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Posted to dev@spark.apache.org by "wangzhenhua (G)" <wa...@huawei.com> on 2017/09/08 02:20:07 UTC
答复: [VOTE] [SPIP] SPARK-15689: Data Source API V2 read path
+1 (non-binding) Great to see data source API is going to be improved!
best regards,
-Zhenhua(Xander)
发件人: Dongjoon Hyun [mailto:dongjoon.hyun@gmail.com]
发送时间: 2017年9月8日 4:07
收件人: 蒋星博
抄送: Michael Armbrust; Reynold Xin; Andrew Ash; Herman van Hövell tot Westerflier; Ryan Blue; Spark dev list; Suresh Thalamati; Wenchen Fan
主题: Re: [VOTE] [SPIP] SPARK-15689: Data Source API V2 read path
+1 (non-binding).
On Thu, Sep 7, 2017 at 12:46 PM, 蒋星博 <ji...@gmail.com>> wrote:
+1
Reynold Xin <rx...@databricks.com>>于2017年9月7日 周四下午12:04写道：
+1 as well
On Thu, Sep 7, 2017 at 9:12 PM, Michael Armbrust <mi...@databricks.com>> wrote:
+1
On Thu, Sep 7, 2017 at 9:32 AM, Ryan Blue <rb...@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 <hv...@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 <an...@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 <su...@gmail.com>> wrote:
+1 (non-binding)
On Sep 6, 2017, at 7:29 PM, Wenchen Fan <cl...@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<ma...@databricks.com>
+31 6 420 590 27
databricks.com<http://databricks.com/>
[http://databricks.com]<http://databricks.com/>
[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
Re: [VOTE] [SPIP] SPARK-15689: Data Source API V2 read path
Posted by Wenchen Fan <cl...@gmail.com>.
This vote passes with 4 binding +1 votes, 10 non-binding votes, one +0
vote, and no -1 votes.
Thanks all!
+1 votes (binding):
Wenchen Fan
Herman van Hövell tot Westerflier
Michael Armbrust
Reynold Xin
+1 votes (non-binding):
Xiao Li
Sameer Agarwal
Suresh Thalamati
Ryan Blue
Xingbo Jiang
Dongjoon Hyun
Zhenhua Wang
Noman Khan
vaquar khan
Hemant Bhanawat
+0 votes:
Andrew Ash
On Mon, Sep 11, 2017 at 4:03 PM, Wenchen Fan <cl...@gmail.com> wrote:
> yea, join push down (providing the other reader and join conditions) and
> aggregate push down (providing grouping keys and aggregate functions) can
> be added via the current framework in the future.
>
> On Mon, Sep 11, 2017 at 1:54 PM, Hemant Bhanawat <he...@gmail.com>
> wrote:
>
>> +1 (non-binding)
>>
>> I have found the suggestion from Andrew Ash and James about plan push
>> down quite interesting. However, I am not clear about the join push-down
>> support at the data source level. Shouldn't it be the responsibility of the
>> join node to carry out a data source specific join? I mean join node and
>> the data source scan of the two sides can be coalesced into a single node
>> (theoretically). This can be done by providing a Strategy that replaces the
>> join node with a data source specific join node. We are doing it that way
>> for our data sources. I find this more intuitive.
>>
>> BTW, aggregate push-down support is desirable and should be considered as
>> an enhancement going forward.
>>
>> Hemant Bhanawat <https://www.linkedin.com/in/hemant-bhanawat-92a3811>
>> www.snappydata.io
>>
>> On Sun, Sep 10, 2017 at 8:45 PM, vaquar khan <va...@gmail.com>
>> wrote:
>>
>>> +1
>>>
>>> Regards,
>>> Vaquar khan
>>>
>>> On Sep 10, 2017 5:18 AM, "Noman Khan" <no...@live.com> wrote:
>>>
>>>> +1
>>>> ------------------------------
>>>> *From:* wangzhenhua (G) <wa...@huawei.com>
>>>> *Sent:* Friday, September 8, 2017 2:20:07 AM
>>>> *To:* Dongjoon Hyun; 蒋星博
>>>> *Cc:* Michael Armbrust; Reynold Xin; Andrew Ash; Herman van Hövell tot
>>>> Westerflier; Ryan Blue; Spark dev list; Suresh Thalamati; Wenchen Fan
>>>> *Subject:* 答复: [VOTE] [SPIP] SPARK-15689: Data Source API V2 read path
>>>>
>>>>
>>>> +1 (non-binding) Great to see data source API is going to be improved!
