cloud-fan commented on a change in pull request #35465:
URL: https://github.com/apache/spark/pull/35465#discussion_r803309117
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File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/expressions.scala
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@@ -680,42 +680,50 @@ object PushFoldableIntoBranches extends Rule[LogicalPlan]
with PredicateHelper {
* pattern.
*/
object LikeSimplification extends Rule[LogicalPlan] {
- // if guards below protect from escapes on trailing %.
- // Cases like "something\%" are not optimized, but this does not affect
correctness.
- private val startsWith = "([^_%]+)%".r
- private val endsWith = "%([^_%]+)".r
- private val startsAndEndsWith = "([^_%]+)%([^_%]+)".r
- private val contains = "%([^_%]+)%".r
- private val equalTo = "([^_%]*)".r
-
private def simplifyLike(
input: Expression, pattern: String, escapeChar: Char = '\\'):
Option[Expression] = {
- if (pattern.contains(escapeChar)) {
- // There are three different situations when pattern containing
escapeChar:
- // 1. pattern contains invalid escape sequence, e.g. 'm\aca'
- // 2. pattern contains escaped wildcard character, e.g. 'ma\%ca'
- // 3. pattern contains escaped escape character, e.g. 'ma\\ca'
- // Although there are patterns can be optimized if we handle the escape
first, we just
- // skip this rule if pattern contains any escapeChar for simplicity.
Review comment:
This is a trade-off between code simplicity and performance. The
assumption is that using escape char is rare and we shouldn't add a complicated
implementation for it.
Besides, Spark now provides `starts_with`, `ends_with`, etc. functions and
people can use them directly.
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