Convert String to DataFrame using Spark/scala

Question

I want to convert String column to timestamp column , but it returns always null values .

  val t = unix_timestamp(col("tracking_time"),"MM/dd/yyyy").cast("timestamp")
   val df=   df2.withColumn("ts", t)

Any idea ?

Thank you .

Answer 1

Make sure your String column is matching with the format specified MM/dd/yyyy .

• If not matching then null will be returned.

Example:

val df2=Seq(("12/12/2020")).toDF("tracking_time")
val t = unix_timestamp(col("tracking_time"),"MM/dd/yyyy").cast("timestamp")

df2.withColumn("ts", t).show()
//+-------------+-------------------+
//|tracking_time|                 ts|
//+-------------+-------------------+
//|   12/12/2020|2020-12-12 00:00:00|
//+-------------+-------------------+

df2.withColumn("ts",unix_timestamp(col("tracking_time"),"MM/dd/yyyy").cast("timestamp")).show()
//+-------------+-------------------+
//|tracking_time|                 ts|
//+-------------+-------------------+
//|   12/12/2020|2020-12-12 00:00:00|
//+-------------+-------------------+
//(or)  by using to_timestamp function.

df2.withColumn("ts",to_timestamp(col("tracking_time"),"MM/dd/yyyy")).show()
//+-------------+-------------------+
//|tracking_time|                 ts|
//+-------------+-------------------+
//|   12/12/2020|2020-12-12 00:00:00|
//+-------------+-------------------+

Answer 2

As @Shu mentioned, the cause might have been the invalid format of tracking_time column. It is worth mentioning though, that Spark is looking for the pattern as a prefix of the column's value. Study these examples for better intuition

Seq(
  "03/29/2020 00:00",
  "03/29/2020",
  "00:00 03/29/2020",
  "03/29/2020somethingsomething"
).toDF("tracking_time")
  .withColumn("ts", unix_timestamp(col("tracking_time"), "MM/dd/yyyy").cast("timestamp"))
  .show()
//+--------------------+-------------------+
//|       tracking_time|                 ts|
//+--------------------+-------------------+
//|    03/29/2020 00:00|2020-03-29 00:00:00|
//|          03/29/2020|2020-03-29 00:00:00|
//|    00:00 03/29/2020|               null|
//|03/29/2020somethi...|2020-03-29 00:00:00|