[RESULT][VOTE] Release apache-calcite-1.4.0-incubating

[Jacques Nadeau]

This vote passes with 4 +1s, one +0 and no -1 votes:

+1 Alan (Mentor)
+1 Ashutosh (Mentor)
+1 Julian
+1 John
+0 Justin

Thanks everyone. We’ll now roll the release out to the mirrors.

Jacques


On Mon, Aug 31, 2015 at 4:51 PM, Ashutosh Chauhan 
wrote:

> Forwarding my +1 from Calcite list.
>
> Ashutosh
>
> On Mon, Aug 31, 2015 at 10:59 AM, Alan Gates  wrote:
>
>> Forwarding my +1 from the Calcite vote.
>>
>> Alan.
>>
>> Jacques Nadeau 
>> August 28, 2015 at 14:32
>> Hi all,
>>
>> The Calcite community has voted on and approved a proposal to release
>> Apache Calcite 1.4.0-incubating.
>>
>> Proposal:
>>
>> http://mail-archives.apache.org/mod_mbox/incubator-calcite-dev/201508.mbox/%3CCAKa9qD%3DWA1s03rUEuCUbUbWiBgmC_9N%3D1r39dXjLAKevRt6UCQ%40mail.gmail.com%3E
>>
>> Vote result:
>> 8 binding +1 votes
>> 1 non-binding +1 votes
>> No -1 votes
>>
>> http://mail-archives.apache.org/mod_mbox/incubator-calcite-dev/201508.mbox/%3CCAKa9qD%3DPUH70eyPY3u25O4ayimwOXfBBxiX2txUEcNbUCYODXg%40mail.gmail.com%3E
>>
>> The commit to be voted upon:
>>
>> http://git-wip-us.apache.org/repos/asf/incubator-calcite/commit/0c0c203daec56c05b6c75fa3896c8af19844df68
>>
>> Its hash is 0c0c203daec56c05b6c75fa3896c8af19844df68.
>>
>> The artifacts to be voted on are located here:
>>
>> https://dist.apache.org/repos/dist/dev/incubator/calcite/apache-calcite-1.4.0-incubating-rc0
>>
>> The hashes of the artifacts are as follows:
>> src.tar.gz.md5 e052e2b1ffdbdab9eaeb30f4ac838e75
>> src.tar.gz.sha1 fd979e8b330bb0d3b9be8625c95589e0eb358722
>> src.zip.md5 ef1880617f3b6415c5e3779d9c2bbc10
>> src.zip.sha1 b865a9a45046a339c53834e7abea7a7a55927f07
>>
>> A staged Maven repository is available for review at:
>> https://repository.apache.org/content/repositories/orgapachecalcite-1009
>>
>> Release artifacts are signed with the following key:
>> https://people.apache.org/keys/committer/jacques.asc
>>
>> Pursuant to the Releases section of the Incubation Policy and with
>> the endorsement of 2 of our mentors we would now like to request
>> the permission of the Incubator PMC to publish the release. The vote
>> is open for 72 hours, or until the necessary number of votes (3 +1)
>> is reached.
>>
>> [ ] +1 Release this package as Apache Calcite 1.4.0-incubating
>> [ ] -1 Do not release this package because...
>>
>> Jacques Nadeau, on behalf of Apache Calcite PPMC
>>
>>
>

Re: [VOTE] Accept HAWQ into the Apache Incubator

[Thejas Nair]

+1

On Mon, Aug 31, 2015 at 7:01 PM, Luke Han  wrote:
> +1 (non-binding)
>
>
> Best Regards!
> -
>
> Luke Han
>
> On Tue, Sep 1, 2015 at 9:41 AM, Chris Douglas  wrote:
>
>> +1 -C
>>
>> On Mon, Aug 31, 2015 at 11:47 AM, Roman Shaposhnik  wrote:
>> > Following the discussion earlier:
>> >http://s.apache.org/Gaf
>> >
>> > I would like to call a VOTE for accepting HAWQ
>> > as a new incubator project.
>> >
>> > The proposal is available at:
>> > https://wiki.apache.org/incubator/HAWQProposal
>> > and is also included at the bottom of this email.
>> >
>> > Vote is open until at least Thu, 3 September 2015, 23:59:00 PST
>> >
>> >  [ ] +1 accept HAWQ into the Apache Incubator
>> >  [ ] ±0
>> >  [ ] -1 because...
>> >
>> > Thanks,
>> > Roman.
>> >
>> > == Abstract ==
>> >
>> > HAWQ is an advanced enterprise SQL on Hadoop analytic engine built
>> > around a robust and high-performance massively-parallel processing
>> > (MPP) SQL framework evolved from Pivotal Greenplum DatabaseⓇ.
>> >
>> > HAWQ runs natively on Apache HadoopⓇ clusters by tightly integrating
>> > with HDFS and YARN. HAWQ supports multiple Hadoop file formats such as
>> > Apache Parquet, native HDFS, and Apache Avro. HAWQ is configured and
>> > managed as a Hadoop service in Apache Ambari. HAWQ is 100% ANSI SQL
>> > compliant (supporting ANSI SQL-92, SQL-99, and SQL-2003, plus OLAP
>> > extensions) and supports open database connectivity (ODBC) and Java
>> > database connectivity (JDBC), as well. Most business intelligence,
>> > data analysis and data visualization tools work with HAWQ out of the
>> > box without the need for specialized drivers.
>> >
>> > A unique aspect of HAWQ is its integration of statistical and machine
>> > learning capabilities that can be natively invoked from SQL or (in the
>> > context of PL/Python, PL/Java or PL/R) in massively parallel modes and
>> > applied to large data sets across a Hadoop cluster. These capabilities
>> > are provided through MADlib – an existing open source, parallel
>> > machine-learning library. Given the close ties between the two
>> > development communities, the MADlib community has expressed interest
>> > in joining HAWQ on its journey into the ASF Incubator and will be
>> > submitting a separate, concurrent proposal.
>> >
>> > HAWQ will provide more robust and higher performing options for Hadoop
>> > environments that demand best-in-class data analytics for business
>> > critical purposes. HAWQ is implemented in C and C++.
>> >
>> > HAWQ has a few runtime dependencies licensed under the Cat X list:
>> >   * gperf (GPL Version 3)
>> >   * libgsasl (LGPL Version 2.1)
>> >   * libuuid-2.26 (LGPL Version 2)
>> > However, given the runtime (dynamic linking) nature of these
>> > dependencies it doesn't represent a problem for HAWQ to be considered
>> > an ASF project.
>> >
>> > == Proposal ==
>> > The goal of this proposal is to bring the core of Pivotal Software,
>> > Inc.’s (Pivotal) Pivotal HAWQⓇ codebase into the Apache Software
>> > Foundation (ASF) in order to build a vibrant, diverse and
>> > self-governed open source community around the technology. Pivotal has
>> > agreed to transfer the brand name "HAWQ" to Apache Software Foundation
>> > and will stop using HAWQ to refer to this software if the project gets
>> > accepted into the ASF Incubator under the name of "Apache HAWQ
>> > (incubating)". Pivotal will continue to market and sell an analytic
>> > engine product that includes Apache HAWQ (incubating). While HAWQ is
>> > our primary choice for a name of the project, in anticipation of any
>> > potential issues with PODLINGNAMESEARCH we have come up with two
>> > alternative names: (1) Hornet; or (2) Grove.
>> >
>> > Pivotal is submitting this proposal to donate the HAWQ source code and
>> > associated artifacts (documentation, web site content, wiki, etc.) to
>> > the Apache Software Foundation Incubator under the Apache License,
>> > Version 2.0 and is asking Incubator PMC to establish an open source
>> > community.
>> >
>> > == Background ==
>> > While the ecosystem of open source SQL-on-Hadoop solutions is fairly
>> > developed by now, HAWQ has several unique features that will set it
>> > apart from existing ASF and non-ASF projects. HAWQ made its debut in
>> > 2013 as a closed source product leveraging a decade's worth of product
>> > development effort invested in Greenplum DatabaseⓇ. Since then HAWQ
>> > has rapidly gained a solid customer base and became available on
>> > non-Pivotal distributions of Hadoop.
>> > In 2015 HAWQ still leverages the rock solid foundation of Greenplum
>> > Database, while at the same time embracing elasticity and resource
>> > management native to Hadoop applications. This allows HAWQ to provide
>> > superior SQL on Hadoop performance, scalability and coverage while
>> > also providing massively-parallel machine learning capabilities and
>> > support for native 

Re: Droids Podling Issue

[Richard Frovarp]

On 08/09/2015 08:16 PM, Marvin Humphrey wrote:

On Sun, Aug 9, 2015 at 5:54 PM, Roman Shaposhnik  wrote:

FWIW: Droids has always been right there after NPanday for me
to be concerned about. This is not the isolated instance you're
seeing.

The Incubator is basically holding Droids open out of deference to
Thorsten and Richard, both of whom are Apache Members and IPMC
members.

Droids has not been active for a long time, and would require
considerable work building a community before it could graduate as a
TLP.  Some small podlings have graduated in the past (no fewer than 5
PMC members) and it has worked out OK.  Having two people as
experienced as Richard and Thorsten on Board in a group of 5 would
make it a decent bet, were the podling active. But almost nothing has
been going on with Droids for years.

The matter will probably resolve once Richard tires of making
quarterly reports and challenging calls to retire the podling whenever
a report is late.

Marvin Humphrey



Thanks Marvin. I'm probably at that point. I'd be happy to work on it, 
and help out the community. However, I don't have the energy to push and 
build a community, which is what is needed. I was waiting to see if 
Thorsten had something to say. I know he was out of the office when the 
last report was due.


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Re: [VOTE] Release apache-calcite-1.4.0-incubating

[Alan Gates]

Forwarding my +1 from the Calcite vote.

Alan.


Jacques Nadeau 
August 28, 2015 at 14:32
Hi all,

The Calcite community has voted on and approved a proposal to release
Apache Calcite 1.4.0-incubating.

Proposal:
http://mail-archives.apache.org/mod_mbox/incubator-calcite-dev/201508.mbox/%3CCAKa9qD%3DWA1s03rUEuCUbUbWiBgmC_9N%3D1r39dXjLAKevRt6UCQ%40mail.gmail.com%3E

Vote result:
8 binding +1 votes
1 non-binding +1 votes
No -1 votes
http://mail-archives.apache.org/mod_mbox/incubator-calcite-dev/201508.mbox/%3CCAKa9qD%3DPUH70eyPY3u25O4ayimwOXfBBxiX2txUEcNbUCYODXg%40mail.gmail.com%3E

The commit to be voted upon:
http://git-wip-us.apache.org/repos/asf/incubator-calcite/commit/0c0c203daec56c05b6c75fa3896c8af19844df68

Its hash is 0c0c203daec56c05b6c75fa3896c8af19844df68.

The artifacts to be voted on are located here:
https://dist.apache.org/repos/dist/dev/incubator/calcite/apache-calcite-1.4.0-incubating-rc0

The hashes of the artifacts are as follows:
src.tar.gz.md5 e052e2b1ffdbdab9eaeb30f4ac838e75
src.tar.gz.sha1 fd979e8b330bb0d3b9be8625c95589e0eb358722
src.zip.md5 ef1880617f3b6415c5e3779d9c2bbc10
src.zip.sha1 b865a9a45046a339c53834e7abea7a7a55927f07

A staged Maven repository is available for review at:
https://repository.apache.org/content/repositories/orgapachecalcite-1009

Release artifacts are signed with the following key:
https://people.apache.org/keys/committer/jacques.asc

Pursuant to the Releases section of the Incubation Policy and with
the endorsement of 2 of our mentors we would now like to request
the permission of the Incubator PMC to publish the release. The vote
is open for 72 hours, or until the necessary number of votes (3 +1)
is reached.

[ ] +1 Release this package as Apache Calcite 1.4.0-incubating
[ ] -1 Do not release this package because...

Jacques Nadeau, on behalf of Apache Calcite PPMC

[VOTE] Accept HAWQ into the Apache Incubator

[Roman Shaposhnik]

Following the discussion earlier:
   http://s.apache.org/Gaf

I would like to call a VOTE for accepting HAWQ
as a new incubator project.

The proposal is available at:
https://wiki.apache.org/incubator/HAWQProposal
and is also included at the bottom of this email.

Vote is open until at least Thu, 3 September 2015, 23:59:00 PST

 [ ] +1 accept HAWQ into the Apache Incubator
 [ ] ±0
 [ ] -1 because...

Thanks,
Roman.

== Abstract ==

HAWQ is an advanced enterprise SQL on Hadoop analytic engine built
around a robust and high-performance massively-parallel processing
(MPP) SQL framework evolved from Pivotal Greenplum DatabaseⓇ.

