Note you can use HiveQL syntax for creating dynamically partitioned tables
though.
On Sun, Mar 22, 2015 at 1:29 PM, Michael Armbrust <mich...@databricks.com>
wrote:
> Not yet. This is on the roadmap for Spark 1.4.
>
> On Sun, Mar 22, 2015 at 12:19 AM, deenar.toraskar <deenar.toras...@db.com>
> wrote:
>
>> Hi
>>
>> I wanted to store DataFrames as partitioned Hive tables. Is there a way to
>> do this via the saveAsTable call. The set of options does not seem to be
>> documented.
>>
>> def
>> saveAsTable(tableName: String, source: String, mode: SaveMode, options:
>> Map[String, String]): Unit
>> (Scala-specific) Creates a table from the the contents of this DataFrame
>> based on a given data source, SaveMode specified by mode, and a set of
>> options.
>>
>> Optionally is there a way to just create external hive tables for data
>> that
>> is already present on HDFS. something similar to
>>
>> sc.sql("alter table results add partition (date = '20141111');")
>>
>> Regards
>> Deenar
>>
>>
>>
>> --
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>