>>>>
>>>>
>>>>
>>>> best regards,
>>>>
>>>> -Zhenhua(Xander)
>>>>
>>>>
>>>>
>>>> *发件人:* Dongjoon Hyun [mailto:dongjoon.hyun@gmail.com]
>>>> *发送时间:* 2017年9月8日 4:07
>>>> *收件人:* 蒋星博
>>>> *抄送:* Michael Armbrust; Reynold Xin; Andrew Ash; Herman van Hövell tot
>>>> Westerflier; Ryan Blue; Spark dev list; Suresh Thalamati; Wenchen Fan
>>>> *主题:* Re: [VOTE] [SPIP] SPARK-15689: Data Source API V2 read path
>>>>
>>>>
>>>>
>>>> +1 (non-binding).
>>>>
>>>>
>>>>
>>>> On Thu, Sep 7, 2017 at 12:46 PM, 蒋星博 <ji...@gmail.com> wrote:
>>>>
>>>> +1
>>>>
>>>>
>>>>
>>>>
>>>>
>>>> Reynold Xin <rx...@databricks.com>于2017年9月7日 周四下午12:04写道：
>>>>
>>>> +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 <rb...@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 <an...@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 <cl...@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
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>
>>
>
Re: [VOTE] [SPIP] SPARK-15689: Data Source API V2 read path
Posted by Wenchen Fan <cl...@gmail.com>.
yea, join push down (providing the other reader and join conditions) and
aggregate push down (providing grouping keys and aggregate functions) can
be added via the current framework in the future.
On Mon, Sep 11, 2017 at 1:54 PM, Hemant Bhanawat <he...@gmail.com>
wrote:
> +1 (non-binding)
>
> I have found the suggestion from Andrew Ash and James about plan push down
> quite interesting. However, I am not clear about the join push-down support
> at the data source level. Shouldn't it be the responsibility of the join
> node to carry out a data source specific join? I mean join node and the
> data source scan of the two sides can be coalesced into a single node
> (theoretically). This can be done by providing a Strategy that replaces the
> join node with a data source specific join node. We are doing it that way
> for our data sources. I find this more intuitive.
>
> BTW, aggregate push-down support is desirable and should be considered as
> an enhancement going forward.
>
> Hemant Bhanawat <https://www.linkedin.com/in/hemant-bhanawat-92a3811>
> www.snappydata.io
>
> On Sun, Sep 10, 2017 at 8:45 PM, vaquar khan <va...@gmail.com>
> wrote:
>
>> +1
>>
>> Regards,
>> Vaquar khan
>>
>> On Sep 10, 2017 5:18 AM, "Noman Khan" <no...@live.com> wrote:
>>
>>> +1
>>> ------------------------------
>>> *From:* wangzhenhua (G) <wa...@huawei.com>
>>> *Sent:* Friday, September 8, 2017 2:20:07 AM
>>> *To:* Dongjoon Hyun; 蒋星博
>>> *Cc:* Michael Armbrust; Reynold Xin; Andrew Ash; Herman van Hövell tot
>>> Westerflier; Ryan Blue; Spark dev list; Suresh Thalamati; Wenchen Fan
>>> *Subject:* 答复: [VOTE] [SPIP] SPARK-15689: Data Source API V2 read path
>>>
>>>
>>> +1 (non-binding) Great to see data source API is going to be improved!
>>>
>>>
>>>
>>> best regards,
>>>
>>> -Zhenhua(Xander)
>>>
>>>
>>>
>>> *发件人:* Dongjoon Hyun [mailto:dongjoon.hyun@gmail.com]
>>> *发送时间:* 2017年9月8日 4:07
>>> *收件人:* 蒋星博
>>> *抄送:* Michael Armbrust; Reynold Xin; Andrew Ash; Herman van Hövell tot
>>> Westerflier; Ryan Blue; Spark dev list; Suresh Thalamati; Wenchen Fan
>>> *主题:* Re: [VOTE] [SPIP] SPARK-15689: Data Source API V2 read path
>>>
>>>
>>>
>>> +1 (non-binding).