HAWQ runs natively on Apache HadoopⓇ clusters by tightly integrating
with HDFS and YARN. HAWQ supports multiple Hadoop file formats such as
Apache Parquet, native HDFS, and Apache Avro. HAWQ is configured and
managed as a Hadoop service in Apache Ambari. HAWQ is 100% ANSI SQL
compliant (supporting ANSI SQL-92, SQL-99, and SQL-2003, plus OLAP
extensions) and supports open database connectivity (ODBC) and Java
database connectivity (JDBC), as well. Most business intelligence,
data analysis and data visualization tools work with HAWQ out of the
box without the need for specialized drivers.

A unique aspect of HAWQ is its integration of statistical and machine
learning capabilities that can be natively invoked from SQL or (in the
context of PL/Python, PL/Java or PL/R) in massively parallel modes and
applied to large data sets across a Hadoop cluster. These capabilities
are provided through MADlib – an existing open source, parallel
machine-learning library. Given the close ties between the two
development communities, the MADlib community has expressed interest
in joining HAWQ on its journey into the ASF Incubator and will be
submitting a separate, concurrent proposal.

HAWQ will provide more robust and higher performing options for Hadoop
environments that demand best-in-class data analytics for business
critical purposes. HAWQ is implemented in C and C++.

HAWQ has a few runtime dependencies licensed under the Cat X list:
  * gperf (GPL Version 3)
  * libgsasl (LGPL Version 2.1)
  * libuuid-2.26 (LGPL Version 2)
However, given the runtime (dynamic linking) nature of these
dependencies it doesn't represent a problem for HAWQ to be considered
an ASF project.

== Proposal ==
The goal of this proposal is to bring the core of Pivotal Software,
Inc.’s (Pivotal) Pivotal HAWQⓇ codebase into the Apache Software
Foundation (ASF) in order to build a vibrant, diverse and
self-governed open source community around the technology. Pivotal has
agreed to transfer the brand name "HAWQ" to Apache Software Foundation
and will stop using HAWQ to refer to this software if the project gets
accepted into the ASF Incubator under the name of "Apache HAWQ
(incubating)". Pivotal will continue to market and sell an analytic
engine product that includes Apache HAWQ (incubating). While HAWQ is
our primary choice for a name of the project, in anticipation of any
potential issues with PODLINGNAMESEARCH we have come up with two
alternative names: (1) Hornet; or (2) Grove.

Pivotal is submitting this proposal to donate the HAWQ source code and
associated artifacts (documentation, web site content, wiki, etc.) to
the Apache Software Foundation Incubator under the Apache License,
Version 2.0 and is asking Incubator PMC to establish an open source
community.

== Background ==
While the ecosystem of open source SQL-on-Hadoop solutions is fairly
developed by now, HAWQ has several unique features that will set it
apart from existing ASF and non-ASF projects. HAWQ made its debut in
2013 as a closed source product leveraging a decade's worth of product
development effort invested in Greenplum DatabaseⓇ. Since then HAWQ
has rapidly gained a solid customer base and became available on
non-Pivotal distributions of Hadoop.
In 2015 HAWQ still leverages the rock solid foundation of Greenplum
Database, while at the same time embracing elasticity and resource
management native to Hadoop applications. This allows HAWQ to provide
superior SQL on Hadoop performance, scalability and coverage while
also providing massively-parallel machine learning capabilities and
support for native Hadoop file formats. In addition, HAWQ's advanced
features include support for complex joins, rich and compliant SQL
dialect and industry-differentiating data federation capabilities.
Dynamic pipelining and pluggable query optimizer architecture enable
HAWQ to perform queries on Hadoop with the speed and scalability
required for enterprise data warehouse (EDW) workloads. HAWQ provides
strong support for low-latency analytic SQL queries, coupled with
massively parallel machine learning capabilities. This enables
discovery-based analysis of large data sets and rapid, iterative
development of data analytics applications that apply deep machine
learning – significantly shortening data-driven innovation cycles for
the enterprise.

Hundreds of companies and 

Re: [VOTE] Accept HAWQ into the Apache Incubator

[Atri Sharma]

+1

On Tue, Sep 1, 2015 at 12:17 AM, Roman Shaposhnik  wrote:

> Following the discussion earlier:
>http://s.apache.org/Gaf
>
> I would like to call a VOTE for accepting HAWQ
> as a new incubator project.
>
> The proposal is available at:
> https://wiki.apache.org/incubator/HAWQProposal
> and is also included at the bottom of this email.
>
> Vote is open until at least Thu, 3 September 2015, 23:59:00 PST
>
>  [ ] +1 accept HAWQ into the Apache Incubator
>  [ ] ±0
>  [ ] -1 because...
>
> Thanks,
> Roman.
>
> == Abstract ==
>
> HAWQ is an advanced enterprise SQL on Hadoop analytic engine built
> around a robust and high-performance massively-parallel processing
> (MPP) SQL framework evolved from Pivotal Greenplum DatabaseⓇ.
>
> HAWQ runs natively on Apache HadoopⓇ clusters by tightly integrating
> with HDFS and YARN. HAWQ supports multiple Hadoop file formats such as
> Apache Parquet, native HDFS, and Apache Avro. HAWQ is configured and
> managed as a Hadoop service in Apache Ambari. HAWQ is 100% ANSI SQL
> compliant (supporting ANSI SQL-92, SQL-99, and SQL-2003, plus OLAP
> extensions) and supports open database connectivity (ODBC) and Java
> database connectivity (JDBC), as well. Most business intelligence,
> data analysis and data visualization tools work with HAWQ out of the
> box without the need for specialized drivers.
>
> A unique aspect of HAWQ is its integration of statistical and machine
> learning capabilities that can be natively invoked from SQL or (in the
> context of PL/Python, PL/Java or PL/R) in massively parallel modes and
> applied to large data sets across a Hadoop cluster. These capabilities
> are provided through MADlib – an existing open source, parallel
> machine-learning library. Given the close ties between the two
> development communities, the MADlib community has expressed interest
> in joining HAWQ on its journey into the ASF Incubator and will be
> submitting a separate, concurrent proposal.
>
> HAWQ will provide more robust and higher performing options for Hadoop
> environments that demand best-in-class data analytics for business
> critical purposes. HAWQ is implemented in C and C++.
>
> HAWQ has a few runtime dependencies licensed under the Cat X list:
>   * gperf (GPL Version 3)
>   * libgsasl (LGPL Version 2.1)
>   * libuuid-2.26 (LGPL Version 2)
> However, given the runtime (dynamic linking) nature of these
> dependencies it doesn't represent a problem for HAWQ to be considered
> an ASF project.
>
> == Proposal ==
> The goal of this proposal is to bring the core of Pivotal Software,
> Inc.’s (Pivotal) Pivotal HAWQⓇ codebase into the Apache Software
> Foundation (ASF) in order to build a vibrant, diverse and
> self-governed open source community around the technology. Pivotal has
> agreed to transfer the brand name "HAWQ" to Apache Software Foundation
> and will stop using HAWQ to refer to this software if the project gets
> accepted into the ASF Incubator under the name of "Apache HAWQ
> (incubating)". Pivotal will continue to market and sell an analytic
> engine product that includes Apache HAWQ (incubating). While HAWQ is
> our primary choice for a name of the project, in anticipation of any
> potential issues with PODLINGNAMESEARCH we have come up with two
> alternative names: (1) Hornet; or (2) Grove.
>
> Pivotal is submitting this proposal to donate the HAWQ source code and
> associated artifacts (documentation, web site content, wiki, etc.) to
> the Apache Software Foundation Incubator under the Apache License,
> Version 2.0 and is asking Incubator PMC to establish an open source
> community.
>
> == Background ==
> While the ecosystem of open source SQL-on-Hadoop solutions is fairly
> developed by now, HAWQ has several unique features that will set it
> apart from existing ASF and non-ASF projects. HAWQ made its debut in
> 2013 as a closed source product leveraging a decade's worth of product
> development effort invested in Greenplum DatabaseⓇ. Since then HAWQ
> has rapidly gained a solid customer base and became available on
> non-Pivotal distributions of Hadoop.
> In 2015 HAWQ still leverages the rock solid foundation of Greenplum
> Database, while at the same time embracing elasticity and resource
> management native to Hadoop applications. This allows HAWQ to provide
> superior SQL on Hadoop performance, scalability and coverage while
> also providing massively-parallel machine learning capabilities and
> support for native Hadoop file formats. In addition, HAWQ's advanced
> features include support for complex joins, rich and compliant SQL
> dialect and industry-differentiating data federation capabilities.
> Dynamic pipelining and pluggable query optimizer architecture enable
> HAWQ to perform queries on Hadoop with the speed and scalability
> required for enterprise data warehouse (EDW) workloads. HAWQ provides
> strong support for low-latency analytic SQL queries, coupled with
> massively parallel machine learning capabilities. 

Re: [VOTE] Accept HAWQ into the Apache Incubator

[Mattmann, Chris A (3980)]

+1 binding cheers

Sent from my iPhone

> On Aug 31, 2015, at 11:54 AM, Roman Shaposhnik  wrote:
> 
> Following the discussion earlier:
>   http://s.apache.org/Gaf
> 
> I would like to call a VOTE for accepting HAWQ
> as a new incubator project.
> 
> The proposal is available at:
>https://wiki.apache.org/incubator/HAWQProposal
> and is also included at the bottom of this email.
> 
> Vote is open until at least Thu, 3 September 2015, 23:59:00 PST
> 
> [ ] +1 accept HAWQ into the Apache Incubator
> [ ] ±0
> [ ] -1 because...
> 
> Thanks,
> Roman.
> 
> == Abstract ==
> 
> HAWQ is an advanced enterprise SQL on Hadoop analytic engine built
> around a robust and high-performance massively-parallel processing
> (MPP) SQL framework evolved from Pivotal Greenplum DatabaseⓇ.
> 
> HAWQ runs natively on Apache HadoopⓇ clusters by tightly integrating
> with HDFS and YARN. HAWQ supports multiple Hadoop file formats such as
> Apache Parquet, native HDFS, and Apache Avro. HAWQ is configured and
> managed as a Hadoop service in Apache Ambari. HAWQ is 100% ANSI SQL
> compliant (supporting ANSI SQL-92, SQL-99, and SQL-2003, plus OLAP
> extensions) and supports open database connectivity (ODBC) and Java
> database connectivity (JDBC), as well. Most business intelligence,
> data analysis and data visualization tools work with HAWQ out of the
> box without the need for specialized drivers.
> 
> A unique aspect of HAWQ is its integration of statistical and machine
> learning capabilities that can be natively invoked from SQL or (in the
> context of PL/Python, PL/Java or PL/R) in massively parallel modes and
> applied to large data sets across a Hadoop cluster. These capabilities
> are provided through MADlib – an existing open source, parallel
> machine-learning library. Given the close ties between the two
> development communities, the MADlib community has expressed interest
> in joining HAWQ on its journey into the ASF Incubator and will be
> submitting a separate, concurrent proposal.
> 
> HAWQ will provide more robust and higher performing options for Hadoop
> environments that demand best-in-class data analytics for business
> critical purposes. HAWQ is implemented in C and C++.
> 
> HAWQ has a few runtime dependencies licensed under the Cat X list:
>  * gperf (GPL Version 3)
>  * libgsasl (LGPL Version 2.1)
>  * libuuid-2.26 (LGPL Version 2)
> However, given the runtime (dynamic linking) nature of these
> dependencies it doesn't represent a problem for HAWQ to be considered
> an ASF project.
> 
> == Proposal ==
> The goal of this proposal is to bring the core of Pivotal Software,
> Inc.’s (Pivotal) Pivotal HAWQⓇ codebase into the Apache Software
> Foundation (ASF) in order to build a vibrant, diverse and
> self-governed open source community around the technology. Pivotal has
> agreed to transfer the brand name "HAWQ" to Apache Software Foundation
> and will stop using HAWQ to refer to this software if the project gets
> accepted into the ASF Incubator under the name of "Apache HAWQ
> (incubating)". Pivotal will continue to market and sell an analytic
> engine product that includes Apache HAWQ (incubating). While HAWQ is
> our primary choice for a name of the project, in anticipation of any
> potential issues with PODLINGNAMESEARCH we have come up with two
> alternative names: (1) Hornet; or (2) Grove.
> 
> Pivotal is submitting this proposal to donate the HAWQ source code and
> associated artifacts (documentation, web site content, wiki, etc.) to
> the Apache Software Foundation Incubator under the Apache License,
> Version 2.0 and is asking Incubator PMC to establish an open source
> community.
> 
> == Background ==
> While the ecosystem of open source SQL-on-Hadoop solutions is fairly
> developed by now, HAWQ has several unique features that will set it
> apart from existing ASF and non-ASF projects. HAWQ made its debut in
> 2013 as a closed source product leveraging a decade's worth of product
> development effort invested in Greenplum DatabaseⓇ. Since then HAWQ
> has rapidly gained a solid customer base and became available on
> non-Pivotal distributions of Hadoop.
> In 2015 HAWQ still leverages the rock solid foundation of Greenplum
> Database, while at the same time embracing elasticity and resource
> management native to Hadoop applications. This allows HAWQ to provide
> superior SQL on Hadoop performance, scalability and coverage while
> also providing massively-parallel machine learning capabilities and
> support for native Hadoop file formats. In addition, HAWQ's advanced
> features include support for complex joins, rich and compliant SQL
> dialect and industry-differentiating data federation capabilities.
> Dynamic pipelining and pluggable query optimizer architecture enable
> HAWQ to perform queries on Hadoop with the speed and scalability
> required for enterprise data warehouse (EDW) workloads. HAWQ provides
> strong support for low-latency analytic SQL queries, coupled with
> 

Re: [VOTE] Accept HAWQ into the Apache Incubator

[Venkatesh Seetharam]

+1.

