cloud-fan commented on a change in pull request #27956: 
[SPARK-31189][SQL][DOCS] Fix errors and missing parts for datetime pattern 
document
URL: https://github.com/apache/spark/pull/27956#discussion_r394848994
 
 

 ##########
 File path: docs/sql-ref-datetime-pattern.md
 ##########
 @@ -21,11 +21,26 @@ license: |
 
 There are several common scenarios for datetime usage in Spark:
 
-- CSV/JSON datasources use the pattern string for parsing and formatting time 
content.
+- CSV/JSON datasources use the pattern string for parsing and formatting 
datetime content.
 
-- Datetime functions related to convert string to/from `DateType` or 
`TimestampType`. For example, unix_timestamp, date_format, to_unix_timestamp, 
from_unixtime, to_date, to_timestamp, from_utc_timestamp, to_utc_timestamp, etc.
+- Datetime functions related to convert `StringType` to/from `DateType` or 
`TimestampType`.
+  For example, `unix_timestamp`, `date_format`, `to_unix_timestamp`, 
`from_unixtime`, `to_date`, `to_timestamp`, `from_utc_timestamp`, 
`to_utc_timestamp`, etc.
+
+Spark uses 
[java.time.format.DateTimeFormatter](https://docs.oracle.com/javase/8/docs/api/java/time/format/DateTimeFormatter.html)
 
 Review comment:
   I wouldn't mention these 2 java classes at all. Users don't care how we 
implement it, but what the behavior is.

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