cloud-fan commented on a change in pull request #23597: [SPARK-26653][SQL] Use
Proleptic Gregorian calendar in parsing JDBC lower/upper bounds
URL: https://github.com/apache/spark/pull/23597#discussion_r249625251
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCRelation.scala
##########
@@ -174,10 +174,19 @@ private[sql] object JDBCRelation extends Logging {
(dialect.quoteIdentifier(column.name), column.dataType)
}
- private def toInternalBoundValue(value: String, columnType: DataType): Long
= columnType match {
- case _: NumericType => value.toLong
- case DateType => DateTimeUtils.fromJavaDate(Date.valueOf(value)).toLong
- case TimestampType =>
DateTimeUtils.fromJavaTimestamp(Timestamp.valueOf(value))
+ private def toInternalBoundValue(value: String, columnType: DataType): Long
= {
+ def parse[T](f: UTF8String => Option[T]): T = {
+ f(UTF8String.fromString(value)).getOrElse {
+ throw new IllegalArgumentException(
+ s"Cannot parse the bound value $value as
${columnType.catalogString}")
+ }
+ }
+ columnType match {
+ case _: NumericType => value.toLong
+ case DateType => parse(stringToDate).toLong
+ case TimestampType =>
+ parse(stringToTimestamp(_,
getTimeZone(SQLConf.get.sessionLocalTimeZone)))
Review comment:
Previously we call `Timestamp.valueOf(value)`, which uses JVM local
timezone. It seems to me that using Spark session timezone is better.
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