Best wishes!

Re: [VOTE] Accept HAWQ into the Apache Incubator

[Alan Gates]

+1.

Alan.


Roman Shaposhnik 
August 31, 2015 at 11:47
Following the discussion earlier:
http://s.apache.org/Gaf

I would like to call a VOTE for accepting HAWQ
as a new incubator project.

The proposal is available at:
https://wiki.apache.org/incubator/HAWQProposal
and is also included at the bottom of this email.

Vote is open until at least Thu, 3 September 2015, 23:59:00 PST

[ ] +1 accept HAWQ into the Apache Incubator
[ ] ±0
[ ] -1 because...

Thanks,
Roman.

== Abstract ==

HAWQ is an advanced enterprise SQL on Hadoop analytic engine built
around a robust and high-performance massively-parallel processing
(MPP) SQL framework evolved from Pivotal Greenplum DatabaseⓇ.

HAWQ runs natively on Apache HadoopⓇ clusters by tightly integrating
with HDFS and YARN. HAWQ supports multiple Hadoop file formats such as
Apache Parquet, native HDFS, and Apache Avro. HAWQ is configured and
managed as a Hadoop service in Apache Ambari. HAWQ is 100% ANSI SQL
compliant (supporting ANSI SQL-92, SQL-99, and SQL-2003, plus OLAP
extensions) and supports open database connectivity (ODBC) and Java
database connectivity (JDBC), as well. Most business intelligence,
data analysis and data visualization tools work with HAWQ out of the
box without the need for specialized drivers.

A unique aspect of HAWQ is its integration of statistical and machine
learning capabilities that can be natively invoked from SQL or (in the
context of PL/Python, PL/Java or PL/R) in massively parallel modes and
applied to large data sets across a Hadoop cluster. These capabilities
are provided through MADlib – an existing open source, parallel
machine-learning library. Given the close ties between the two
development communities, the MADlib community has expressed interest
in joining HAWQ on its journey into the ASF Incubator and will be
submitting a separate, concurrent proposal.

HAWQ will provide more robust and higher performing options for Hadoop
environments that demand best-in-class data analytics for business
critical purposes. HAWQ is implemented in C and C++.

HAWQ has a few runtime dependencies licensed under the Cat X list:
* gperf (GPL Version 3)
* libgsasl (LGPL Version 2.1)
* libuuid-2.26 (LGPL Version 2)
However, given the runtime (dynamic linking) nature of these
dependencies it doesn't represent a problem for HAWQ to be considered
an ASF project.

== Proposal ==
The goal of this proposal is to bring the core of Pivotal Software,
Inc.’s (Pivotal) Pivotal HAWQⓇ codebase into the Apache Software
Foundation (ASF) in order to build a vibrant, diverse and
self-governed open source community around the technology. Pivotal has
agreed to transfer the brand name "HAWQ" to Apache Software Foundation
and will stop using HAWQ to refer to this software if the project gets
accepted into the ASF Incubator under the name of "Apache HAWQ
(incubating)". Pivotal will continue to market and sell an analytic
engine product that includes Apache HAWQ (incubating). While HAWQ is
our primary choice for a name of the project, in anticipation of any
potential issues with PODLINGNAMESEARCH we have come up with two
alternative names: (1) Hornet; or (2) Grove.

Pivotal is submitting this proposal to donate the HAWQ source code and
associated artifacts (documentation, web site content, wiki, etc.) to
the Apache Software Foundation Incubator under the Apache License,
Version 2.0 and is asking Incubator PMC to establish an open source
community.

== Background ==
While the ecosystem of open source SQL-on-Hadoop solutions is fairly
developed by now, HAWQ has several unique features that will set it
apart from existing ASF and non-ASF projects. HAWQ made its debut in
2013 as a closed source product leveraging a decade's worth of product
development effort invested in Greenplum DatabaseⓇ. Since then HAWQ
has rapidly gained a solid customer base and became available on
non-Pivotal distributions of Hadoop.
In 2015 HAWQ still leverages the rock solid foundation of Greenplum
Database, while at the same time embracing elasticity and resource
management native to Hadoop applications. This allows HAWQ to provide
superior SQL on Hadoop performance, scalability and coverage while
also providing massively-parallel machine learning capabilities and
support for native Hadoop file formats. In addition, HAWQ's advanced
features include support for complex joins, rich and compliant SQL
dialect and industry-differentiating data federation capabilities.
Dynamic pipelining and pluggable query optimizer architecture enable
HAWQ to perform queries on Hadoop with the speed and scalability
required for enterprise data warehouse (EDW) workloads. HAWQ provides
strong support for low-latency analytic SQL queries, coupled with
massively parallel machine learning capabilities. This enables
discovery-based analysis of large data sets and rapid, iterative
development of data analytics applications that apply deep machine
learning – significantly shortening data-driven 

Re: [VOTE] Accept HAWQ into the Apache Incubator

[Henry Saputra]

+1

Good luck guys! =)

On Mon, Aug 31, 2015 at 11:47 AM, Roman Shaposhnik  wrote:
> Following the discussion earlier:
>http://s.apache.org/Gaf
>
> I would like to call a VOTE for accepting HAWQ
> as a new incubator project.
>
> The proposal is available at:
> https://wiki.apache.org/incubator/HAWQProposal
> and is also included at the bottom of this email.
>
> Vote is open until at least Thu, 3 September 2015, 23:59:00 PST
>
>  [ ] +1 accept HAWQ into the Apache Incubator
>  [ ] ±0
>  [ ] -1 because...
>
> Thanks,
> Roman.
>
> == Abstract ==
>
> HAWQ is an advanced enterprise SQL on Hadoop analytic engine built
> around a robust and high-performance massively-parallel processing
> (MPP) SQL framework evolved from Pivotal Greenplum DatabaseⓇ.
>
> HAWQ runs natively on Apache HadoopⓇ clusters by tightly integrating
> with HDFS and YARN. HAWQ supports multiple Hadoop file formats such as
> Apache Parquet, native HDFS, and Apache Avro. HAWQ is configured and
> managed as a Hadoop service in Apache Ambari. HAWQ is 100% ANSI SQL
> compliant (supporting ANSI SQL-92, SQL-99, and SQL-2003, plus OLAP
> extensions) and supports open database connectivity (ODBC) and Java
> database connectivity (JDBC), as well. Most business intelligence,
> data analysis and data visualization tools work with HAWQ out of the
> box without the need for specialized drivers.
>
> A unique aspect of HAWQ is its integration of statistical and machine
> learning capabilities that can be natively invoked from SQL or (in the
> context of PL/Python, PL/Java or PL/R) in massively parallel modes and
> applied to large data sets across a Hadoop cluster. These capabilities
> are provided through MADlib – an existing open source, parallel
> machine-learning library. Given the close ties between the two
> development communities, the MADlib community has expressed interest
> in joining HAWQ on its journey into the ASF Incubator and will be
> submitting a separate, concurrent proposal.
>
> HAWQ will provide more robust and higher performing options for Hadoop
> environments that demand best-in-class data analytics for business
> critical purposes. HAWQ is implemented in C and C++.
>
> HAWQ has a few runtime dependencies licensed under the Cat X list:
>   * gperf (GPL Version 3)
>   * libgsasl (LGPL Version 2.1)
>   * libuuid-2.26 (LGPL Version 2)
> However, given the runtime (dynamic linking) nature of these
> dependencies it doesn't represent a problem for HAWQ to be considered
> an ASF project.
>
> == Proposal ==
> The goal of this proposal is to bring the core of Pivotal Software,
> Inc.’s (Pivotal) Pivotal HAWQⓇ codebase into the Apache Software
> Foundation (ASF) in order to build a vibrant, diverse and
> self-governed open source community around the technology. Pivotal has
> agreed to transfer the brand name "HAWQ" to Apache Software Foundation
> and will stop using HAWQ to refer to this software if the project gets
> accepted into the ASF Incubator under the name of "Apache HAWQ
> (incubating)". Pivotal will continue to market and sell an analytic
> engine product that includes Apache HAWQ (incubating). While HAWQ is
> our primary choice for a name of the project, in anticipation of any
> potential issues with PODLINGNAMESEARCH we have come up with two
> alternative names: (1) Hornet; or (2) Grove.
>
> Pivotal is submitting this proposal to donate the HAWQ source code and
> associated artifacts (documentation, web site content, wiki, etc.) to
> the Apache Software Foundation Incubator under the Apache License,
> Version 2.0 and is asking Incubator PMC to establish an open source
> community.
>
> == Background ==
> While the ecosystem of open source SQL-on-Hadoop solutions is fairly
> developed by now, HAWQ has several unique features that will set it
> apart from existing ASF and non-ASF projects. HAWQ made its debut in
> 2013 as a closed source product leveraging a decade's worth of product
> development effort invested in Greenplum DatabaseⓇ. Since then HAWQ
> has rapidly gained a solid customer base and became available on
> non-Pivotal distributions of Hadoop.
> In 2015 HAWQ still leverages the rock solid foundation of Greenplum
> Database, while at the same time embracing elasticity and resource
> management native to Hadoop applications. This allows HAWQ to provide
> superior SQL on Hadoop performance, scalability and coverage while
> also providing massively-parallel machine learning capabilities and
> support for native Hadoop file formats. In addition, HAWQ's advanced
> features include support for complex joins, rich and compliant SQL
> dialect and industry-differentiating data federation capabilities.
> Dynamic pipelining and pluggable query optimizer architecture enable
> HAWQ to perform queries on Hadoop with the speed and scalability
> required for enterprise data warehouse (EDW) workloads. HAWQ provides
> strong support for low-latency analytic SQL queries, coupled with
> massively parallel machine 

Re: [VOTE] Accept HAWQ into the Apache Incubator

[Hitesh Shah]

+1

— Hitesh

On Aug 31, 2015, at 11:47 AM, Roman Shaposhnik  wrote:

