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https://issues.apache.org/jira/browse/SPARK-42458?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon resolved SPARK-42458.
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Fix Version/s: 3.4.0
Resolution: Fixed
Issue resolved by pull request 40240
[https://github.com/apache/spark/pull/40240]
> createDataFrame should support DDL string as schema
> ---------------------------------------------------
>
> Key: SPARK-42458
> URL: https://issues.apache.org/jira/browse/SPARK-42458
> Project: Spark
> Issue Type: Sub-task
> Components: Connect
> Affects Versions: 3.4.0
> Reporter: Takuya Ueshin
> Assignee: Takuya Ueshin
> Priority: Major
> Fix For: 3.4.0
>
>
> {code:python}
> File "/.../python/pyspark/sql/connect/readwriter.py", line 393, in
> pyspark.sql.connect.readwriter.DataFrameWriter.option
> Failed example:
> with tempfile.TemporaryDirectory() as d:
> # Write a DataFrame into a CSV file with 'nullValue' option set to
> 'Hyukjin Kwon'.
> df = spark.createDataFrame([(100, None)], "age INT, name STRING")
> df.write.option("nullValue", "Hyukjin
> Kwon").mode("overwrite").format("csv").save(d)
> # Read the CSV file as a DataFrame.
> spark.read.schema(df.schema).format('csv').load(d).show()
> Exception raised:
> Traceback (most recent call last):
> File "/.../lib/python3.9/doctest.py", line 1334, in __run
> exec(compile(example.source, filename, "single",
> File "<doctest
> pyspark.sql.connect.readwriter.DataFrameWriter.option[2]>", line 3, in
> <module>
> df = spark.createDataFrame([(100, None)], "age INT, name STRING")
> File "/.../python/pyspark/sql/connect/session.py", line 312, in
> createDataFrame
> raise ValueError(
> ValueError: Some of types cannot be determined after inferring, a
> StructType Schema is required in this case
> {code}
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