// Query with two current_date's
import org.apache.spark.sql.functions.current_date
val q = spark.range(1).select(current_date() as "d1", current_date() as "d2")
val analyzedPlan = q.queryExecution.analyzed

scala> println(analyzedPlan.numberedTreeString)
00 Project [current_date(Some(Europe/Warsaw)) AS d1#12, current_date(Some(Europe/Warsaw)) AS d2#13]
01 +- Range (0, 1, step=1, splits=Some(8))

import org.apache.spark.sql.catalyst.optimizer.ComputeCurrentTime

val afterComputeCurrentTime = ComputeCurrentTime(analyzedPlan)
scala> println(afterComputeCurrentTime.numberedTreeString)
00 Project [17773 AS d1#12, 17773 AS d2#13]
01 +- Range (0, 1, step=1, splits=Some(8))

// Another query with two current_timestamp's
// Here the millis play a bigger role so it is easier to notice the results
import org.apache.spark.sql.functions.current_timestamp
val q = spark.range(1).select(current_timestamp() as "ts1", current_timestamp() as "ts2")
val analyzedPlan = q.queryExecution.analyzed
val afterComputeCurrentTime = ComputeCurrentTime(analyzedPlan)
scala> println(afterComputeCurrentTime.numberedTreeString)
00 Project [1535629687768000 AS ts1#18, 1535629687768000 AS ts2#19]
01 +- Range (0, 1, step=1, splits=Some(8))