> Following the discussion earlier:
>   http://s.apache.org/Gaf
> 
> I would like to call a VOTE for accepting HAWQ
> as a new incubator project.
> 
> The proposal is available at:
>https://wiki.apache.org/incubator/HAWQProposal
> and is also included at the bottom of this email.
> 
> Vote is open until at least Thu, 3 September 2015, 23:59:00 PST
> 
> [ ] +1 accept HAWQ into the Apache Incubator
> [ ] ±0
> [ ] -1 because...
> 
> Thanks,
> Roman.
> 
> == Abstract ==
> 
> HAWQ is an advanced enterprise SQL on Hadoop analytic engine built
> around a robust and high-performance massively-parallel processing
> (MPP) SQL framework evolved from Pivotal Greenplum DatabaseⓇ.
> 
> HAWQ runs natively on Apache HadoopⓇ clusters by tightly integrating
> with HDFS and YARN. HAWQ supports multiple Hadoop file formats such as
> Apache Parquet, native HDFS, and Apache Avro. HAWQ is configured and
> managed as a Hadoop service in Apache Ambari. HAWQ is 100% ANSI SQL
> compliant (supporting ANSI SQL-92, SQL-99, and SQL-2003, plus OLAP
> extensions) and supports open database connectivity (ODBC) and Java
> database connectivity (JDBC), as well. Most business intelligence,
> data analysis and data visualization tools work with HAWQ out of the
> box without the need for specialized drivers.
> 
> A unique aspect of HAWQ is its integration of statistical and machine
> learning capabilities that can be natively invoked from SQL or (in the
> context of PL/Python, PL/Java or PL/R) in massively parallel modes and
> applied to large data sets across a Hadoop cluster. These capabilities
> are provided through MADlib – an existing open source, parallel
> machine-learning library. Given the close ties between the two
> development communities, the MADlib community has expressed interest
> in joining HAWQ on its journey into the ASF Incubator and will be
> submitting a separate, concurrent proposal.
> 
> HAWQ will provide more robust and higher performing options for Hadoop
> environments that demand best-in-class data analytics for business
> critical purposes. HAWQ is implemented in C and C++.
> 
> HAWQ has a few runtime dependencies licensed under the Cat X list:
>  * gperf (GPL Version 3)
>  * libgsasl (LGPL Version 2.1)
>  * libuuid-2.26 (LGPL Version 2)
> However, given the runtime (dynamic linking) nature of these
> dependencies it doesn't represent a problem for HAWQ to be considered
> an ASF project.
> 
> == Proposal ==
> The goal of this proposal is to bring the core of Pivotal Software,
> Inc.’s (Pivotal) Pivotal HAWQⓇ codebase into the Apache Software
> Foundation (ASF) in order to build a vibrant, diverse and
> self-governed open source community around the technology. Pivotal has
> agreed to transfer the brand name "HAWQ" to Apache Software Foundation
> and will stop using HAWQ to refer to this software if the project gets
> accepted into the ASF Incubator under the name of "Apache HAWQ
> (incubating)". Pivotal will continue to market and sell an analytic
> engine product that includes Apache HAWQ (incubating). While HAWQ is
> our primary choice for a name of the project, in anticipation of any
> potential issues with PODLINGNAMESEARCH we have come up with two
> alternative names: (1) Hornet; or (2) Grove.
> 
> Pivotal is submitting this proposal to donate the HAWQ source code and
> associated artifacts (documentation, web site content, wiki, etc.) to
> the Apache Software Foundation Incubator under the Apache License,
> Version 2.0 and is asking Incubator PMC to establish an open source
> community.
> 
> == Background ==
> While the ecosystem of open source SQL-on-Hadoop solutions is fairly
> developed by now, HAWQ has several unique features that will set it
> apart from existing ASF and non-ASF projects. HAWQ made its debut in
> 2013 as a closed source product leveraging a decade's worth of product
> development effort invested in Greenplum DatabaseⓇ. Since then HAWQ
> has rapidly gained a solid customer base and became available on
> non-Pivotal distributions of Hadoop.
> In 2015 HAWQ still leverages the rock solid foundation of Greenplum
> Database, while at the same time embracing elasticity and resource
> management native to Hadoop applications. This allows HAWQ to provide
> superior SQL on Hadoop performance, scalability and coverage while
> also providing massively-parallel machine learning capabilities and
> support for native Hadoop file formats. In addition, HAWQ's advanced
> features include support for complex joins, rich and compliant SQL
> dialect and industry-differentiating data federation capabilities.
> Dynamic pipelining and pluggable query optimizer architecture enable
> HAWQ to perform queries on Hadoop with the speed and scalability
> required for enterprise data warehouse (EDW) workloads. HAWQ provides
> strong support for low-latency analytic SQL queries, coupled with
> massively parallel machine learning 

RE: [VOTE] Ripple Release 0.9.32

[Tim Barham]

Oh, thanks everyone, and sorry for the ping - I missed those as I'm not 
subscribed to general@incubator.apache.org.

Tim

-Original Message-
From: Ross Gardler [mailto:ross.gard...@microsoft.com] 
Sent: Friday, August 28, 2015 12:32 PM
To: d...@ripple.incubator.apache.org; general@incubator.apache.org
Subject: RE: [VOTE] Ripple Release 0.9.32

Tim, there were a couple of additional IPMC votes you can close the vote with a 
result thread:

https://na01.safelinks.protection.outlook.com/?url=http%3a%2f%2fmarkmail.org%2fthread%2fh7pwrlvoousj6x2q=01%7c01%7cTBARHAM%40064d.mgd.microsoft.com%7c4f5652b522394c2b52c808d2afb61be3%7c72f988bf86f141af91ab2d7cd011db47%7c1=71C3vafd06IaTXLgimYJhwR3c5ATRTtwdApYdOesFcg%3d

-Original Message-
From: Tim Barham [mailto:tim.bar...@microsoft.com] 
Sent: Thursday, August 27, 2015 6:59 PM
To: d...@ripple.incubator.apache.org; general@incubator.apache.org
Subject: RE: [VOTE] Ripple Release 0.9.32

Ping! Any takers for a final IPMC vote? This should be a fairly easy one to 
validate, as there were very few changes since the last release (but one of 
those is an important fix we need to get out).

Thanks!

Tim

-Original Message-
From: Ross Gardler [mailto:ross.gard...@microsoft.com]
Sent: Sunday, August 23, 2015 8:57 AM
To: general@incubator.apache.org; d...@ripple.incubator.apache.org
Subject: RE: [VOTE] Ripple Release 0.9.32

Moving comdev to BCC, adding dev@ripple as it should have been

Ross

From: Ross Gardler
Sent: Saturday, August 22, 2015 2:43 PM
To: general@incubator.apache.org; ComDev 
Subject: [VOTE] Ripple Release 0.9.32

A vote is underway on the Ripple Dev list for release 0.9.32.

The Ripple dev thread can be found at 
https://na01.safelinks.protection.outlook.com/?url=http%3a%2f%2fmail-archives.apache.org%2fmod_mbox%2fincubator-ripple-dev%2f201508.mbox%2fbrowser=01%7c01%7cTBARHAM%40064d.mgd.microsoft.com%7ce1d3b634899b402cd20608d2abb24e57%7c72f988bf86f141af91ab2d7cd011db47%7c1=43vQT6hSifbgEkNuLz4V7ZvDjpgz1NwXPvm5dmWGW4I%3d

The text of the initial vote email is copied below for your convenience.

At this point we have 2 IPMC votes and 3 PPMC votes, I request IPMC members to 
look over the VOTE for us:

--- pasted initial VOTE text from 
https://na01.safelinks.protection.outlook.com/?url=http%3a%2f%2fmail-archives.apache.org%2fmod_mbox%2fincubator-ripple-dev%2f201508.mbox%2fbrowser=01%7c01%7cTBARHAM%40064d.mgd.microsoft.com%7ce1d3b634899b402cd20608d2abb24e57%7c72f988bf86f141af91ab2d7cd011db47%7c1=43vQT6hSifbgEkNuLz4V7ZvDjpgz1NwXPvm5dmWGW4I%3d
---

[Since 0.9.31 was a bust because of a regression, here is another release that 
includes a fix for that regression (and a couple of other minor fixes)]

Please review and vote on the release of Ripple 0.9.32.

The package you are voting on is available for review at 
https://na01.safelinks.protection.outlook.com/?url=https%3a%2f%2fdist.apache.org%2frepos%2fdist%2fdev%2fincubator%2fripple%2f.=01%7c01%7cTBARHAM%40064d.mgd.microsoft.com%7ce1d3b634899b402cd20608d2abb24e57%7c72f988bf86f141af91ab2d7cd011db47%7c1=yzBC3iO7dBinoVeu5LWkbr6S8G9a4r9xX9N3jlvBTuM%3d
The SHA-1 hash for the package is:

63a997594e4f08df8d48a644962b47bee4efd91e

It was published from its corresponding git tag:

incubator-ripple: 0.9.32 (f8c6a0bc99)

While we need three +1 *binding* votes (which for an Apache Incubator project 
like Ripple means Apache IPMC members), active Ripple contributors and 
committers/PPMC members are still encouraged to review the release and vote. 
Before voting +1, please refer to and verify compliance with the checklist at 
https://na01.safelinks.protection.outlook.com/?url=http%3a%2f%2fincubator.apache.org%2fguides%2freleasemanagement.html%23check-list=01%7c01%7cTBARHAM%40064d.mgd.microsoft.com%7ce1d3b634899b402cd20608d2abb24e57%7c72f988bf86f141af91ab2d7cd011db47%7c1=ESF8QLBAKhBz21HyHiyNLfrPBHUp7eA8FJHIcyttfYQ%3d
(however, we only need to consider changes since the previous release).

If you do vote +1, please include the steps you took in order to be confident 
the release meets requirements.

Upon a successful vote, I will upload the archive to 
dist/release/incubator/ripple and publish it to NPM.

I vote +1:
* Verified license headers with Apache RAT (using 'jake rat').
* Manually verified there were no new source files that need license headers, 
nor new third party dependencies that needed to have license information 
included in the LICENSE file.
* Verified the build works and all tests pass.
* Manually tested all changes that have been made since the last release.

Thanks!

Tim


-
To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org
For additional commands, e-mail: general-h...@incubator.apache.org

Re: [VOTE] Accept HAWQ into the Apache Incubator

[Till Westmann]

+1

> On Aug 31, 2015, at 11:49, Hitesh Shah  wrote:
> 
> +1
> 
> — Hitesh
> 
>> On Aug 31, 2015, at 11:47 AM, Roman Shaposhnik  wrote:
>> 
>> Following the discussion earlier:
>>  http://s.apache.org/Gaf
>> 
>> I would like to call a VOTE for accepting HAWQ
>> as a new incubator project.
>> 
>> The proposal is available at:
>>   https://wiki.apache.org/incubator/HAWQProposal
>> and is also included at the bottom of this email.
>> 
>> Vote is open until at least Thu, 3 September 2015, 23:59:00 PST
>> 
>> [ ] +1 accept HAWQ into the Apache Incubator
>> [ ] ±0
>> [ ] -1 because...
>> 
>> Thanks,
>> Roman.
>> 
>> == Abstract ==
>> 
>> HAWQ is an advanced enterprise SQL on Hadoop analytic engine built
>> around a robust and high-performance massively-parallel processing
>> (MPP) SQL framework evolved from Pivotal Greenplum DatabaseⓇ.
>> 
>> HAWQ runs natively on Apache HadoopⓇ clusters by tightly integrating
>> with HDFS and YARN. HAWQ supports multiple Hadoop file formats such as
>> Apache Parquet, native HDFS, and Apache Avro. HAWQ is configured and
>> managed as a Hadoop service in Apache Ambari. HAWQ is 100% ANSI SQL
>> compliant (supporting ANSI SQL-92, SQL-99, and SQL-2003, plus OLAP
>> extensions) and supports open database connectivity (ODBC) and Java
>> database connectivity (JDBC), as well. Most business intelligence,
>> data analysis and data visualization tools work with HAWQ out of the
>> box without the need for specialized drivers.
>> 
>> A unique aspect of HAWQ is its integration of statistical and machine
>> learning capabilities that can be natively invoked from SQL or (in the
>> context of PL/Python, PL/Java or PL/R) in massively parallel modes and
>> applied to large data sets across a Hadoop cluster. These capabilities
>> are provided through MADlib – an existing open source, parallel
>> machine-learning library. Given the close ties between the two
>> development communities, the MADlib community has expressed interest
>> in joining HAWQ on its journey into the ASF Incubator and will be
>> submitting a separate, concurrent proposal.
>> 
>> HAWQ will provide more robust and higher performing options for Hadoop
>> environments that demand best-in-class data analytics for business
>> critical purposes. HAWQ is implemented in C and C++.
>> 
>> HAWQ has a few runtime dependencies licensed under the Cat X list:
>> * gperf (GPL Version 3)
>> * libgsasl (LGPL Version 2.1)
>> * libuuid-2.26 (LGPL Version 2)
>> However, given the runtime (dynamic linking) nature of these
>> dependencies it doesn't represent a problem for HAWQ to be considered
>> an ASF project.
>> 
>> == Proposal ==
>> The goal of this proposal is to bring the core of Pivotal Software,
>> Inc.’s (Pivotal) Pivotal HAWQⓇ codebase into the Apache Software
>> Foundation (ASF) in order to build a vibrant, diverse and
>> self-governed open source community around the technology. Pivotal has
>> agreed to transfer the brand name "HAWQ" to Apache Software Foundation
>> and will stop using HAWQ to refer to this software if the project gets
>> accepted into the ASF Incubator under the name of "Apache HAWQ
>> (incubating)". Pivotal will continue to market and sell an analytic
>> engine product that includes Apache HAWQ (incubating). While HAWQ is
>> our primary choice for a name of the project, in anticipation of any
>> potential issues with PODLINGNAMESEARCH we have come up with two
>> alternative names: (1) Hornet; or (2) Grove.
>> 
>> Pivotal is submitting this proposal to donate the HAWQ source code and
>> associated artifacts (documentation, web site content, wiki, etc.) to
>> the Apache Software Foundation Incubator under the Apache License,
>> Version 2.0 and is asking Incubator PMC to establish an open source
>> community.
>> 
>> == Background ==
>> While the ecosystem of open source SQL-on-Hadoop solutions is fairly
>> developed by now, HAWQ has several unique features that will set it
>> apart from existing ASF and non-ASF projects. HAWQ made its debut in
>> 2013 as a closed source product leveraging a decade's worth of product
>> development effort invested in Greenplum DatabaseⓇ. Since then HAWQ
>> has rapidly gained a solid customer base and became available on
>> non-Pivotal distributions of Hadoop.
>> In 2015 HAWQ still leverages the rock solid foundation of Greenplum
>> Database, while at the same time embracing elasticity and resource
>> management native to Hadoop applications. This allows HAWQ to provide
>> superior SQL on Hadoop performance, scalability and coverage while
>> also providing massively-parallel machine learning capabilities and
>> support for native Hadoop file formats. In addition, HAWQ's advanced
>> features include support for complex joins, rich and compliant SQL
>> dialect and industry-differentiating data federation capabilities.
>> Dynamic pipelining and pluggable query optimizer architecture enable
>> HAWQ to perform queries on Hadoop with the speed and scalability

