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https://issues.apache.org/jira/browse/SPARK-50051?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Ruifeng Zheng resolved SPARK-50051.
-----------------------------------
Fix Version/s: 4.0.0
Resolution: Fixed
Issue resolved by pull request 48589
[https://github.com/apache/spark/pull/48589]
> Spark Connect should support str ndarray
> ----------------------------------------
>
> Key: SPARK-50051
> URL: https://issues.apache.org/jira/browse/SPARK-50051
> Project: Spark
> Issue Type: Improvement
> Components: Connect, PySpark
> Affects Versions: 4.0.0
> Reporter: Ruifeng Zheng
> Assignee: Ruifeng Zheng
> Priority: Major
> Labels: pull-request-available
> Fix For: 4.0.0
>
>
> In [5]: spark.range(1).select(sf.lit(np.array(["a", "b"], np.str_))).schema
> ---------------------------------------------------------------------------
> PySparkTypeError Traceback (most recent call last)
> Cell In[5], line 1
> ----> 1 spark.range(1).select(sf.lit(np.array(["a", "b"], np.str_))).schema
> File ~/Dev/spark/python/pyspark/sql/utils.py:272, in
> try_remote_functions.<locals>.wrapped(*args, **kwargs)
> 269 if is_remote() and "PYSPARK_NO_NAMESPACE_SHARE" not in os.environ:
> 270 from pyspark.sql.connect import functions
> --> 272 return getattr(functions, f.__name__)(*args, **kwargs)
> 273 else:
> 274 return f(*args, **kwargs)
> File ~/Dev/spark/python/pyspark/sql/connect/functions/builtin.py:271, in
> lit(col)
> 269 elif isinstance(col, np.ndarray) and col.ndim == 1:
> 270 if _from_numpy_type(col.dtype) is None:
> --> 271 raise PySparkTypeError(
> 272 errorClass="UNSUPPORTED_NUMPY_ARRAY_SCALAR",
> 273 messageParameters=\{"dtype": col.dtype.name},
> 274 )
> 276 # NumpyArrayConverter for Py4J can not support ndarray with int8
> values.
> 277 # Actually this is not a problem for Connect, but here still
> convert it
> 278 # to int16 for compatibility.
> 279 if col.dtype == np.int8:
> PySparkTypeError: [UNSUPPORTED_NUMPY_ARRAY_SCALAR] The type of array scalar
> 'str32' is not supported.
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