[ https://issues.apache.org/jira/browse/SPARK-26915?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-26915: ------------------------------------ Assignee: (was: Apache Spark) > File source should write without schema inference and validation in > DataFrameWriter.save() > ------------------------------------------------------------------------------------------ > > Key: SPARK-26915 > URL: https://issues.apache.org/jira/browse/SPARK-26915 > 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 process file sources as a special case in > `DataFrameWriter.save()`. So that we can keep the original behavior for this > DataFrame API. -- This message was sent by Atlassian JIRA (v7.6.3#76005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org