Is this a candidate for the version 1.X/2.0 split?
2015-12-09 16:29 GMT-08:00 Michael Armbrust :
> Yeah, I would like to address any actual gaps in functionality that are
> present.
>
> On Wed, Dec 9, 2015 at 4:24 PM, Cristian Opris > wrote:
>
>> The reason I'm asking is because it's important i
Yeah, I would like to address any actual gaps in functionality that are
present.
On Wed, Dec 9, 2015 at 4:24 PM, Cristian Opris
wrote:
> The reason I'm asking is because it's important in larger projects to be
> able to stick to a particular programming style. Some people are more
> comfortable
That sounds great! When it is decided, please let us know and we can add
more features and make it ANSI SQL compliant.
Thank you!
Xiao Li
2015-12-09 11:31 GMT-08:00 Michael Armbrust :
> I don't plan to abandon HiveQL compatibility, but I'd like to see us move
> towards something with more SQL
I don't plan to abandon HiveQL compatibility, but I'd like to see us move
towards something with more SQL compliance (perhaps just newer versions of
the HiveQL parser). Exactly which parser will do that for us is under
investigation.
On Wed, Dec 9, 2015 at 11:02 AM, Xiao Li wrote:
> Hi, Michael
Hi, Michael,
Does that mean SqlContext will be built on HiveQL in the near future?
Thanks,
Xiao Li
2015-12-09 10:36 GMT-08:00 Michael Armbrust :
> I think that it is generally good to have parity when the functionality is
> useful. However, in some cases various features are there just to ma
I think that it is generally good to have parity when the functionality is
useful. However, in some cases various features are there just to maintain
compatibility with other system. For example CACHE TABLE is eager because
Shark's cache table was. df.cache() is lazy because Spark's cache is.
Do
Hi,
I was wondering what the "official" view is on feature parity between SQL
and DF apis. Docs are pretty sparse on the SQL front, and it seems that
some features are only supported at various times in only one of Spark SQL
dialect, HiveQL dialect and DF API. DF.cube(), DISTRIBUTE BY, CACHE LAZY
