))
+ case x: String => null
+ case _ => throw new InvalidRegExException(this, "$str can not be
compiled to regex pattern")
--- End diff --
The parameter type is String(Text) of the HIVE UDFLike.evaluate, which
means the UDF initialization will fail if the wrong type passed in. I put an
exception throwing here just to guarantee we passed the right type. You are
right, it also will throw exception if mis-match case happens, or it maybe
never happens if the HiveTypeCoercion always does the right type casting.
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