Spark Scala: DateDiff of two columns by hour or minute

Question

I have two timestamp columns in a dataframe that I'd like to get the minute difference of, or alternatively, the hour difference of. Currently I'm able to get the day difference, with rounding, by doing

val df2 = df1.withColumn("time", datediff(df1("ts1"), df1("ts2")))

However, when i looked at the doc page https://issues.apache.org/jira/browse/SPARK-8185 I didn't see any extra parameters to change the unit. Is their a different function I should be using for this?

Answer 1

The answer given by Daniel de Paula works, but that solution does not work in the case where the difference is needed for every row in your table. Here is a solution that will do that for each row:

import org.apache.spark.sql.functions

val df2 = df1.selectExpr("(unix_timestamp(ts1) - unix_timestamp(ts2))/3600")

This first converts the data in the columns to a unix timestamp in seconds, subtracts them and then converts the difference to hours.

A useful list of functions can be found at: http://spark.apache.org/docs/latest/api/scala/#org.apache.spark.sql.functions$

Answer 2

You can get the difference in seconds by

import org.apache.spark.sql.functions._
val diff_secs_col = col("ts1").cast("long") - col("ts2").cast("long")

Then you can do some math to get the unit you want. For example:

val df2 = df1
  .withColumn( "diff_secs", diff_secs_col )
  .withColumn( "diff_mins", diff_secs_col / 60D )
  .withColumn( "diff_hrs",  diff_secs_col / 3600D )
  .withColumn( "diff_days", diff_secs_col / (24D * 3600D) )

Or, in pyspark:

from pyspark.sql.functions import *
diff_secs_col = col("ts1").cast("long") - col("ts2").cast("long")

df2 = df1 \
  .withColumn( "diff_secs", diff_secs_col ) \
  .withColumn( "diff_mins", diff_secs_col / 60D ) \
  .withColumn( "diff_hrs",  diff_secs_col / 3600D ) \
  .withColumn( "diff_days", diff_secs_col / (24D * 3600D) )