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https://issues.apache.org/jira/browse/KUDU-1676?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16452518#comment-16452518
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Ivan Vergiliev edited comment on KUDU-1676 at 4/25/18 3:45 PM:
---------------------------------------------------------------
This is now possible using the following call:
{{ val kuduSchema = kuduContext.createSchema(schema)}}
where `schema` is a Spark `StructType` schema.
was (Author: ivan.vergiliev):
This is now possible using the following call:
```
val kuduSchema = kuduContext.createSchema(schema)
```
where `schema` is a Spark `StructType` schema.
> Spark DDL needs elegant way to specify range partitioning
> ---------------------------------------------------------
>
> Key: KUDU-1676
> URL: https://issues.apache.org/jira/browse/KUDU-1676
> Project: Kudu
> Issue Type: New Feature
> Components: spark
> Affects Versions: 1.0.0
> Reporter: Mladen Kovacevic
> Assignee: Mladen Kovacevic
> Priority: Major
> Original Estimate: 96h
> Remaining Estimate: 96h
>
> To define partition column splits, you need a PartialRow object.
> These are easy to create when you have the Schema object. But since your
> table schema in Spark is defined with StructType instead of Schema, then its
> cumbersome to define a new Schema object to be the exact duplicate of the
> StructType version, only to get the PartialRow, to set what the range
> partition will values would be, then set the addSplitRow() function call to
> your CreateTableOptions.
> We need an elegant way to have the Spark API handle specifying range
> partition attributes without having to drop into the Java API in Spark.
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