Re: [VOTE] Accept HAWQ into the Apache Incubator

[P. Taylor Goetz]

+1 (binding)

-Taylor

> On Aug 31, 2015, at 2:47 PM, Roman Shaposhnik  wrote:
> 
> Following the discussion earlier:
>   http://s.apache.org/Gaf
> 
> I would like to call a VOTE for accepting HAWQ
> as a new incubator project.
> 
> The proposal is available at:
>https://wiki.apache.org/incubator/HAWQProposal
> and is also included at the bottom of this email.
> 
> Vote is open until at least Thu, 3 September 2015, 23:59:00 PST
> 
> [ ] +1 accept HAWQ into the Apache Incubator
> [ ] ±0
> [ ] -1 because...
> 
> Thanks,
> Roman.
> 
> == Abstract ==
> 
> HAWQ is an advanced enterprise SQL on Hadoop analytic engine built
> around a robust and high-performance massively-parallel processing
> (MPP) SQL framework evolved from Pivotal Greenplum DatabaseⓇ.
> 
> HAWQ runs natively on Apache HadoopⓇ clusters by tightly integrating
> with HDFS and YARN. HAWQ supports multiple Hadoop file formats such as
> Apache Parquet, native HDFS, and Apache Avro. HAWQ is configured and
> managed as a Hadoop service in Apache Ambari. HAWQ is 100% ANSI SQL
> compliant (supporting ANSI SQL-92, SQL-99, and SQL-2003, plus OLAP
> extensions) and supports open database connectivity (ODBC) and Java
> database connectivity (JDBC), as well. Most business intelligence,
> data analysis and data visualization tools work with HAWQ out of the
> box without the need for specialized drivers.
> 
> A unique aspect of HAWQ is its integration of statistical and machine
> learning capabilities that can be natively invoked from SQL or (in the
> context of PL/Python, PL/Java or PL/R) in massively parallel modes and
> applied to large data sets across a Hadoop cluster. These capabilities
> are provided through MADlib – an existing open source, parallel
> machine-learning library. Given the close ties between the two
> development communities, the MADlib community has expressed interest
> in joining HAWQ on its journey into the ASF Incubator and will be
> submitting a separate, concurrent proposal.
> 
> HAWQ will provide more robust and higher performing options for Hadoop
> environments that demand best-in-class data analytics for business
> critical purposes. HAWQ is implemented in C and C++.
> 
> HAWQ has a few runtime dependencies licensed under the Cat X list:
>  * gperf (GPL Version 3)
>  * libgsasl (LGPL Version 2.1)
>  * libuuid-2.26 (LGPL Version 2)
> However, given the runtime (dynamic linking) nature of these
> dependencies it doesn't represent a problem for HAWQ to be considered
> an ASF project.
> 
> == Proposal ==
> The goal of this proposal is to bring the core of Pivotal Software,
> Inc.’s (Pivotal) Pivotal HAWQⓇ codebase into the Apache Software
> Foundation (ASF) in order to build a vibrant, diverse and
> self-governed open source community around the technology. Pivotal has
> agreed to transfer the brand name "HAWQ" to Apache Software Foundation
> and will stop using HAWQ to refer to this software if the project gets
> accepted into the ASF Incubator under the name of "Apache HAWQ
> (incubating)". Pivotal will continue to market and sell an analytic
> engine product that includes Apache HAWQ (incubating). While HAWQ is
> our primary choice for a name of the project, in anticipation of any
> potential issues with PODLINGNAMESEARCH we have come up with two
> alternative names: (1) Hornet; or (2) Grove.
> 
> Pivotal is submitting this proposal to donate the HAWQ source code and
> associated artifacts (documentation, web site content, wiki, etc.) to
> the Apache Software Foundation Incubator under the Apache License,
> Version 2.0 and is asking Incubator PMC to establish an open source
> community.
> 
> == Background ==
> While the ecosystem of open source SQL-on-Hadoop solutions is fairly
> developed by now, HAWQ has several unique features that will set it
> apart from existing ASF and non-ASF projects. HAWQ made its debut in
> 2013 as a closed source product leveraging a decade's worth of product
> development effort invested in Greenplum DatabaseⓇ. Since then HAWQ
> has rapidly gained a solid customer base and became available on
> non-Pivotal distributions of Hadoop.
> In 2015 HAWQ still leverages the rock solid foundation of Greenplum
> Database, while at the same time embracing elasticity and resource
> management native to Hadoop applications. This allows HAWQ to provide
> superior SQL on Hadoop performance, scalability and coverage while
> also providing massively-parallel machine learning capabilities and
> support for native Hadoop file formats. In addition, HAWQ's advanced
> features include support for complex joins, rich and compliant SQL
> dialect and industry-differentiating data federation capabilities.
> Dynamic pipelining and pluggable query optimizer architecture enable
> HAWQ to perform queries on Hadoop with the speed and scalability
> required for enterprise data warehouse (EDW) workloads. HAWQ provides
> strong support for low-latency analytic SQL queries, coupled with
> massively parallel 

Re: [VOTE] Accept HAWQ into the Apache Incubator

[Justin Mclean]

+1 (binding)

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Re: [VOTE] Accept HAWQ into the Apache Incubator

[Amol Kekre]

+1 (non-binding)

Amol


On Mon, Aug 31, 2015 at 3:03 PM, Justin Mclean  wrote:

> +1 (binding)
>
> -
> To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org
> For additional commands, e-mail: general-h...@incubator.apache.org
>
>

Re: [VOTE] Accept HAWQ into the Apache Incubator

[Edward J. Yoon]

+1 (binding)

On Tuesday, September 1, 2015, Amol Kekre  wrote:

> +1 (non-binding)
>
> Amol
>
>
> On Mon, Aug 31, 2015 at 3:03 PM, Justin Mclean  > wrote:
>
> > +1 (binding)
> >
> > -
> > To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org
> 
> > For additional commands, e-mail: general-h...@incubator.apache.org
> 
> >
> >
>


-- 
Best Regards, Edward J. Yoon

Re: [VOTE] Ripple Release 0.9.32

[Ted Dunning]

As a member of the Ripple PMC it is a good idea to subscribe to the
incubator general list.



On Fri, Aug 28, 2015 at 6:36 PM, Tim Barham 
wrote:

> Oh, thanks everyone, and sorry for the ping - I missed those as I'm not
> subscribed to general@incubator.apache.org.
>
> Tim
>
> -Original Message-
> From: Ross Gardler [mailto:ross.gard...@microsoft.com]
> Sent: Friday, August 28, 2015 12:32 PM
> To: d...@ripple.incubator.apache.org; general@incubator.apache.org
> Subject: RE: [VOTE] Ripple Release 0.9.32
>
> Tim, there were a couple of additional IPMC votes you can close the vote
> with a result thread:
>
>
> https://na01.safelinks.protection.outlook.com/?url=http%3a%2f%2fmarkmail.org%2fthread%2fh7pwrlvoousj6x2q=01%7c01%7cTBARHAM%40064d.mgd.microsoft.com%7c4f5652b522394c2b52c808d2afb61be3%7c72f988bf86f141af91ab2d7cd011db47%7c1=71C3vafd06IaTXLgimYJhwR3c5ATRTtwdApYdOesFcg%3d
>
> -Original Message-
> From: Tim Barham [mailto:tim.bar...@microsoft.com]
> Sent: Thursday, August 27, 2015 6:59 PM
> To: d...@ripple.incubator.apache.org; general@incubator.apache.org
> Subject: RE: [VOTE] Ripple Release 0.9.32
>
> Ping! Any takers for a final IPMC vote? This should be a fairly easy one
> to validate, as there were very few changes since the last release (but one
> of those is an important fix we need to get out).
>
> Thanks!
>
> Tim
>
> -Original Message-
> From: Ross Gardler [mailto:ross.gard...@microsoft.com]
> Sent: Sunday, August 23, 2015 8:57 AM
> To: general@incubator.apache.org; d...@ripple.incubator.apache.org
> Subject: RE: [VOTE] Ripple Release 0.9.32
>
> Moving comdev to BCC, adding dev@ripple as it should have been
>
> Ross
>
> From: Ross Gardler
> Sent: Saturday, August 22, 2015 2:43 PM
> To: general@incubator.apache.org; ComDev 
> Subject: [VOTE] Ripple Release 0.9.32
>
> A vote is underway on the Ripple Dev list for release 0.9.32.
>
> The Ripple dev thread can be found at
> https://na01.safelinks.protection.outlook.com/?url=http%3a%2f%2fmail-archives.apache.org%2fmod_mbox%2fincubator-ripple-dev%2f201508.mbox%2fbrowser=01%7c01%7cTBARHAM%40064d.mgd.microsoft.com%7ce1d3b634899b402cd20608d2abb24e57%7c72f988bf86f141af91ab2d7cd011db47%7c1=43vQT6hSifbgEkNuLz4V7ZvDjpgz1NwXPvm5dmWGW4I%3d
>
> The text of the initial vote email is copied below for your convenience.
>
> At this point we have 2 IPMC votes and 3 PPMC votes, I request IPMC
> members to look over the VOTE for us:
>
> --- pasted initial VOTE text from
> https://na01.safelinks.protection.outlook.com/?url=http%3a%2f%2fmail-archives.apache.org%2fmod_mbox%2fincubator-ripple-dev%2f201508.mbox%2fbrowser=01%7c01%7cTBARHAM%40064d.mgd.microsoft.com%7ce1d3b634899b402cd20608d2abb24e57%7c72f988bf86f141af91ab2d7cd011db47%7c1=43vQT6hSifbgEkNuLz4V7ZvDjpgz1NwXPvm5dmWGW4I%3d
> ---
>
> [Since 0.9.31 was a bust because of a regression, here is another release
> that includes a fix for that regression (and a couple of other minor fixes)]
>
> Please review and vote on the release of Ripple 0.9.32.
>
> The package you are voting on is available for review at
> https://na01.safelinks.protection.outlook.com/?url=https%3a%2f%2fdist.apache.org%2frepos%2fdist%2fdev%2fincubator%2fripple%2f.=01%7c01%7cTBARHAM%40064d.mgd.microsoft.com%7ce1d3b634899b402cd20608d2abb24e57%7c72f988bf86f141af91ab2d7cd011db47%7c1=yzBC3iO7dBinoVeu5LWkbr6S8G9a4r9xX9N3jlvBTuM%3d
> The SHA-1 hash for the package is:
>
> 63a997594e4f08df8d48a644962b47bee4efd91e
>
> It was published from its corresponding git tag:
>
> incubator-ripple: 0.9.32 (f8c6a0bc99)
>
> While we need three +1 *binding* votes (which for an Apache Incubator
> project like Ripple means Apache IPMC members), active Ripple contributors
> and committers/PPMC members are still encouraged to review the release and
> vote. Before voting +1, please refer to and verify compliance with the
> checklist at
> https://na01.safelinks.protection.outlook.com/?url=http%3a%2f%2fincubator.apache.org%2fguides%2freleasemanagement.html%23check-list=01%7c01%7cTBARHAM%40064d.mgd.microsoft.com%7ce1d3b634899b402cd20608d2abb24e57%7c72f988bf86f141af91ab2d7cd011db47%7c1=ESF8QLBAKhBz21HyHiyNLfrPBHUp7eA8FJHIcyttfYQ%3d
> (however, we only need to consider changes since the previous release).
>
> If you do vote +1, please include the steps you took in order to be
> confident the release meets requirements.
>
> Upon a successful vote, I will upload the archive to
> dist/release/incubator/ripple and publish it to NPM.
>
> I vote +1:
> * Verified license headers with Apache RAT (using 'jake rat').
> * Manually verified there were no new source files that need license
> headers, nor new third party dependencies that needed to have license
> information included in the LICENSE file.
> * Verified the build works and all tests pass.
> * Manually tested all changes that have been made since the last release.
>
> Thanks!
>
> Tim
>
>
> 

Re: [VOTE] Accept Horn into the ASF incubator

[Behroz Sikander]

+1

On Tue, Sep 1, 2015 at 1:13 AM, Edward J. Yoon 
wrote:

