jinchengchenghh opened a new issue, #11135:
URL: https://github.com/apache/incubator-gluten/issues/11135
### Description
```
[ERROR]
TestGlutenDataFrameWriterV2>TestDataFrameWriterV2.testMergeSchemaIgnoreCastingDoubleToFloat:290->SparkTestHelperBase.assertEquals:67->SparkTestHelperBase.assertEquals:87
[Should include new rows with unchanged double column type: row 1 col 1
contents should match]
expected: 1.0
but was: 5.325712093E-315
```
If user ever set TableProperties.SPARK_WRITE_ACCEPT_ANY_SCHEMA and merge
schema to true to write the data, source column is double, but the Spark
dataframe type is float, iceberg will write the float in parquet file.
```
scala> val df =
spark.read.parquet("/Users/chengchengjin/code/test/table/data/00001-6-45ee1a66-11a1-49f4-ad79-5c66c8f67d6d-0-00001.parquet")
df: org.apache.spark.sql.DataFrame = [id: float, data: string]
scala> df.printSchema()
root
|-- id: float (nullable = true)
|-- data: string (nullable = true)
```
This PR https://github.com/apache/iceberg/pull/11419 supports the feature.
Now fallback for table property SPARK_WRITE_ACCEPT_ANY_SCHEMA to true
### Gluten version
None
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