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https://issues.apache.org/jira/browse/SPARK-52382?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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ASF GitHub Bot updated SPARK-52382:
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Labels: pull-request-available (was: )
> MapType column with ArrayType key leads to TypeError in df.collect
> ------------------------------------------------------------------
>
> Key: SPARK-52382
> URL: https://issues.apache.org/jira/browse/SPARK-52382
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 3.5.3
> Reporter: Eyck Troschke
> Priority: Major
> Labels: pull-request-available
>
> According to the PySpark documentation, it should be possible to have a
> {{MapType column with ArrayType keys. MapType supports keys of type DataType
> and ArrayType}} inherits from {{{}DataType{}}}.
>
> When i try that with PySpark 3.5.3, the {{show() method of the DataFrame
> works as aspected, but the collect()}} method throws "{{{}TypeError:
> unhashable type: 'list'{}}}":
>
> {code:java}
> from pyspark.sql import SparkSession
> from pyspark.sql.types import MapType, ArrayType, StringType
>
> schema = MapType(ArrayType(StringType()), StringType())
> data = [\{("A", "B"): "foo", ("X", "Y", "Z"): "bar"}]
> df = spark.createDataFrame(data, schema)
> df.show() # works
> df.collect() # throws exception{code}
>
> So either the documentation or the behavior seems to be incorrect.
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