Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/14279
I think it is okay. Just to make sure,
- **This writes date and timestamps fine**:
```scala
val path = "/tmp"
val date = java.sql.Date.valueOf("1970-01-01")
val timestamp = java.sql.Timestamp.valueOf("1970-01-01 11:46:40.0")
val data = Seq((date, timestamp)).toDF("date", "timestamp")
// Write CSV data
data.write.format("csv").save(s"$path/csv")
spark.read.format("text").load(s"$path/csv").collect().foreach(println(_))
// Write JSON data
data.write.format("json").save(s"$path/json")
spark.read.format("text").load(s"$path/json").collect().foreach(println(_))
```
prints below:
```
[1970-01-01,1970-01-01T11:46:40.000-08:00]
[{"date":"1970-01-01","timestamp":"1970-01-01T11:46:40.000-08:00"}]
```
- **Able to be read back fine.**
```scala
val path = "/tmp"
val date = java.sql.Date.valueOf("1970-01-01")
val timestamp = java.sql.Timestamp.valueOf("1970-01-01 11:46:40.0")
val data = Seq((date, timestamp)).toDF("date", "timestamp")
// Roundtrip in reading and writing CSV data
data.write.format("csv").save(s"$path/csv")
val roundtripCsvDF =
spark.read.schema(data.schema).format("csv").load(s"$path/csv")
roundtripCsvDF.collect().foreach(println(_))
roundtripCsvDF.printSchema()
// Roundtrip in reading and writing JSON data
data.write.format("json").save(s"$path/json")
val roundtripJsonDF =
spark.read.schema(data.schema).format("json").load(s"$path/json")
roundtripJsonDF.collect().foreach(println(_))
roundtripJsonDF.printSchema()
```
prints below:
```
[1970-01-01,1970-01-01 11:46:40.0]
root
|-- date: date (nullable = true)
|-- timestamp: timestamp (nullable = true)
[1970-01-01,1970-01-01 11:46:40.0]
root
|-- date: date (nullable = true)
|-- timestamp: timestamp (nullable = true)
```
- **`FastDateFormat` is thread-safe and compatible with
`SimpleDateFormat`** (See
https://github.com/apache/commons-lang/blob/LANG_3_2/src/main/java/org/apache/commons/lang3/time/FastDateFormat.java#L30-L37).
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