>>>
>>>
>>>
>>> On Thu, Sep 7, 2017 at 12:46 PM, 蒋星博 <ji...@gmail.com> wrote:
>>>
>>> +1
>>>
>>>
>>>
>>>
>>>
>>> Reynold Xin <rx...@databricks.com>于2017年9月7日 周四下午12:04写道：
>>>
>>> +1 as well
>>>
>>>
>>>
>>> On Thu, Sep 7, 2017 at 9:12 PM, Michael Armbrust <mi...@databricks.com>
>>> wrote:
>>>
>>> +1
>>>
>>>
>>>
>>> On Thu, Sep 7, 2017 at 9:32 AM, Ryan Blue <rb...@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 <an...@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 <cl...@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
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>
>
Re: [VOTE] [SPIP] SPARK-15689: Data Source API V2 read path
Posted by Hemant Bhanawat <he...@gmail.com>.
+1 (non-binding)
I have found the suggestion from Andrew Ash and James about plan push down
quite interesting. However, I am not clear about the join push-down support
at the data source level. Shouldn't it be the responsibility of the join
node to carry out a data source specific join? I mean join node and the
data source scan of the two sides can be coalesced into a single node
(theoretically). This can be done by providing a Strategy that replaces the
join node with a data source specific join node. We are doing it that way
for our data sources. I find this more intuitive.
BTW, aggregate push-down support is desirable and should be considered as
an enhancement going forward.
Hemant Bhanawat <https://www.linkedin.com/in/hemant-bhanawat-92a3811>
www.snappydata.io
On Sun, Sep 10, 2017 at 8:45 PM, vaquar khan <va...@gmail.com> wrote:
> +1
>
> Regards,
> Vaquar khan
>
> On Sep 10, 2017 5:18 AM, "Noman Khan" <no...@live.com> wrote:
>
>> +1
>> ------------------------------
>> *From:* wangzhenhua (G) <wa...@huawei.com>
>> *Sent:* Friday, September 8, 2017 2:20:07 AM
>> *To:* Dongjoon Hyun; 蒋星博
>> *Cc:* Michael Armbrust; Reynold Xin; Andrew Ash; Herman van Hövell tot
>> Westerflier; Ryan Blue; Spark dev list; Suresh Thalamati; Wenchen Fan
>> *Subject:* 答复: [VOTE] [SPIP] SPARK-15689: Data Source API V2 read path
>>
>>
>> +1 (non-binding) Great to see data source API is going to be improved!
>>
>>
>>
>> best regards,
>>
>> -Zhenhua(Xander)
>>
>>
>>
>> *发件人:* Dongjoon Hyun [mailto:dongjoon.hyun@gmail.com]
>> *发送时间:* 2017年9月8日 4:07
>> *收件人:* 蒋星博
>> *抄送:* Michael Armbrust; Reynold Xin; Andrew Ash; Herman van Hövell tot
>> Westerflier; Ryan Blue; Spark dev list; Suresh Thalamati; Wenchen Fan
>> *主题:* Re: [VOTE] [SPIP] SPARK-15689: Data Source API V2 read path
>>
>>
>>
>> +1 (non-binding).
>>
>>
>>
>> On Thu, Sep 7, 2017 at 12:46 PM, 蒋星博 <ji...@gmail.com> wrote:
>>
>> +1
>>
>>
>>
>>
>>
>> Reynold Xin <rx...@databricks.com>于2017年9月7日 周四下午12:04写道：
>>
>> +1 as well
>>
>>
>>
>> On Thu, Sep 7, 2017 at 9:12 PM, Michael Armbrust <mi...@databricks.com>
>> wrote:
>>
>> +1
>>
>>
>>
>> On Thu, Sep 7, 2017 at 9:32 AM, Ryan Blue <rb...@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 <an...@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 <cl...@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
>>
>>
>>
>>
>>
>>
>>
>
Re: [VOTE] [SPIP] SPARK-15689: Data Source API V2 read path
Posted by vaquar khan <va...@gmail.com>.