> Hi folks,
>
> I would like to call a vote to accept Horn, as a new Apache Incubator
> project. The full proposal is available at the end of this mail and as
> a https://wiki.apache.org/incubator/HornProposal (the changes from
> initial discussion draft are addition of 2 committers from cldi-kaist
> team and Rich as a mentor).
>
> The VOTE is open for at least the next 72 hours:
>
> [ ] +1 Accept Horn into the Apache Incubator
> [ ] 0
> [ ] -1 Do not accept Horn into the Apache Incubator bc ..
>
> I'd like to get the voting started w/ my own +1
>
> Thanks!
>
> == Abstract ==
>
> Horn [hɔ:n] (korean meaning of Horn is a "Spirit") is a neuron-centric
> programming APIs and execution framework for large-scale deep
> learning, built on top of Apache Hama.
>
> == Proposal ==
>
> It is a goal of the Horn to provide a neuron-centric programming APIs
> which allows user to easily define the characteristic of artificial
> neural network model and its structure, and its execution framework
> that leverages the heterogeneous resources on Hama and Hadoop YARN
> cluster.
>
> == Background ==
>
> The initial ANN code was developed at Apache Hama project by a
> committer, Yexi Jiang (Facebook) in 2013. The motivation behind this
> work is to build a framework that provides more intuitive programming
> APIs like Google's MapReduce or Pregel and supports applications
> needing large model with huge memory consumptions in distributed way.
>
> == Rationale ==
>
> While many of deep learning open source softwares such as Caffe,
> DeepDist, DL4j, and NeuralGiraph are still data or model parallel
> only, we aim to support both data and model parallelism and also
> fault-tolerant system design. The basic idea of data and model
> parallelism is use of the remote parameter server to parallelize model
> creation and distribute training across machines, and the BSP
> framework of Apache Hama for performing asynchronous mini-batches.
> Within single BSP job, each task group works asynchronously using
> region barrier synchronization instead of global barrier
> synchronization, and trains large-scale neural network model using
> assigned data sets in BSP paradigm. Thus, we achieve data and model
> parallelism. This architecture is inspired by Google's !DistBelief
> (Jeff Dean et al, 2012).
>
> == Initial Goals ==
>
> Some current goals include:
>
>  * builds new community
>  * provides more intuitive programming APIs
>  * needs both data and model parallelism support
>  * must run natively on both Hama and Hadoop2
>  * needs also GPUs and InfiniBand support (FPGAs if possible)
>
> == Current Status ==
>
> === Meritocracy ===
>
> The core developers understand what it means to have a process based
> on meritocracy. We will provide continuous efforts to build an
> environment that supports this, encouraging community members to
> contribute.
>
> === Community ===
>
> A small community has formed within the Apache Hama project community,
> universities, and companies such as deep learning startup, instant
> messenger service company, and mobile manufacturing company. And many
> people are interested in the large-scale deep learning platform
> itself. By bringing Horn into Apache, we believe that the community
> will grow even bigger.
>
> === Core Developers ===
>
> Edward J. Yoon, Thomas Jungblut, Jungin Lee, and Minho Kim
>
> == Known Risks ==
>
> === Orphaned Products ===
>
> Apache Hama is already a core open source component at Samsung
> Electronics, and Horn also will be used by Samsung Electronics and
> Cldi Inc., and so there is no direct risk for this project to be
> orphaned.
>
> === Inexperience with Open Source ===
>
> Some are very new and the others have experience using and/or working
> on Apache open source projects.
>
> === Homogeneous Developers ===
>
> The initial committers are from different organizations such as,
> Microsoft, Samsung Electronics, Seoul National University, Technical
> University of Munich, KAIST, LINE plus, and Cldi Inc.
>
> === Reliance on Salaried Developers ===
>
> Few will be worked as a full-time open source developer. Other
> developers will also start working on the project in their spare time.
>
> === Relationships with Other Apache Products ===
>
>  * Horn is based on Apache Hama
>  * Apache Zookeeper is used for distributed locking service
>  * Natively run on Apache Hadoop and Mesos
>  * Horn can be somewhat overlapped with Singa podling (If possible,
> we'd also like to use Singa or Caffe to do the heavy lifting part).
>
> === An Excessive Fascination with the Apache Brand ===
>
> Horn itself will hopefully have benefits from Apache, in terms of
> attracting a community and establishing a solid group of developers,
> but also the relation with Apache Hadoop, Zookeeper, and Hama. These
> are the main reasons for us to send this proposal.
>
> == Documentation ==
>
> Initial plan about Horn can be found at
> 

Re: [VOTE] Release apache-calcite-1.4.0-incubating

[Ashutosh Chauhan]

Forwarding my +1 from Calcite list.

Ashutosh

On Mon, Aug 31, 2015 at 10:59 AM, Alan Gates  wrote:

> Forwarding my +1 from the Calcite vote.
>
> Alan.
>
> Jacques Nadeau 
> August 28, 2015 at 14:32
> Hi all,
>
> The Calcite community has voted on and approved a proposal to release
> Apache Calcite 1.4.0-incubating.
>
> Proposal:
>
> http://mail-archives.apache.org/mod_mbox/incubator-calcite-dev/201508.mbox/%3CCAKa9qD%3DWA1s03rUEuCUbUbWiBgmC_9N%3D1r39dXjLAKevRt6UCQ%40mail.gmail.com%3E
>
> Vote result:
> 8 binding +1 votes
> 1 non-binding +1 votes
> No -1 votes
>
> http://mail-archives.apache.org/mod_mbox/incubator-calcite-dev/201508.mbox/%3CCAKa9qD%3DPUH70eyPY3u25O4ayimwOXfBBxiX2txUEcNbUCYODXg%40mail.gmail.com%3E
>
> The commit to be voted upon:
>
> http://git-wip-us.apache.org/repos/asf/incubator-calcite/commit/0c0c203daec56c05b6c75fa3896c8af19844df68
>
> Its hash is 0c0c203daec56c05b6c75fa3896c8af19844df68.
>
> The artifacts to be voted on are located here:
>
> https://dist.apache.org/repos/dist/dev/incubator/calcite/apache-calcite-1.4.0-incubating-rc0
>
> The hashes of the artifacts are as follows:
> src.tar.gz.md5 e052e2b1ffdbdab9eaeb30f4ac838e75
> src.tar.gz.sha1 fd979e8b330bb0d3b9be8625c95589e0eb358722
> src.zip.md5 ef1880617f3b6415c5e3779d9c2bbc10
> src.zip.sha1 b865a9a45046a339c53834e7abea7a7a55927f07
>
> A staged Maven repository is available for review at:
> https://repository.apache.org/content/repositories/orgapachecalcite-1009
>
> Release artifacts are signed with the following key:
> https://people.apache.org/keys/committer/jacques.asc
>
> Pursuant to the Releases section of the Incubation Policy and with
> the endorsement of 2 of our mentors we would now like to request
> the permission of the Incubator PMC to publish the release. The vote
> is open for 72 hours, or until the necessary number of votes (3 +1)
> is reached.
>
> [ ] +1 Release this package as Apache Calcite 1.4.0-incubating
> [ ] -1 Do not release this package because...
>
> Jacques Nadeau, on behalf of Apache Calcite PPMC
>
>

Re: September 2015 Report

[Konstantin Boudnik]

I have just updated the podlings.xml to reflect that Ignite has graduated. So
they won't be reporting as a part of Incubator any more.

Thanks,
  Cos

On Sat, Aug 29, 2015 at 08:58AM, jan i wrote:
> Hi.
> 
> I really like our open way of reporting using the wiki but we have a small
> flaw in the procedure.
> 
> The wiki is not the place to report a  section, so I
> will send it to private@i.a.o and hope it will  be included.
> 
> rgds
> jan i.
> 
> 
> On 29 August 2015 at 01:00, Marvin Humphrey  wrote:
> 
> > Greetings, {podling} developers!
> >
> > This is a reminder that your report is due next Wednesday, September
> > 2nd.  Details below.
> >
> > Best,
> >
> > Marvin Humphrey, Report Manager for September, on behalf of the
> > Incubator PMC
> >
> > ---
> >
> > Dear podling,
> >
> > This email was sent by an automated system on behalf of the Apache
> > Incubator PMC. It is an initial reminder to give you plenty of time to
> > prepare your quarterly board report.
> >
> > The board meeting is scheduled for Wed, 16 September 2015, 10:30 am
> > Pacific.  The report for your podling will form a part of the Incubator
> > PMC report. The Incubator PMC requires your report to be submitted 2
> > weeks before the board meeting, to allow sufficient time for review and
> > submission (Wed, September 2nd).
> >
> > Please submit your report with sufficient time to allow the incubator
> > PMC, and subsequently board members to review and digest. Again, the
> > very latest you should submit your report is 2 weeks prior to the board
> > meeting.
> >
> > Thanks,
> >
> > The Apache Incubator PMC
> >
> > Submitting your Report
> >
> > --
> >
> > Your report should contain the following:
> >
> > *   Your project name
> > *   A brief description of your project, which assumes no knowledge of
> > the project or necessarily of its field
> > *   A list of the three most important issues to address in the move
> > towards graduation.
> > *   Any issues that the Incubator PMC or ASF Board might wish/need to be
> > aware of
> > *   How has the community developed since the last report
> > *   How has the project developed since the last report.
> >
> > This should be appended to the Incubator Wiki page at:
> >
> > http://wiki.apache.org/incubator/September2015
> >
> > Note: This is manually populated. You may need to wait a little before
> > this page is created from a template.
> >
> > Mentors
> > ---
> >
> > Mentors should review reports for their project(s) and sign them off on
> > the Incubator wiki page. Signing off reports shows that you are
> > following the project - projects that are not signed may raise alarms
> > for the Incubator PMC.
> >
> > Incubator PMC
> >

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Re: [VOTE] Accept HAWQ into the Apache Incubator

[Konstantin Boudnik]

+1 (binding)

On Mon, Aug 31, 2015 at 11:47AM, Roman Shaposhnik wrote:
> Following the discussion earlier:
>http://s.apache.org/Gaf
> 
> I would like to call a VOTE for accepting HAWQ
> as a new incubator project.
> 
> The proposal is available at:
> https://wiki.apache.org/incubator/HAWQProposal
> and is also included at the bottom of this email.
> 
> Vote is open until at least Thu, 3 September 2015, 23:59:00 PST
> 
>  [ ] +1 accept HAWQ into the Apache Incubator
>  [ ] ±0
>  [ ] -1 because...
> 
> Thanks,
> Roman.
> 
> == Abstract ==
> 
> HAWQ is an advanced enterprise SQL on Hadoop analytic engine built
> around a robust and high-performance massively-parallel processing
> (MPP) SQL framework evolved from Pivotal Greenplum DatabaseⓇ.
> 
> HAWQ runs natively on Apache HadoopⓇ clusters by tightly integrating
> with HDFS and YARN. HAWQ supports multiple Hadoop file formats such as
> Apache Parquet, native HDFS, and Apache Avro. HAWQ is configured and
> managed as a Hadoop service in Apache Ambari. HAWQ is 100% ANSI SQL
> compliant (supporting ANSI SQL-92, SQL-99, and SQL-2003, plus OLAP
> extensions) and supports open database connectivity (ODBC) and Java
> database connectivity (JDBC), as well. Most business intelligence,
> data analysis and data visualization tools work with HAWQ out of the
> box without the need for specialized drivers.
> 
> A unique aspect of HAWQ is its integration of statistical and machine
> learning capabilities that can be natively invoked from SQL or (in the
> context of PL/Python, PL/Java or PL/R) in massively parallel modes and
> applied to large data sets across a Hadoop cluster. These capabilities
> are provided through MADlib – an existing open source, parallel
> machine-learning library. Given the close ties between the two
> development communities, the MADlib community has expressed interest
> in joining HAWQ on its journey into the ASF Incubator and will be
> submitting a separate, concurrent proposal.
> 
> HAWQ will provide more robust and higher performing options for Hadoop
> environments that demand best-in-class data analytics for business
> critical purposes. HAWQ is implemented in C and C++.
> 
> HAWQ has a few runtime dependencies licensed under the Cat X list:
>   * gperf (GPL Version 3)
>   * libgsasl (LGPL Version 2.1)
>   * libuuid-2.26 (LGPL Version 2)
> However, given the runtime (dynamic linking) nature of these
> dependencies it doesn't represent a problem for HAWQ to be considered
> an ASF project.
> 
> == Proposal ==
> The goal of this proposal is to bring the core of Pivotal Software,
> Inc.’s (Pivotal) Pivotal HAWQⓇ codebase into the Apache Software
> Foundation (ASF) in order to build a vibrant, diverse and
> self-governed open source community around the technology. Pivotal has
> agreed to transfer the brand name "HAWQ" to Apache Software Foundation
> and will stop using HAWQ to refer to this software if the project gets
> accepted into the ASF Incubator under the name of "Apache HAWQ
> (incubating)". Pivotal will continue to market and sell an analytic
> engine product that includes Apache HAWQ (incubating). While HAWQ is
> our primary choice for a name of the project, in anticipation of any
> potential issues with PODLINGNAMESEARCH we have come up with two
> alternative names: (1) Hornet; or (2) Grove.
> 
> Pivotal is submitting this proposal to donate the HAWQ source code and
> associated artifacts (documentation, web site content, wiki, etc.) to
> the Apache Software Foundation Incubator under the Apache License,
> Version 2.0 and is asking Incubator PMC to establish an open source
> community.
> 
> == Background ==
> While the ecosystem of open source SQL-on-Hadoop solutions is fairly
> developed by now, HAWQ has several unique features that will set it
> apart from existing ASF and non-ASF projects. HAWQ made its debut in
> 2013 as a closed source product leveraging a decade's worth of product
> development effort invested in Greenplum DatabaseⓇ. Since then HAWQ
> has rapidly gained a solid customer base and became available on
> non-Pivotal distributions of Hadoop.
> In 2015 HAWQ still leverages the rock solid foundation of Greenplum
> Database, while at the same time embracing elasticity and resource
> management native to Hadoop applications. This allows HAWQ to provide
> superior SQL on Hadoop performance, scalability and coverage while
> also providing massively-parallel machine learning capabilities and
> support for native Hadoop file formats. In addition, HAWQ's advanced
> features include support for complex joins, rich and compliant SQL
> dialect and industry-differentiating data federation capabilities.
> Dynamic pipelining and pluggable query optimizer architecture enable
> HAWQ to perform queries on Hadoop with the speed and scalability
> required for enterprise data warehouse (EDW) workloads. HAWQ provides
> strong support for low-latency analytic SQL queries, coupled with
> massively parallel machine learning 

Re: September 2015 Report

[John D. Ament]

I went ahead and removed them from this month's report as well.  Thanks for
the info Cos.

