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https://issues.apache.org/jira/browse/SPARK-61031?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon resolved SPARK-61031.
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    Resolution: Fixed

Issue resolved by pull request 236
[https://github.com/apache/spark-connect-rust/pull/236]

> Take the arguments of the readers, the writer and the catalog, and create the 
> tables of createTable on the call, in the Python client as PySpark does
> -----------------------------------------------------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-61031
>                 URL: https://issues.apache.org/jira/browse/SPARK-61031
>             Project: Spark
>          Issue Type: Bug
>          Components: Connect
>    Affects Versions: connect-rust-4.3.0
>            Reporter: Hyukjin Kwon
>            Assignee: Hyukjin Kwon
>            Priority: Major
>              Labels: pull-request-available
>             Fix For: connect-rust-4.3.0
>
>
> In PySpark, {{spark.read.load(path)}} and the readers of formats, such as 
> {{csv}}, {{json}}, {{parquet}}, {{text}}, {{orc}} and {{xml}}, take a path or 
> a list of paths, and {{parquet(*paths)}} takes any number of them. {{csv}}, 
> {{json}} and {{xml}} also take a DataFrame of one string column, which they 
> parse with the schema and the options of the reader ({{Parse}}). {{json}} and 
> {{xml}} raise {{NOT_EXPECTED_TYPE}} for any other {{path}}.
> {{df.write.bucketBy(numBuckets, col, *cols)}} and {{sortBy(col, *cols)}} take 
> the columns as names or as a list or tuple of them. They raise 
> {{NOT_EXPECTED_TYPE}} for a {{numBuckets}} that is not an int and for columns 
> that are not strings, and {{CANNOT_SET_TOGETHER}} for a list together with 
> more columns. {{clusterBy}} takes a list or tuple of columns too, and 
> {{df.write.mode(None)}} keeps the default mode.
> {{spark.catalog.createTable}} creates the table on the call, with the schema 
> and the options given. It raises {{NOT_EXPECTED_TYPE}} for a schema that is 
> not a StructType. {{createExternalTable}} warns that it is deprecated and 
> creates the table as {{createTable}} does. {{tableExists}}, 
> {{functionExists}} and {{listColumns}} warn that {{dbName}} is deprecated.
> The Rust-backed Python client raises a TypeError for a list of paths, as 
> {{spark.read.csv([path])}}, and for a DataFrame of strings. It raises a 
> ValueError for {{parquet}} of more than one path. It raises TypeErrors for 
> the list of columns of {{bucketBy}}, {{sortBy}} and {{clusterBy}}, and for 
> {{mode(None)}}, and TypeErrors rather than PySpark's errors for the other 
> arguments of {{bucketBy}}. {{createTable}} and {{createExternalTable}} ignore 
> the schema and the options, and create the table only when the DataFrame they 
> return runs. {{createExternalTable}} and {{dbName}} do not warn. Take the 
> arguments, and create the tables, as PySpark does.



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