[
https://issues.apache.org/jira/browse/FLINK-37625?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
ASF GitHub Bot updated FLINK-37625:
-----------------------------------
Labels: pull-request-available (was: )
> PyFlink Table API skips validation for Rows created with positional arguments
> -----------------------------------------------------------------------------
>
> Key: FLINK-37625
> URL: https://issues.apache.org/jira/browse/FLINK-37625
> Project: Flink
> Issue Type: Bug
> Components: API / Python
> Reporter: Mika Naylor
> Assignee: Mika Naylor
> Priority: Minor
> Labels: pull-request-available
>
> When creating a table using {{{}TableEnvironment.from_elements{}}}, the Table
> API skips type validation on any Row elements that were created using
> positional arguments, rather than keyword arguments.
>
> For example, take a table with a single column, whose type is an array of
> {{{}Row{}}}s. These rows have 2 columns, {{a VARCHAR}} and {{{}b BOOLEAN{}}}.
> If we create a table with elements where one of these rows has columns in the
> wrong order:
> {code:java}
> schema = DataTypes.ROW(
> [
> DataTypes.FIELD(
> "col",
> DataTypes.ARRAY(
> DataTypes.ROW(
> [
> DataTypes.FIELD("a", DataTypes.STRING()),
> DataTypes.FIELD("b", DataTypes.BOOLEAN()),
> ]
> )
> ),
> ),
> ]
> )
> elements = [(
> [("pyflink", True), ("pyflink", False), (True, "pyflink")],
> )]
> table = self.t_env.from_elements(elements, schema)
> table_result = list(table.execute().collect()){code}
> This results in a type validation error:
> {code:java}
> TypeError: field a in element in array field col: VARCHAR can not accept
> object True in type <class 'bool'>{code}
> In an example where we use {{Row}} instead of tuples, but with column
> arguments:
> {code:java}
> elements = [(
> [Row(a="pyflink", b=True), Row(a="pyflink", b=False), Row(a=True,
> b="pyflink")],
> )]{code}
> We also get the same type validation error. However, when we use {{Row}} with
> positional arguments:
> {code:java}
> elements = [(
> [Row("pyflink", True), Row("pyflink", False), Row(True, "pyflink")],
> )]{code}
> the type validation is skipped, leading to an unpickling error when
> collecting:
> {code:java}
> > data = pickle.loads(data)
> E EOFError: Ran out of input {code}
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