John

On Mon, Aug 31, 2015 at 7:56 PM Konstantin Boudnik  wrote:

> I have just updated the podlings.xml to reflect that Ignite has graduated.
> So
> they won't be reporting as a part of Incubator any more.
>
> Thanks,
>   Cos
>
> On Sat, Aug 29, 2015 at 08:58AM, jan i wrote:
> > Hi.
> >
> > I really like our open way of reporting using the wiki but we have a
> small
> > flaw in the procedure.
> >
> > The wiki is not the place to report a  section, so I
> > will send it to private@i.a.o and hope it will  be included.
> >
> > rgds
> > jan i.
> >
> >
> > On 29 August 2015 at 01:00, Marvin Humphrey  wrote:
> >
> > > Greetings, {podling} developers!
> > >
> > > This is a reminder that your report is due next Wednesday, September
> > > 2nd.  Details below.
> > >
> > > Best,
> > >
> > > Marvin Humphrey, Report Manager for September, on behalf of the
> > > Incubator PMC
> > >
> > > ---
> > >
> > > Dear podling,
> > >
> > > This email was sent by an automated system on behalf of the Apache
> > > Incubator PMC. It is an initial reminder to give you plenty of time to
> > > prepare your quarterly board report.
> > >
> > > The board meeting is scheduled for Wed, 16 September 2015, 10:30 am
> > > Pacific.  The report for your podling will form a part of the Incubator
> > > PMC report. The Incubator PMC requires your report to be submitted 2
> > > weeks before the board meeting, to allow sufficient time for review and
> > > submission (Wed, September 2nd).
> > >
> > > Please submit your report with sufficient time to allow the incubator
> > > PMC, and subsequently board members to review and digest. Again, the
> > > very latest you should submit your report is 2 weeks prior to the board
> > > meeting.
> > >
> > > Thanks,
> > >
> > > The Apache Incubator PMC
> > >
> > > Submitting your Report
> > >
> > > --
> > >
> > > Your report should contain the following:
> > >
> > > *   Your project name
> > > *   A brief description of your project, which assumes no knowledge of
> > > the project or necessarily of its field
> > > *   A list of the three most important issues to address in the move
> > > towards graduation.
> > > *   Any issues that the Incubator PMC or ASF Board might wish/need to
> be
> > > aware of
> > > *   How has the community developed since the last report
> > > *   How has the project developed since the last report.
> > >
> > > This should be appended to the Incubator Wiki page at:
> > >
> > > http://wiki.apache.org/incubator/September2015
> > >
> > > Note: This is manually populated. You may need to wait a little before
> > > this page is created from a template.
> > >
> > > Mentors
> > > ---
> > >
> > > Mentors should review reports for their project(s) and sign them off on
> > > the Incubator wiki page. Signing off reports shows that you are
> > > following the project - projects that are not signed may raise alarms
> > > for the Incubator PMC.
> > >
> > > Incubator PMC
> > >
>
> -
> To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org
> For additional commands, e-mail: general-h...@incubator.apache.org
>
>

Re: [VOTE] Accept Horn into the ASF incubator

[Minho Kim]

+1

2015-09-01 8:35 GMT+09:00 Behroz Sikander :

> +1
>
> On Tue, Sep 1, 2015 at 1:13 AM, Edward J. Yoon 
> wrote:
>
> > Hi folks,
> >
> > I would like to call a vote to accept Horn, as a new Apache Incubator
> > project. The full proposal is available at the end of this mail and as
> > a https://wiki.apache.org/incubator/HornProposal (the changes from
> > initial discussion draft are addition of 2 committers from cldi-kaist
> > team and Rich as a mentor).
> >
> > The VOTE is open for at least the next 72 hours:
> >
> > [ ] +1 Accept Horn into the Apache Incubator
> > [ ] 0
> > [ ] -1 Do not accept Horn into the Apache Incubator bc ..
> >
> > I'd like to get the voting started w/ my own +1
> >
> > Thanks!
> >
> > == Abstract ==
> >
> > Horn [hɔ:n] (korean meaning of Horn is a "Spirit") is a neuron-centric
> > programming APIs and execution framework for large-scale deep
> > learning, built on top of Apache Hama.
> >
> > == Proposal ==
> >
> > It is a goal of the Horn to provide a neuron-centric programming APIs
> > which allows user to easily define the characteristic of artificial
> > neural network model and its structure, and its execution framework
> > that leverages the heterogeneous resources on Hama and Hadoop YARN
> > cluster.
> >
> > == Background ==
> >
> > The initial ANN code was developed at Apache Hama project by a
> > committer, Yexi Jiang (Facebook) in 2013. The motivation behind this
> > work is to build a framework that provides more intuitive programming
> > APIs like Google's MapReduce or Pregel and supports applications
> > needing large model with huge memory consumptions in distributed way.
> >
> > == Rationale ==
> >
> > While many of deep learning open source softwares such as Caffe,
> > DeepDist, DL4j, and NeuralGiraph are still data or model parallel
> > only, we aim to support both data and model parallelism and also
> > fault-tolerant system design. The basic idea of data and model
> > parallelism is use of the remote parameter server to parallelize model
> > creation and distribute training across machines, and the BSP
> > framework of Apache Hama for performing asynchronous mini-batches.
> > Within single BSP job, each task group works asynchronously using
> > region barrier synchronization instead of global barrier
> > synchronization, and trains large-scale neural network model using
> > assigned data sets in BSP paradigm. Thus, we achieve data and model
> > parallelism. This architecture is inspired by Google's !DistBelief
> > (Jeff Dean et al, 2012).
> >
> > == Initial Goals ==
> >
> > Some current goals include:
> >
> >  * builds new community
> >  * provides more intuitive programming APIs
> >  * needs both data and model parallelism support
> >  * must run natively on both Hama and Hadoop2
> >  * needs also GPUs and InfiniBand support (FPGAs if possible)
> >
> > == Current Status ==
> >
> > === Meritocracy ===
> >
> > The core developers understand what it means to have a process based
> > on meritocracy. We will provide continuous efforts to build an
> > environment that supports this, encouraging community members to
> > contribute.
> >
> > === Community ===
> >
> > A small community has formed within the Apache Hama project community,
> > universities, and companies such as deep learning startup, instant
> > messenger service company, and mobile manufacturing company. And many
> > people are interested in the large-scale deep learning platform
> > itself. By bringing Horn into Apache, we believe that the community
> > will grow even bigger.
> >
> > === Core Developers ===
> >
> > Edward J. Yoon, Thomas Jungblut, Jungin Lee, and Minho Kim
> >
> > == Known Risks ==
> >
> > === Orphaned Products ===
> >
> > Apache Hama is already a core open source component at Samsung
> > Electronics, and Horn also will be used by Samsung Electronics and
> > Cldi Inc., and so there is no direct risk for this project to be
> > orphaned.
> >
> > === Inexperience with Open Source ===
> >
> > Some are very new and the others have experience using and/or working
> > on Apache open source projects.
> >
> > === Homogeneous Developers ===
> >
> > The initial committers are from different organizations such as,
> > Microsoft, Samsung Electronics, Seoul National University, Technical
> > University of Munich, KAIST, LINE plus, and Cldi Inc.
> >
> > === Reliance on Salaried Developers ===
> >
> > Few will be worked as a full-time open source developer. Other
> > developers will also start working on the project in their spare time.
> >
> > === Relationships with Other Apache Products ===
> >
> >  * Horn is based on Apache Hama
> >  * Apache Zookeeper is used for distributed locking service
> >  * Natively run on Apache Hadoop and Mesos
> >  * Horn can be somewhat overlapped with Singa podling (If possible,
> > we'd also like to use Singa or Caffe to do the heavy lifting part).
> >
> > === An Excessive Fascination with the Apache Brand ===
> >
> > Horn 

Re: [VOTE] Accept HAWQ into the Apache Incubator

[Justin Erenkrantz]

+1.  -- justin
On Aug 31, 2015 2:48 PM, "Roman Shaposhnik"  wrote:

> Following the discussion earlier:
>http://s.apache.org/Gaf
>
> I would like to call a VOTE for accepting HAWQ
> as a new incubator project.
>
> The proposal is available at:
> https://wiki.apache.org/incubator/HAWQProposal
> and is also included at the bottom of this email.
>
> Vote is open until at least Thu, 3 September 2015, 23:59:00 PST
>
>  [ ] +1 accept HAWQ into the Apache Incubator
>  [ ] ±0
>  [ ] -1 because...
>
> Thanks,
> Roman.
>
> == Abstract ==
>
> HAWQ is an advanced enterprise SQL on Hadoop analytic engine built
> around a robust and high-performance massively-parallel processing
> (MPP) SQL framework evolved from Pivotal Greenplum DatabaseⓇ.
>
> HAWQ runs natively on Apache HadoopⓇ clusters by tightly integrating
> with HDFS and YARN. HAWQ supports multiple Hadoop file formats such as
> Apache Parquet, native HDFS, and Apache Avro. HAWQ is configured and
> managed as a Hadoop service in Apache Ambari. HAWQ is 100% ANSI SQL
> compliant (supporting ANSI SQL-92, SQL-99, and SQL-2003, plus OLAP
> extensions) and supports open database connectivity (ODBC) and Java
> database connectivity (JDBC), as well. Most business intelligence,
> data analysis and data visualization tools work with HAWQ out of the
> box without the need for specialized drivers.
>
> A unique aspect of HAWQ is its integration of statistical and machine
> learning capabilities that can be natively invoked from SQL or (in the
> context of PL/Python, PL/Java or PL/R) in massively parallel modes and
> applied to large data sets across a Hadoop cluster. These capabilities
> are provided through MADlib – an existing open source, parallel
> machine-learning library. Given the close ties between the two
> development communities, the MADlib community has expressed interest
> in joining HAWQ on its journey into the ASF Incubator and will be
> submitting a separate, concurrent proposal.
>
> HAWQ will provide more robust and higher performing options for Hadoop
> environments that demand best-in-class data analytics for business
> critical purposes. HAWQ is implemented in C and C++.
>
> HAWQ has a few runtime dependencies licensed under the Cat X list:
>   * gperf (GPL Version 3)
>   * libgsasl (LGPL Version 2.1)
>   * libuuid-2.26 (LGPL Version 2)
> However, given the runtime (dynamic linking) nature of these
> dependencies it doesn't represent a problem for HAWQ to be considered
> an ASF project.
>
> == Proposal ==
> The goal of this proposal is to bring the core of Pivotal Software,
> Inc.’s (Pivotal) Pivotal HAWQⓇ codebase into the Apache Software
> Foundation (ASF) in order to build a vibrant, diverse and
> self-governed open source community around the technology. Pivotal has
> agreed to transfer the brand name "HAWQ" to Apache Software Foundation
> and will stop using HAWQ to refer to this software if the project gets
> accepted into the ASF Incubator under the name of "Apache HAWQ
> (incubating)". Pivotal will continue to market and sell an analytic
> engine product that includes Apache HAWQ (incubating). While HAWQ is
> our primary choice for a name of the project, in anticipation of any
> potential issues with PODLINGNAMESEARCH we have come up with two
> alternative names: (1) Hornet; or (2) Grove.
>
> Pivotal is submitting this proposal to donate the HAWQ source code and
> associated artifacts (documentation, web site content, wiki, etc.) to
> the Apache Software Foundation Incubator under the Apache License,
> Version 2.0 and is asking Incubator PMC to establish an open source
> community.
>
> == Background ==
> While the ecosystem of open source SQL-on-Hadoop solutions is fairly
> developed by now, HAWQ has several unique features that will set it
> apart from existing ASF and non-ASF projects. HAWQ made its debut in
> 2013 as a closed source product leveraging a decade's worth of product
> development effort invested in Greenplum DatabaseⓇ. Since then HAWQ
> has rapidly gained a solid customer base and became available on
> non-Pivotal distributions of Hadoop.
> In 2015 HAWQ still leverages the rock solid foundation of Greenplum
> Database, while at the same time embracing elasticity and resource
> management native to Hadoop applications. This allows HAWQ to provide
> superior SQL on Hadoop performance, scalability and coverage while
> also providing massively-parallel machine learning capabilities and
> support for native Hadoop file formats. In addition, HAWQ's advanced
> features include support for complex joins, rich and compliant SQL
> dialect and industry-differentiating data federation capabilities.
> Dynamic pipelining and pluggable query optimizer architecture enable
> HAWQ to perform queries on Hadoop with the speed and scalability
> required for enterprise data warehouse (EDW) workloads. HAWQ provides
> strong support for low-latency analytic SQL queries, coupled with
> massively parallel machine learning 

