HyukjinKwon commented on a change in pull request #23462: [SPARK-26546][SQL]
Caching of java.time.format.DateTimeFormatter
URL: https://github.com/apache/spark/pull/23462#discussion_r245511351
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File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/DateTimeFormatterHelper.scala
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@@ -22,10 +22,40 @@ import java.time.chrono.IsoChronology
import java.time.format.{DateTimeFormatter, DateTimeFormatterBuilder,
ResolverStyle}
import java.time.temporal.{ChronoField, TemporalAccessor, TemporalQueries}
import java.util.Locale
+import java.util.concurrent.ConcurrentHashMap
trait DateTimeFormatterHelper {
+ protected def toInstantWithZoneId(temporalAccessor: TemporalAccessor,
zoneId: ZoneId): Instant = {
+ val localTime = if (temporalAccessor.query(TemporalQueries.localTime) ==
null) {
+ LocalTime.ofNanoOfDay(0)
+ } else {
+ LocalTime.from(temporalAccessor)
+ }
+ val localDate = LocalDate.from(temporalAccessor)
+ val localDateTime = LocalDateTime.of(localDate, localTime)
+ val zonedDateTime = ZonedDateTime.of(localDateTime, zoneId)
+ Instant.from(zonedDateTime)
+ }
+}
+
+object DateTimeFormatterHelper {
+ private val cache = new ConcurrentHashMap[(String, Locale),
DateTimeFormatter]()
Review comment:
Yea but this can be performed row-based operation as a corner case. For
instance, an expression that allows different formats for each value can make
this cache grows a lot. It's unlikely but pretty possible. Also, most
importantly currently it doesn't look super useful for the same reason of
https://github.com/apache/spark/pull/23462#issuecomment-451714252
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