[jira] [Assigned] (SPARK-26913) New data source V2 API: SupportsDirectWrite

["Apache Spark (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-26913?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Apache Spark reassigned SPARK-26913:
------------------------------------

    Assignee:     (was: Apache Spark)

> New data source V2 API: SupportsDirectWrite
> -------------------------------------------
>
>                 Key: SPARK-26913
>                 URL: https://issues.apache.org/jira/browse/SPARK-26913
>             Project: Spark
>          Issue Type: Task
>          Components: SQL
>    Affects Versions: 3.0.0
>            Reporter: Gengliang Wang
>            Priority: Major
>
> Spark supports writing to file data sources without getting and validation with the table schema.
> For example, 
> ```
> spark.range(10).write.orc(path)
> val newDF = spark.range(20).map(id => (id.toDouble, id.toString)).toDF("double", "string")
> newDF.write.mode("overwrite").orc(path)
> ```
> 1. There is no need to get/infer the schema from the table/path
> 2.  The schema of `newDF` can be different with the original table schema.
> However, from https://github.com/apache/spark/pull/23606/files#r255319992 we can see that the feature above is missing in data source V2. Currently, data source V2 always validates the output query with the table schema. Even after the catalog support of DS V2 is implemented,  I think it is hard to support both behaviors with the current API/framework. 
> This PR proposes to create a new mix-in interface `SupportsDirectWrite`.  With the interface, Spark will write to the table location directly without schema inference and validation on `DataFrameWriter.save`.



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