I am using Spark 2.1 with Scala.
How to convert a string column with milliseconds to a timestamp with milliseconds?
I tried the following code from the question Better way to convert a string field into timestamp in Spark
import org.apache.spark.sql.functions.unix_timestamp
val tdf = Seq((1L, "05/26/2016 01:01:01.601"), (2L, "#$@#@#")).toDF("id", "dts")
val tts = unix_timestamp($"dts", "MM/dd/yyyy HH:mm:ss.SSS").cast("timestamp")
tdf.withColumn("ts", tts).show(2, false)
But I get the result without milliseconds:
+---+-----------------------+---------------------+
|id |dts |ts |
+---+-----------------------+---------------------+
|1 |05/26/2016 01:01:01.601|2016-05-26 01:01:01.0|
|2 |#$@#@# |null |
+---+-----------------------+---------------------+
UDF with SimpleDateFormat works. The idea is taken from the Ram Ghadiyaram's link to an UDF logic.
import java.text.SimpleDateFormat
import java.sql.Timestamp
import org.apache.spark.sql.functions.udf
import scala.util.{Try, Success, Failure}
val getTimestamp: (String => Option[Timestamp]) = s => s match {
case "" => None
case _ => {
val format = new SimpleDateFormat("MM/dd/yyyy' 'HH:mm:ss.SSS")
Try(new Timestamp(format.parse(s).getTime)) match {
case Success(t) => Some(t)
case Failure(_) => None
}
}
}
val getTimestampUDF = udf(getTimestamp)
val tdf = Seq((1L, "05/26/2016 01:01:01.601"), (2L, "#$@#@#")).toDF("id", "dts")
val tts = getTimestampUDF($"dts")
tdf.withColumn("ts", tts).show(2, false)
with output:
+---+-----------------------+-----------------------+
|id |dts |ts |
+---+-----------------------+-----------------------+
|1 |05/26/2016 01:01:01.601|2016-05-26 01:01:01.601|
|2 |#$@#@# |null |
+---+-----------------------+-----------------------+
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