I filed a ticket: https://issues.apache.org/jira/browse/INFRA-17403
Please add your support there.
On Tue, Dec 11, 2018 at 4:58 PM, Sean Owen < sro...@apache.org > wrote:
>
> I asked on the original ticket at https:/ / issues. apache. org/ jira/ browse/
> INFRA-17385 (
I asked on the original ticket at
https://issues.apache.org/jira/browse/INFRA-17385 but no follow-up. Go
ahead and open a new INFRA ticket.
On Tue, Dec 11, 2018 at 6:20 PM Reynold Xin wrote:
> Thanks, Sean. Which INFRA ticket is it? It's creating a lot of noise so I
> want to put some pressure
Me too. I want to put some input as well if that can be helpful.
On Wed, 12 Dec 2018, 8:20 am Reynold Xin Thanks, Sean. Which INFRA ticket is it? It's creating a lot of noise so I
> want to put some pressure myself there too.
>
>
> On Mon, Dec 10, 2018 at 9:51 AM, Sean Owen wrote:
>
>> Agree,
Thanks, Sean. Which INFRA ticket is it? It's creating a lot of noise so I want
to put some pressure myself there too.
On Mon, Dec 10, 2018 at 9:51 AM, Sean Owen < sro...@apache.org > wrote:
>
>
>
> Agree, I'll ask on the INFRA ticket and follow up. That's a lot of extra
> noise.
>
>
>
>
Now, it's recovered.
Dongjoon.
On Tue, Dec 11, 2018 at 2:15 PM Dongjoon Hyun
wrote:
> https://issues.apache.org/jira/browse/INFRA-17401 is filed.
>
> Dongjoon.
>
> On Tue, Dec 11, 2018 at 12:49 PM Dongjoon Hyun
> wrote:
>
>> Hi, All.
>>
>> Currently, GitHub `spark:branch-2.4` is out of sync
https://issues.apache.org/jira/browse/INFRA-17401 is filed.
Dongjoon.
On Tue, Dec 11, 2018 at 12:49 PM Dongjoon Hyun
wrote:
> Hi, All.
>
> Currently, GitHub `spark:branch-2.4` is out of sync (with two commits).
>
>
>
Hi, All.
Currently, GitHub `spark:branch-2.4` is out of sync (with two commits).
https://gitbox.apache.org/repos/asf?p=spark.git;a=shortlog;h=refs/heads/branch-2.4
https://github.com/apache/spark/commits/branch-2.4
I did the followings already.
1. Wait for the next commit.
2. Trigger
Of course. I added some comments in the doc.
On Tue, Dec 11, 2018 at 12:01 PM Imran Rashid wrote:
> Hi Li,
>
> thanks for the comments! I admit I had not thought very much about python
> support, its a good point. But I'd actually like to clarify one thing
> about the doc -- though it
Hi Spark guys,
I'm Etienne Chauchot and I'm a committer on the Apache Beam project.
We have what we call runners. They are pieces of software that translate
pipelines written using Beam API into pipelines
that use native execution engine API. Currently, the Spark runner uses old RDD
/ DStream
I don’t know your exact underlying business problem, but maybe a graph
solution, such as Spark Graphx meets better your requirements. Usually
self-joins are done to address some kind of graph problem (even if you would
not describe it as such) and is for these kind of problems much more
Hi Li,
thanks for the comments! I admit I had not thought very much about python
support, its a good point. But I'd actually like to clarify one thing
about the doc -- though it discusses java types, the point is actually
about having support for these logical types at the SQL level. The doc
Marco,
Thanks for starting the discussion! I think it would be great to have a
clear description of the problem and a proposed solution. Do you have
anything like that? It would help bring the rest of us up to speed without
reading different pull requests.
Thanks!
rb
On Tue, Dec 11, 2018 at
In v2, it is up to the data source to tell Spark that a pushed filter is
satisfied, by returning the pushed filters that Spark should run. You can
indicate that a filter is handled by the source by not returning it for
Spark. You can also show that a filter is used by the source by showing it
in
Hi all,
I'd like to bring to the attention of a more people a problem which has
been there for long, ie, self joins. Currently, we have many troubles with
them. This has been reported several times to the community and seems to
affect many people, but as of now no solution has been accepted for
Hi,
Thank you for responding to this thread. I'm really interested in this
discussion.
My original idea might be the same as what Alessandro said, introducing a
mechanism that Spark can communicate with DataSource and get metadata which
shows if pushdown is supported or not.
I'm wondering if it
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