[jira] [Created] (SPARK-40289) The result is strange when casting string to date in ORC reading via Schema Evolution

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

Jianbang Xian created SPARK-40289:
-------------------------------------

             Summary: The result is strange when casting string to date in ORC reading via Schema Evolution
                 Key: SPARK-40289
                 URL: https://issues.apache.org/jira/browse/SPARK-40289
             Project: Spark
          Issue Type: Bug
          Components: Spark Shell
    Affects Versions: 3.1.1
         Environment: * Ubuntu 1804 LTS
 * Spark 311
            Reporter: Jianbang Xian


I created an ORC file by the code as follows.


{code:java}
val data = Seq(
    ("", "2022-01-32"),  // pay attention to this, null
    ("", "9808-02-30"),  // pay attention to this, 9808-02-29
    ("", "2022-06-31"),  // pay attention to this, 2022-06-30
)
val cols = Seq("str", "date_str")
val df=spark.createDataFrame(data).toDF(cols:_*).repartition(1)
df.printSchema()
df.show(100)
df.write.mode("overwrite").orc("/tmp/orc/data.orc")
{code}

Please note that these three cases are invalid date.
And I read it via:
{code:java}
scala> var df = spark.read.schema("date_str date").orc("/tmp/orc/data.orc"); df.show()
+----------+
|  date_str|
+----------+
|      null|
|9808-02-29|
|2022-06-30|
+----------+{code}
Why is `2022-01-31` converted to `null`, while `9808-02-30` is converted to `9808-02-29`?

Intuitively, they are invalid date, we should return 3 nulls. Is it a bug or a feature?

 

 

*Background*

 
 * I am working on the project: [https://github.com/NVIDIA/spark-rapids]
 * And I am working on a feature, that is to support reading ORC file as an cuDF (CUDA DataFrame). cuDF is an in-memory data-format of GPU.
 * I need to follow the behaviors of ORC reading in CPU. Otherwise, the users of spark-rapids will feel strange with the results.
 * Therefore I want to know why those happpened.



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