[jira] [Commented] (SPARK-30098) Use default datasource as provider for CREATE TABLE command

2020-11-30 Thread Apache Spark (Jira)


[ 
https://issues.apache.org/jira/browse/SPARK-30098?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17240897#comment-17240897
 ] 

Apache Spark commented on SPARK-30098:
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User 'cloud-fan' has created a pull request for this issue:
https://github.com/apache/spark/pull/30554

> Use default datasource as provider for CREATE TABLE command
> ---
>
> Key: SPARK-30098
> URL: https://issues.apache.org/jira/browse/SPARK-30098
> Project: Spark
>  Issue Type: Improvement
>  Components: SQL
>Affects Versions: 3.0.0
>Reporter: wuyi
>Priority: Major
> Fix For: 3.0.0
>
>
> Changing the default provider from `hive` to the value of 
> `spark.sql.sources.default` for "CREATE TABLE" command to make it be 
> consistent with DataFrameWriter.saveAsTable API.
> Also, it brings more friendly to end users since Spark is well know of using 
> parquet(default value of `spark.sql.sources.default`) as its default I/O 
> format.



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[jira] [Commented] (SPARK-30098) Use default datasource as provider for CREATE TABLE command

2020-11-30 Thread Apache Spark (Jira)


[ 
https://issues.apache.org/jira/browse/SPARK-30098?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17240899#comment-17240899
 ] 

Apache Spark commented on SPARK-30098:
--

User 'cloud-fan' has created a pull request for this issue:
https://github.com/apache/spark/pull/30554

> Use default datasource as provider for CREATE TABLE command
> ---
>
> Key: SPARK-30098
> URL: https://issues.apache.org/jira/browse/SPARK-30098
> Project: Spark
>  Issue Type: Improvement
>  Components: SQL
>Affects Versions: 3.0.0
>Reporter: wuyi
>Assignee: Apache Spark
>Priority: Major
> Fix For: 3.0.0
>
>
> Changing the default provider from `hive` to the value of 
> `spark.sql.sources.default` for "CREATE TABLE" command to make it be 
> consistent with DataFrameWriter.saveAsTable API.
> Also, it brings more friendly to end users since Spark is well know of using 
> parquet(default value of `spark.sql.sources.default`) as its default I/O 
> format.



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