Better way to convert a string field into timestamp in Spark

Question

I have a CSV in which a field is datetime in a specific format. I cannot import it directly in my Dataframe because it needs to be a timestamp. So I import it as string and

Answer 1

I have ISO8601 timestamp in my dataset and I needed to convert it to "yyyy-MM-dd" format. This is what I did:

import org.joda.time.{DateTime, DateTimeZone}
object DateUtils extends Serializable {
  def dtFromUtcSeconds(seconds: Int): DateTime = new DateTime(seconds * 1000L, DateTimeZone.UTC)
  def dtFromIso8601(isoString: String): DateTime = new DateTime(isoString, DateTimeZone.UTC)
}

sqlContext.udf.register("formatTimeStamp", (isoTimestamp : String) => DateUtils.dtFromIso8601(isoTimestamp).toString("yyyy-MM-dd"))

And you can just use the UDF in your spark SQL query.