[GitHub] [spark] wangyum edited a comment on pull request #32090: [SPARK-34212][SQL][FOLLOWUP] Support reading data when DecimalMetadata is null

[GitBox <gi...@apache.org>]

wangyum edited a comment on pull request #32090:
URL: https://github.com/apache/spark/pull/32090#issuecomment-817106123


   I think we should not support this case. It has potential data issues. For example:
   ```scala
       import org.apache.spark.sql.types.StructType
   
       spark.sql("SELECT 999999999 AS a").write.mode("overwrite").parquet("/tmp/SPARK-34212")
       val df = spark.read.schema(StructType.fromDDL("a decimal(2, 0)")).parquet("/tmp/SPARK-34212")
       df.write.saveAsTable("t1")
   
       spark.sql("select a, a * a as a2, a * a * a as a3, a * a * a * a as a4 from t1").write.saveAsTable("t2")
       spark.sql("select * from t2").show(false)
       spark.sql("desc t2").show(false)
   ```
   
   ```
   +---------+----+----+----+
   |a        |a2  |a3  |a4  |
   +---------+----+----+----+
   |999999999|null|null|null|
   +---------+----+----+----+
   
   +--------+-------------+-------+
   |col_name|data_type    |comment|
   +--------+-------------+-------+
   |a       |decimal(2,0) |null   |
   |a2      |decimal(5,0) |null   |
   |a3      |decimal(8,0) |null   |
   |a4      |decimal(11,0)|null   |
   +--------+-------------+-------+
   ```


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