+1
Regards,
Vaquar khan
On Sep 10, 2017 5:18 AM, "Noman Khan" <no...@live.com> wrote:
> +1
> ------------------------------
> *From:* wangzhenhua (G) <wa...@huawei.com>
> *Sent:* Friday, September 8, 2017 2:20:07 AM
> *To:* Dongjoon Hyun; 蒋星博
> *Cc:* Michael Armbrust; Reynold Xin; Andrew Ash; Herman van Hövell tot
> Westerflier; Ryan Blue; Spark dev list; Suresh Thalamati; Wenchen Fan
> *Subject:* 答复: [VOTE] [SPIP] SPARK-15689: Data Source API V2 read path
>
>
> +1 (non-binding) Great to see data source API is going to be improved!
>
>
>
> best regards,
>
> -Zhenhua(Xander)
>
>
>
> *发件人:* Dongjoon Hyun [mailto:dongjoon.hyun@gmail.com]
> *发送时间:* 2017年9月8日 4:07
> *收件人:* 蒋星博
> *抄送:* Michael Armbrust; Reynold Xin; Andrew Ash; Herman van Hövell tot
> Westerflier; Ryan Blue; Spark dev list; Suresh Thalamati; Wenchen Fan
> *主题:* Re: [VOTE] [SPIP] SPARK-15689: Data Source API V2 read path
>
>
>
> +1 (non-binding).
>
>
>
> On Thu, Sep 7, 2017 at 12:46 PM, 蒋星博 <ji...@gmail.com> wrote:
>
> +1
>
>
>
>
>
> Reynold Xin <rx...@databricks.com>于2017年9月7日 周四下午12:04写道：
>
> +1 as well
>
>
>
> On Thu, Sep 7, 2017 at 9:12 PM, Michael Armbrust <mi...@databricks.com>
> wrote:
>
> +1
>
>
>
> On Thu, Sep 7, 2017 at 9:32 AM, Ryan Blue <rb...@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 <an...@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 <cl...@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
>
>
>
>
>
>
>
Re: [VOTE] [SPIP] SPARK-15689: Data Source API V2 read path
Posted by Noman Khan <no...@live.com>.
+1
________________________________
From: wangzhenhua (G) <wa...@huawei.com>
Sent: Friday, September 8, 2017 2:20:07 AM
To: Dongjoon Hyun; 蒋星博
Cc: Michael Armbrust; Reynold Xin; Andrew Ash; Herman van Hövell tot Westerflier; Ryan Blue; Spark dev list; Suresh Thalamati; Wenchen Fan
Subject: 答复: [VOTE] [SPIP] SPARK-15689: Data Source API V2 read path
+1 (non-binding) Great to see data source API is going to be improved!
best regards,
-Zhenhua(Xander)
发件人: Dongjoon Hyun [mailto:dongjoon.hyun@gmail.com]
发送时间: 2017年9月8日 4:07
收件人: 蒋星博
抄送: Michael Armbrust; Reynold Xin; Andrew Ash; Herman van Hövell tot Westerflier; Ryan Blue; Spark dev list; Suresh Thalamati; Wenchen Fan
主题: Re: [VOTE] [SPIP] SPARK-15689: Data Source API V2 read path
+1 (non-binding).
On Thu, Sep 7, 2017 at 12:46 PM, 蒋星博 <ji...@gmail.com>> wrote:
+1
Reynold Xin <rx...@databricks.com>>于2017年9月7日 周四下午12:04写道：
+1 as well
On Thu, Sep 7, 2017 at 9:12 PM, Michael Armbrust <mi...@databricks.com>> wrote:
+1
On Thu, Sep 7, 2017 at 9:32 AM, Ryan Blue <rb...@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 <hv...@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 <an...@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 <su...@gmail.com>> wrote:
+1 (non-binding)
On Sep 6, 2017, at 7:29 PM, Wenchen Fan <cl...@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<ma...@databricks.com>
+31 6 420 590 27
databricks.com<http://databricks.com/>
[http://databricks.com]<http://databricks.com/>
[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