You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Takuya Ueshin (Jira)" <ji...@apache.org> on 2023/03/22 21:57:00 UTC
[jira] [Updated] (SPARK-42899) DataFrame.to(schema) fails with the schema of itself.
[ https://issues.apache.org/jira/browse/SPARK-42899?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Takuya Ueshin updated SPARK-42899:
----------------------------------
Description:
{{DataFrame.to(schema)}} fails when it contains non-nullable nested field in nullable field:
{code:scala}
scala> val df = spark.sql("VALUES (1, STRUCT(1 as i)), (NULL, NULL) as t(a, b)")
df: org.apache.spark.sql.DataFrame = [a: int, b: struct<i: int>]
scala> df.printSchema()
root
|-- a: integer (nullable = true)
|-- b: struct (nullable = true)
| |-- i: integer (nullable = false)
scala> df.to(df.schema)
org.apache.spark.sql.AnalysisException: [NULLABLE_COLUMN_OR_FIELD] Column or field `b`.`i` is nullable while it's required to be non-nullable.
{code}
was:
{{DataFrame.to(schema)}} fails with the schema of itself, when it contains non-nullable nested field in nullable field:
{code:scala}
scala> val df = spark.sql("VALUES (1, STRUCT(1 as i)), (NULL, NULL) as t(a, b)")
df: org.apache.spark.sql.DataFrame = [a: int, b: struct<i: int>]
scala> df.printSchema()
root
|-- a: integer (nullable = true)
|-- b: struct (nullable = true)
| |-- i: integer (nullable = false)
scala> df.to(df.schema)
org.apache.spark.sql.AnalysisException: [NULLABLE_COLUMN_OR_FIELD] Column or field `b`.`i` is nullable while it's required to be non-nullable.
{code}
> DataFrame.to(schema) fails with the schema of itself.
> -----------------------------------------------------
>
> Key: SPARK-42899
> URL: https://issues.apache.org/jira/browse/SPARK-42899
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.4.0
> Reporter: Takuya Ueshin
> Priority: Major
>
> {{DataFrame.to(schema)}} fails when it contains non-nullable nested field in nullable field:
> {code:scala}
> scala> val df = spark.sql("VALUES (1, STRUCT(1 as i)), (NULL, NULL) as t(a, b)")
> df: org.apache.spark.sql.DataFrame = [a: int, b: struct<i: int>]
> scala> df.printSchema()
> root
> |-- a: integer (nullable = true)
> |-- b: struct (nullable = true)
> | |-- i: integer (nullable = false)
> scala> df.to(df.schema)
> org.apache.spark.sql.AnalysisException: [NULLABLE_COLUMN_OR_FIELD] Column or field `b`.`i` is nullable while it's required to be non-nullable.
> {code}
--
This message was sent by Atlassian Jira
(v8.20.10#820010)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org