Reputation: 8721
I need to convert a descriptive date format from a log file "MMM dd, yyyy hh:mm:ss AM/PM" to the spark timestamp datatype. I tried something like below, but it is giving null.
val df = Seq(("Nov 05, 2018 02:46:47 AM"),("Nov 5, 2018 02:46:47 PM")).toDF("times")
df.withColumn("time2",date_format('times,"MMM dd, yyyy HH:mm:ss AM")).show(false)
+------------------------+-----+
|times |time2|
+------------------------+-----+
|Nov 05, 2018 02:46:47 AM|null |
|Nov 5, 2018 02:46:47 PM |null |
+------------------------+-----+
Expected output
+------------------------+----------------------------+
|times |time2 |
+------------------------+-----+----------------------+
|Nov 05, 2018 02:46:47 AM|2018-11-05 02:46:47.000000" |
|Nov 5, 2018 02:46:47 PM |2018-11-05 14:46:47.000000" |
+------------------------+-----+----------------------+
What is the proper format for converting this?. Note that DD may be having leading zeroes.
Upvotes: 2
Views: 17741
Reputation: 41
We can use splitby
Select date.split('-')[2]||'-'||case when length(date.split('-')[0]) = 1 then '0'||date.split('-')[0] else date.split('-')[0] end || case when length(date.split('-')[1]) = 1 then '0'||date.split('-')[1] else date.split('-')[1] end]
Date = date_column
Date format yyyy-mm-dd
Delimiter can be different.
Without any date format
Upvotes: -1
Reputation: 1189
Here is your answer
val df = Seq(("Nov 05, 2018 02:46:47 AM"),("Nov 5, 2018 02:46:47 PM")).toDF("times")
scala> df.withColumn("times2", from_unixtime(unix_timestamp(col("times"), "MMM d, yyyy hh:mm:ss a"),"yyyy-MM-dd HH:mm:ss.SSSSSS")).show(false)
+------------------------+--------------------------+
|times |times2 |
+------------------------+--------------------------+
|Nov 05, 2018 02:46:47 AM|2018-11-05 02:46:47.000000|
|Nov 5, 2018 02:46:47 PM |2018-11-05 14:46:47.000000|
+------------------------+--------------------------+
Please use hh for hour instead of HH if you want to parse 12 hour format. Also am/pm is indicated by suffix "a" while parsing.
Hope this helps!!
Upvotes: 10
Reputation: 2045
Using SQL syntax:
select date_format(to_timestamp(ColumnTimestamp, "MM/dd/yyyy hh:mm:ss aa"), "yyyy-MM-dd") as ColumnDate
from database_name.table_name
Upvotes: 0
Reputation: 8721
Using to_timestamp and date_format functions
scala> df.withColumn("times2",to_timestamp('times,"MMM d, yyyy hh:mm:ss a")).show(false)
+------------------------+-------------------+
|times |times2 |
+------------------------+-------------------+
|Nov 05, 2018 02:46:47 AM|2018-11-05 02:46:47|
|Nov 5, 2018 02:46:47 PM |2018-11-05 14:46:47|
+------------------------+-------------------+
scala> df.withColumn("times2",date_format(to_timestamp('times,"MMM d, yyyy hh:mm:ss a"),"yyyy-MM-dd HH:mm:ss.SSSSSS")).show(false)
+------------------------+--------------------------+
|times |times2 |
+------------------------+--------------------------+
|Nov 05, 2018 02:46:47 AM|2018-11-05 02:46:47.000000|
|Nov 5, 2018 02:46:47 PM |2018-11-05 14:46:47.000000|
+------------------------+--------------------------+
scala>
Upvotes: 3