Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/17633#discussion_r113596554
--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/client/HiveShim.scala ---
@@ -589,18 +590,34 @@ private[client] class Shim_v0_13 extends Shim_v0_12 {
col.getType.startsWith(serdeConstants.CHAR_TYPE_NAME))
.map(col => col.getName).toSet
- filters.collect {
- case op @ BinaryComparison(a: Attribute, Literal(v, _:
IntegralType)) =>
- s"${a.name} ${op.symbol} $v"
- case op @ BinaryComparison(Literal(v, _: IntegralType), a:
Attribute) =>
- s"$v ${op.symbol} ${a.name}"
- case op @ BinaryComparison(a: Attribute, Literal(v, _: StringType))
- if !varcharKeys.contains(a.name) =>
- s"""${a.name} ${op.symbol} ${quoteStringLiteral(v.toString)}"""
- case op @ BinaryComparison(Literal(v, _: StringType), a: Attribute)
- if !varcharKeys.contains(a.name) =>
- s"""${quoteStringLiteral(v.toString)} ${op.symbol} ${a.name}"""
- }.mkString(" and ")
+ def isFoldable(expr: Expression): Boolean =
+ (expr.dataType.isInstanceOf[IntegralType] ||
expr.dataType.isInstanceOf[StringType]) &&
+ expr.foldable &&
+ expr.deterministic
+
+ def convertFoldable(expr: Expression): String = expr.dataType match {
--- End diff --
yea, to make the code simpler, we can just match literals.
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