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Posted to issues@spark.apache.org by "Haejoon Lee (Jira)" <ji...@apache.org> on 2023/03/15 03:18:00 UTC
[jira] [Resolved] (SPARK-42666) Fix `createDataFrame` to work properly with rows and schema
[ https://issues.apache.org/jira/browse/SPARK-42666?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Haejoon Lee resolved SPARK-42666.
---------------------------------
Fix Version/s: 3.4.0
Resolution: Duplicate
Resolved from SPARK-42679
> Fix `createDataFrame` to work properly with rows and schema
> -----------------------------------------------------------
>
> Key: SPARK-42666
> URL: https://issues.apache.org/jira/browse/SPARK-42666
> Project: Spark
> Issue Type: Sub-task
> Components: Connect
> Affects Versions: 3.5.0
> Reporter: Haejoon Lee
> Priority: Major
> Fix For: 3.4.0
>
>
> The code below is not working properly in Spark Connect:
> {code:java}
> >>> sdf = spark.range(10)
> >>> spark.createDataFrame(sdf.tail(5), sdf.schema)
> Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> File "/.../spark/python/pyspark/sql/connect/dataframe.py", line 94, in __repr__
> return "DataFrame[%s]" % (", ".join("%s: %s" % c for c in self.dtypes))
> File "/.../spark/python/pyspark/sql/connect/dataframe.py", line 162, in dtypes
> return [(str(f.name), f.dataType.simpleString()) for f in self.schema.fields]
> File "/.../spark/python/pyspark/sql/connect/dataframe.py", line 1346, in schema
> self._schema = self._session.client.schema(query)
> File "/.../spark/python/pyspark/sql/connect/client.py", line 614, in schema
> proto_schema = self._analyze(method="schema", plan=plan).schema
> File "/.../spark/python/pyspark/sql/connect/client.py", line 755, in _analyze
> self._handle_error(rpc_error)
> File "/.../spark/python/pyspark/sql/connect/client.py", line 894, in _handle_error
> raise convert_exception(info, status.message) from None
> pyspark.errors.exceptions.connect.AnalysisException: [NULLABLE_COLUMN_OR_FIELD] Column or field `id` is nullable while it's required to be non-nullable.{code}
> whereas working properly in regular PySpark:
> {code:java}
> >>> sdf = spark.range(10)
> >>> spark.createDataFrame(sdf.tail(5), sdf.schema).show()
> +---+
> | id|
> +---+
> | 5|
> | 6|
> | 7|
> | 8|
> | 9|
> +---+ {code}
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