Nikolaus Schuetz created FLINK-40322:
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Summary: PyFlink ArrayType/MultisetType.from_sql_type calls
to_sql_type instead
Key: FLINK-40322
URL: https://issues.apache.org/jira/browse/FLINK-40322
Project: Flink
Issue Type: Bug
Components: API / Python
Reporter: Nikolaus Schuetz
{{}}
h2. Summary
{{PyFlink's
[ArrayType|https://github.com/apache/flink/blob/release-2.3.0/flink-python/pyflink/table/types.py#L926]}}
and
[{{MultisetType}}|https://github.com/apache/flink/blob/release-2.3.0/flink-python/pyflink/table/types.py#L1054]
mistakenly call {{to_sql_type}} from their {{from_sql_type}} wrappers:
* *MultisetType:*
[https://github.com/apache/flink/blob/release-2.3.0/flink-python/pyflink/table/types.py#L1054]
* *ArrayType:*
[https://github.com/apache/flink/blob/release-2.3.0/flink-python/pyflink/table/types.py#L926]
This is a typo from the above wrapping of {{{}to_sql_type{}}}. To be clear,
{{from_sql_type}} is meant to decode the internal/SQL representation back to
Python. For an element type that needs conversion (e.g. {{{}DATE{}}}, whose
internal form is an int day-count), decoding an {{{}ARRAY{}}}/{{{}MULTISET{}}}
then feeds an {{int}} into {{{}DateType.to_sql_type{}}}, which does
{{v.toordinal()}} and as expected it raises:
{{AttributeError: 'int' object has no attribute 'toordinal'}}
The sibling {{MapType.from_sql_type}} (same file) is correct — it calls
{{from_sql_type}} on both key and value — so
{{{}ArrayType{}}}/{{{}MultisetType{}}} are simply inconsistent with it.
h3. Reproduction
{code:python}
from pyflink.table.types import DataTypes
at = DataTypes.ARRAY(DataTypes.DATE())
at.from_sql_type([0, 1])
# expected: [datetime.date(1970, 1, 1), datetime.date(1970, 1, 2)]
# actual: AttributeError: 'int' object has no attribute 'toordinal'
{code}
Same for {{{}DataTypes.MULTISET(DataTypes.DATE()){}}}.
h3. Fix
Call {{from_sql_type}} on each element, matching {{{}MapType.from_sql_type{}}}.
Regression tests added for {{ARRAY<DATE>}} and {{{}MULTISET<DATE>{}}}.
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