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From Reynold Xin <r...@databricks.com>
Subject Re: [VOTE] [SPIP] SPARK-15689: Data Source API V2 read path
Date Thu, 07 Sep 2017 19:03:47 GMT
+1 as well

On Thu, Sep 7, 2017 at 9:12 PM, Michael Armbrust <michael@databricks.com>
wrote:

> +1
>
> On Thu, Sep 7, 2017 at 9:32 AM, Ryan Blue <rblue@netflix.com.invalid>
> wrote:
>
>> +1 (non-binding)
>>
>> Thanks for making the updates reflected in the current PR. It would be
>> great to see the doc updated before it is finally published though.
>>
>> Right now it feels like this SPIP is focused more on getting the basics
>> right for what many datasources are already doing in API V1 combined with
>> other private APIs, vs pushing forward state of the art for performance.
>>
>> I think that’s the right approach for this SPIP. We can add the support
>> you’re talking about later with a more specific plan that doesn’t block
>> fixing the problems that this addresses.
>> ​
>>
>> On Thu, Sep 7, 2017 at 2:00 AM, Herman van Hövell tot Westerflier <
>> hvanhovell@databricks.com> wrote:
>>
>>> +1 (binding)
>>>
>>> I personally believe that there is quite a big difference between having
>>> a generic data source interface with a low surface area and pushing down a
>>> significant part of query processing into a datasource. The later has much
>>> wider wider surface area and will require us to stabilize most of the
>>> internal catalyst API's which will be a significant burden on the community
>>> to maintain and has the potential to slow development velocity
>>> significantly. If you want to write such integrations then you should be
>>> prepared to work with catalyst internals and own up to the fact that things
>>> might change across minor versions (and in some cases even maintenance
>>> releases). If you are willing to go down that road, then your best bet is
>>> to use the already existing spark session extensions which will allow you
>>> to write such integrations and can be used as an `escape hatch`.
>>>
>>>
>>> On Thu, Sep 7, 2017 at 10:23 AM, Andrew Ash <andrew@andrewash.com>
>>> wrote:
>>>
>>>> +0 (non-binding)
>>>>
>>>> I think there are benefits to unifying all the Spark-internal
>>>> datasources into a common public API for sure.  It will serve as a forcing
>>>> function to ensure that those internal datasources aren't advantaged vs
>>>> datasources developed externally as plugins to Spark, and that all Spark
>>>> features are available to all datasources.
>>>>
>>>> But I also think this read-path proposal avoids the more difficult
>>>> questions around how to continue pushing datasource performance forwards.
>>>> James Baker (my colleague) had a number of questions about advanced
>>>> pushdowns (combined sorting and filtering), and Reynold also noted that
>>>> pushdown of aggregates and joins are desirable on longer timeframes as
>>>> well.  The Spark community saw similar requests, for aggregate pushdown in
>>>> SPARK-12686, join pushdown in SPARK-20259, and arbitrary plan pushdown
>>>> in SPARK-12449.  Clearly a number of people are interested in this kind of
>>>> performance work for datasources.
>>>>
>>>> To leave enough space for datasource developers to continue
>>>> experimenting with advanced interactions between Spark and their
>>>> datasources, I'd propose we leave some sort of escape valve that enables
>>>> these datasources to keep pushing the boundaries without forking Spark.
>>>> Possibly that looks like an additional unsupported/unstable interface that
>>>> pushes down an entire (unstable API) logical plan, which is expected to
>>>> break API on every release.   (Spark attempts this full-plan pushdown, and
>>>> if that fails Spark ignores it and continues on with the rest of the V2 API
>>>> for compatibility).  Or maybe it looks like something else that we don't
>>>> know of yet.  Possibly this falls outside of the desired goals for the V2
>>>> API and instead should be a separate SPIP.
>>>>
>>>> If we had a plan for this kind of escape valve for advanced datasource
>>>> developers I'd be an unequivocal +1.  Right now it feels like this SPIP is
>>>> focused more on getting the basics right for what many datasources are
>>>> already doing in API V1 combined with other private APIs, vs pushing
>>>> forward state of the art for performance.
>>>>
>>>> Andrew
>>>>
>>>> On Wed, Sep 6, 2017 at 10:56 PM, Suresh Thalamati <
>>>> suresh.thalamati@gmail.com> wrote:
>>>>
>>>>> +1 (non-binding)
>>>>>
>>>>>
>>>>> On Sep 6, 2017, at 7:29 PM, Wenchen Fan <cloud0fan@gmail.com> wrote:
>>>>>
>>>>> Hi all,
>>>>>
>>>>> In the previous discussion, we decided to split the read and write
>>>>> path of data source v2 into 2 SPIPs, and I'm sending this email to call
a
>>>>> vote for Data Source V2 read path only.
>>>>>
>>>>> The full document of the Data Source API V2 is:
>>>>> https://docs.google.com/document/d/1n_vUVbF4KD3gxTmkNEon5qdQ
>>>>> -Z8qU5Frf6WMQZ6jJVM/edit
>>>>>
>>>>> The ready-for-review PR that implements the basic infrastructure for
>>>>> the read path is:
>>>>> https://github.com/apache/spark/pull/19136
>>>>>
>>>>> The vote will be up for the next 72 hours. Please reply with your vote:
>>>>>
>>>>> +1: Yeah, let's go forward and implement the SPIP.
>>>>> +0: Don't really care.
>>>>> -1: I don't think this is a good idea because of the following
>>>>> technical reasons.
>>>>>
>>>>> Thanks!
>>>>>
>>>>>
>>>>>
>>>>
>>>
>>>
>>> --
>>>
>>> Herman van Hövell
>>>
>>> Software Engineer
>>>
>>> Databricks Inc.
>>>
>>> hvanhovell@databricks.com
>>>
>>> +31 6 420 590 27
>>>
>>> databricks.com
>>>
>>> [image: http://databricks.com] <http://databricks.com/>
>>>
>>>
>>>
>>> [image: Announcing Databricks Serverless. The first serverless data
>>> science and big data platform. Watch the demo from Spark Summit 2017.]
>>> <http://go.databricks.com/announcing-databricks-serverless>
>>>
>>
>>
>>
>> --
>> Ryan Blue
>> Software Engineer
>> Netflix
>>
>
>

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