chong created SPARK-38520:
-----------------------------

             Summary: Overflow occurs when reading ANSI day time interval from 
CSV file
                 Key: SPARK-38520
                 URL: https://issues.apache.org/jira/browse/SPARK-38520
             Project: Spark
          Issue Type: Bug
          Components: Spark Core
    Affects Versions: 3.3.0
            Reporter: chong


*Problem:*

Overflow occurs when reading the following positive intervals, the results 
become to negative

interval '106751992' day     => INTERVAL '-106751990' DAY

INTERVAL +'+2562047789' hour => INTERVAL '-2562047787' HOUR

interval '153722867281' minute => INTERVAL '-153722867280' MINUTE

 

*Produce:*
```
// days overflow
 scala> val schema = StructType(Seq(StructField("c1",
   DayTimeIntervalType(DayTimeIntervalType.DAY, DayTimeIntervalType.DAY))))
 scala> spark.read.csv(path).show(false)
 +------------------------+
 |_c0                     |
 +------------------------+
 |interval '106751992' day|
 +------------------------+
 scala> spark.read.schema(schema).csv(path).show(false)
 +-------------------------+
 |c1                       |
 +-------------------------+
 |INTERVAL '-106751990' DAY|
 +-------------------------+
  // hour overflow
 scala> val schema = StructType(Seq(StructField("c1",
   DayTimeIntervalType(DayTimeIntervalType.HOUR, DayTimeIntervalType.HOUR))))
 scala> spark.read.csv(path).show(false)
 +----------------------------+
 |_c0                         |
 +----------------------------+
 |INTERVAL +'+2562047789' hour|
 +----------------------------+
 scala> spark.read.schema(schema).csv(path).show(false)
 +---------------------------+
 |c1                         |
 +---------------------------+
 |INTERVAL '-2562047787' HOUR|
 +---------------------------+
 // minute overflow
 scala> val schema = StructType(Seq(StructField("c1",
   DayTimeIntervalType(DayTimeIntervalType.MINUTE, 
DayTimeIntervalType.MINUTE))))
 scala> spark.read.csv(path).show(false)
 +------------------------------+
 |_c0                           |
 +------------------------------+
 |interval '153722867281' minute|
 +------------------------------+
 scala> spark.read.schema(schema).csv(path).show(false)
 +-------------------------------+
 |c1                             |
 +-------------------------------+
 |INTERVAL '-153722867280' MINUTE|
 +-------------------------------+
```
 

*others:*

Also check the negative value is read to positive.

 

others:

should check the negative also, 



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