[
https://issues.apache.org/jira/browse/SPARK-41903?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Hyukjin Kwon resolved SPARK-41903.
----------------------------------
Fix Version/s: 3.4.0
Resolution: Fixed
Issue resolved by pull request 39570
[https://github.com/apache/spark/pull/39570]
> Support data type ndarray
> -------------------------
>
> Key: SPARK-41903
> URL: https://issues.apache.org/jira/browse/SPARK-41903
> Project: Spark
> Issue Type: Sub-task
> Components: Connect
> Affects Versions: 3.4.0
> Reporter: Sandeep Singh
> Assignee: Sandeep Singh
> Priority: Major
> Fix For: 3.4.0
>
>
> {code:java}
> import numpy as np
> arr_dtype_to_spark_dtypes = [
> ("int8", [("b", "array<smallint>")]),
> ("int16", [("b", "array<smallint>")]),
> ("int32", [("b", "array<int>")]),
> ("int64", [("b", "array<bigint>")]),
> ("float32", [("b", "array<float>")]),
> ("float64", [("b", "array<double>")]),
> ]
> for t, expected_spark_dtypes in arr_dtype_to_spark_dtypes:
> arr = np.array([1, 2]).astype(t)
> self.assertEqual(
> expected_spark_dtypes,
> self.spark.range(1).select(lit(arr).alias("b")).dtypes
> )
> arr = np.array([1, 2]).astype(np.uint)
> with self.assertRaisesRegex(
> TypeError, "The type of array scalar '%s' is not supported" % arr.dtype
> ):
> self.spark.range(1).select(lit(arr).alias("b")){code}
> {code:java}
> Traceback (most recent call last):
> File
> "/Users/s.singh/personal/spark-oss/python/pyspark/sql/tests/test_functions.py",
> line 1100, in test_ndarray_input
> expected_spark_dtypes,
> self.spark.range(1).select(lit(arr).alias("b")).dtypes
> File "/Users/s.singh/personal/spark-oss/python/pyspark/sql/utils.py", line
> 332, in wrapped
> return getattr(functions, f.__name__)(*args, **kwargs)
> File
> "/Users/s.singh/personal/spark-oss/python/pyspark/sql/connect/functions.py",
> line 198, in lit
> return Column(LiteralExpression._from_value(col))
> File
> "/Users/s.singh/personal/spark-oss/python/pyspark/sql/connect/expressions.py",
> line 266, in _from_value
> return LiteralExpression(value=value,
> dataType=LiteralExpression._infer_type(value))
> File
> "/Users/s.singh/personal/spark-oss/python/pyspark/sql/connect/expressions.py",
> line 262, in _infer_type
> raise ValueError(f"Unsupported Data Type {type(value).__name__}")
> ValueError: Unsupported Data Type ndarray {code}
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