[jira] [Created] (SPARK-38577) Interval types are not truncated to the expected endField when creating a DataFrame via Duration

["chong (Jira)" <ji...@apache.org>]

chong created SPARK-38577:
-----------------------------

             Summary: Interval types are not truncated to the expected endField when creating a DataFrame via Duration
                 Key: SPARK-38577
                 URL: https://issues.apache.org/jira/browse/SPARK-38577
             Project: Spark
          Issue Type: Bug
          Components: SQL
    Affects Versions: 3.3.0
         Environment: Spark 3.3.0 snapshot version

 
            Reporter: chong


*Problem:*

ANSI interval types are store as long internally.

The long value are not truncated to the expected endField when creating a DataFrame via Duration.

 

*Reproduce:*

Create a "day to day" interval, the seconds are not truncated, see below code.

The internal long is not {*}86400 * 1000000{*}, but it's ({*}86400 + 1)  * 1000000{*}{*}{*}

 
{code:java}
  test("my test") {
    val data = Seq(Row(Duration.ofDays(1).plusSeconds(1)))
    val schema = StructType(Array(
      StructField("t", DayTimeIntervalType(DayTimeIntervalType.DAY, DayTimeIntervalType.DAY))
    ))
    val df = spark.createDataFrame(spark.sparkContext.parallelize(data), schema)
    df.show()
  } {code}
 

 

After debug, the {{endField}} is always {{SECOND}} in {{{}durationToMicros{}}}, see below:

 
{code:java}
  // IntervalUtils class

  def durationToMicros(duration: Duration): Long = {
    durationToMicros(duration, DT.SECOND)   // always SECOND
  }

  def durationToMicros(duration: Duration, endField: Byte)

{code}
Seems should use different endField which could be [DAY, HOUR, MINUTE, SECOND]

 

 
 



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