Re: [VOTE] Accept Horn into the ASF incubator

[Chris Aniszczyk]

+1

On Mon, Aug 31, 2015 at 7:13 PM, Edward J. Yoon 
wrote:

> Hi folks,
>
> I would like to call a vote to accept Horn, as a new Apache Incubator
> project. The full proposal is available at the end of this mail and as
> a https://wiki.apache.org/incubator/HornProposal (the changes from
> initial discussion draft are addition of 2 committers from cldi-kaist
> team and Rich as a mentor).
>
> The VOTE is open for at least the next 72 hours:
>
> [ ] +1 Accept Horn into the Apache Incubator
> [ ] 0
> [ ] -1 Do not accept Horn into the Apache Incubator bc ..
>
> I'd like to get the voting started w/ my own +1
>
> Thanks!
>
> == Abstract ==
>
> Horn [hɔ:n] (korean meaning of Horn is a "Spirit") is a neuron-centric
> programming APIs and execution framework for large-scale deep
> learning, built on top of Apache Hama.
>
> == Proposal ==
>
> It is a goal of the Horn to provide a neuron-centric programming APIs
> which allows user to easily define the characteristic of artificial
> neural network model and its structure, and its execution framework
> that leverages the heterogeneous resources on Hama and Hadoop YARN
> cluster.
>
> == Background ==
>
> The initial ANN code was developed at Apache Hama project by a
> committer, Yexi Jiang (Facebook) in 2013. The motivation behind this
> work is to build a framework that provides more intuitive programming
> APIs like Google's MapReduce or Pregel and supports applications
> needing large model with huge memory consumptions in distributed way.
>
> == Rationale ==
>
> While many of deep learning open source softwares such as Caffe,
> DeepDist, DL4j, and NeuralGiraph are still data or model parallel
> only, we aim to support both data and model parallelism and also
> fault-tolerant system design. The basic idea of data and model
> parallelism is use of the remote parameter server to parallelize model
> creation and distribute training across machines, and the BSP
> framework of Apache Hama for performing asynchronous mini-batches.
> Within single BSP job, each task group works asynchronously using
> region barrier synchronization instead of global barrier
> synchronization, and trains large-scale neural network model using
> assigned data sets in BSP paradigm. Thus, we achieve data and model
> parallelism. This architecture is inspired by Google's !DistBelief
> (Jeff Dean et al, 2012).
>
> == Initial Goals ==
>
> Some current goals include:
>
>  * builds new community
>  * provides more intuitive programming APIs
>  * needs both data and model parallelism support
>  * must run natively on both Hama and Hadoop2
>  * needs also GPUs and InfiniBand support (FPGAs if possible)
>
> == Current Status ==
>
> === Meritocracy ===
>
> The core developers understand what it means to have a process based
> on meritocracy. We will provide continuous efforts to build an
> environment that supports this, encouraging community members to
> contribute.
>
> === Community ===
>
> A small community has formed within the Apache Hama project community,
> universities, and companies such as deep learning startup, instant
> messenger service company, and mobile manufacturing company. And many
> people are interested in the large-scale deep learning platform
> itself. By bringing Horn into Apache, we believe that the community
> will grow even bigger.
>
> === Core Developers ===
>
> Edward J. Yoon, Thomas Jungblut, Jungin Lee, and Minho Kim
>
> == Known Risks ==
>
> === Orphaned Products ===
>
> Apache Hama is already a core open source component at Samsung
> Electronics, and Horn also will be used by Samsung Electronics and
> Cldi Inc., and so there is no direct risk for this project to be
> orphaned.
>
> === Inexperience with Open Source ===
>
> Some are very new and the others have experience using and/or working
> on Apache open source projects.
>
> === Homogeneous Developers ===
>
> The initial committers are from different organizations such as,
> Microsoft, Samsung Electronics, Seoul National University, Technical
> University of Munich, KAIST, LINE plus, and Cldi Inc.
>
> === Reliance on Salaried Developers ===
>
> Few will be worked as a full-time open source developer. Other
> developers will also start working on the project in their spare time.
>
> === Relationships with Other Apache Products ===
>
>  * Horn is based on Apache Hama
>  * Apache Zookeeper is used for distributed locking service
>  * Natively run on Apache Hadoop and Mesos
>  * Horn can be somewhat overlapped with Singa podling (If possible,
> we'd also like to use Singa or Caffe to do the heavy lifting part).
>
> === An Excessive Fascination with the Apache Brand ===
>
> Horn itself will hopefully have benefits from Apache, in terms of
> attracting a community and establishing a solid group of developers,
> but also the relation with Apache Hadoop, Zookeeper, and Hama. These
> are the main reasons for us to send this proposal.
>
> == Documentation ==
>
> Initial plan about Horn can be found at

Re: [VOTE] Accept HAWQ into the Apache Incubator

[John D. Ament]

+1

On Mon, Aug 31, 2015 at 2:48 PM Roman Shaposhnik  wrote:

> Following the discussion earlier:
>http://s.apache.org/Gaf
>
> I would like to call a VOTE for accepting HAWQ
> as a new incubator project.
>
> The proposal is available at:
> https://wiki.apache.org/incubator/HAWQProposal
> and is also included at the bottom of this email.
>
> Vote is open until at least Thu, 3 September 2015, 23:59:00 PST
>
>  [ ] +1 accept HAWQ into the Apache Incubator
>  [ ] ±0
>  [ ] -1 because...
>
> Thanks,
> Roman.
>
> == Abstract ==
>
> HAWQ is an advanced enterprise SQL on Hadoop analytic engine built
> around a robust and high-performance massively-parallel processing
> (MPP) SQL framework evolved from Pivotal Greenplum DatabaseⓇ.
>
> HAWQ runs natively on Apache HadoopⓇ clusters by tightly integrating
> with HDFS and YARN. HAWQ supports multiple Hadoop file formats such as
> Apache Parquet, native HDFS, and Apache Avro. HAWQ is configured and
> managed as a Hadoop service in Apache Ambari. HAWQ is 100% ANSI SQL
> compliant (supporting ANSI SQL-92, SQL-99, and SQL-2003, plus OLAP
> extensions) and supports open database connectivity (ODBC) and Java
> database connectivity (JDBC), as well. Most business intelligence,
> data analysis and data visualization tools work with HAWQ out of the
> box without the need for specialized drivers.
>
> A unique aspect of HAWQ is its integration of statistical and machine
> learning capabilities that can be natively invoked from SQL or (in the
> context of PL/Python, PL/Java or PL/R) in massively parallel modes and
> applied to large data sets across a Hadoop cluster. These capabilities
> are provided through MADlib – an existing open source, parallel
> machine-learning library. Given the close ties between the two
> development communities, the MADlib community has expressed interest
> in joining HAWQ on its journey into the ASF Incubator and will be
> submitting a separate, concurrent proposal.
>
> HAWQ will provide more robust and higher performing options for Hadoop
> environments that demand best-in-class data analytics for business
> critical purposes. HAWQ is implemented in C and C++.
>
> HAWQ has a few runtime dependencies licensed under the Cat X list:
>   * gperf (GPL Version 3)
>   * libgsasl (LGPL Version 2.1)
>   * libuuid-2.26 (LGPL Version 2)
> However, given the runtime (dynamic linking) nature of these
> dependencies it doesn't represent a problem for HAWQ to be considered
> an ASF project.
>
> == Proposal ==
> The goal of this proposal is to bring the core of Pivotal Software,
> Inc.’s (Pivotal) Pivotal HAWQⓇ codebase into the Apache Software
> Foundation (ASF) in order to build a vibrant, diverse and
> self-governed open source community around the technology. Pivotal has
> agreed to transfer the brand name "HAWQ" to Apache Software Foundation
> and will stop using HAWQ to refer to this software if the project gets
> accepted into the ASF Incubator under the name of "Apache HAWQ
> (incubating)". Pivotal will continue to market and sell an analytic
> engine product that includes Apache HAWQ (incubating). While HAWQ is
> our primary choice for a name of the project, in anticipation of any
> potential issues with PODLINGNAMESEARCH we have come up with two
> alternative names: (1) Hornet; or (2) Grove.
>
> Pivotal is submitting this proposal to donate the HAWQ source code and
> associated artifacts (documentation, web site content, wiki, etc.) to
> the Apache Software Foundation Incubator under the Apache License,
> Version 2.0 and is asking Incubator PMC to establish an open source
> community.
>
> == Background ==
> While the ecosystem of open source SQL-on-Hadoop solutions is fairly
> developed by now, HAWQ has several unique features that will set it
> apart from existing ASF and non-ASF projects. HAWQ made its debut in
> 2013 as a closed source product leveraging a decade's worth of product
> development effort invested in Greenplum DatabaseⓇ. Since then HAWQ
> has rapidly gained a solid customer base and became available on
> non-Pivotal distributions of Hadoop.
> In 2015 HAWQ still leverages the rock solid foundation of Greenplum
> Database, while at the same time embracing elasticity and resource
> management native to Hadoop applications. This allows HAWQ to provide
> superior SQL on Hadoop performance, scalability and coverage while
> also providing massively-parallel machine learning capabilities and
> support for native Hadoop file formats. In addition, HAWQ's advanced
> features include support for complex joins, rich and compliant SQL
> dialect and industry-differentiating data federation capabilities.
> Dynamic pipelining and pluggable query optimizer architecture enable
> HAWQ to perform queries on Hadoop with the speed and scalability
> required for enterprise data warehouse (EDW) workloads. HAWQ provides
> strong support for low-latency analytic SQL queries, coupled with
> massively parallel machine learning capabilities. 

Re: [VOTE] Accept Horn into the ASF incubator

[John D. Ament]

+1

On Mon, Aug 31, 2015 at 7:13 PM Edward J. Yoon 
wrote:

> Hi folks,
>
> I would like to call a vote to accept Horn, as a new Apache Incubator
> project. The full proposal is available at the end of this mail and as
> a https://wiki.apache.org/incubator/HornProposal (the changes from
> initial discussion draft are addition of 2 committers from cldi-kaist
> team and Rich as a mentor).
>
> The VOTE is open for at least the next 72 hours:
>
> [ ] +1 Accept Horn into the Apache Incubator
> [ ] 0
> [ ] -1 Do not accept Horn into the Apache Incubator bc ..
>
> I'd like to get the voting started w/ my own +1
>
> Thanks!
>
> == Abstract ==
>
> Horn [hɔ:n] (korean meaning of Horn is a "Spirit") is a neuron-centric
> programming APIs and execution framework for large-scale deep
> learning, built on top of Apache Hama.
>
> == Proposal ==
>
> It is a goal of the Horn to provide a neuron-centric programming APIs
> which allows user to easily define the characteristic of artificial
> neural network model and its structure, and its execution framework
> that leverages the heterogeneous resources on Hama and Hadoop YARN
> cluster.
>
> == Background ==
>
> The initial ANN code was developed at Apache Hama project by a
> committer, Yexi Jiang (Facebook) in 2013. The motivation behind this
> work is to build a framework that provides more intuitive programming
> APIs like Google's MapReduce or Pregel and supports applications
> needing large model with huge memory consumptions in distributed way.
>
> == Rationale ==
>
> While many of deep learning open source softwares such as Caffe,
> DeepDist, DL4j, and NeuralGiraph are still data or model parallel
> only, we aim to support both data and model parallelism and also
> fault-tolerant system design. The basic idea of data and model
> parallelism is use of the remote parameter server to parallelize model
> creation and distribute training across machines, and the BSP
> framework of Apache Hama for performing asynchronous mini-batches.
> Within single BSP job, each task group works asynchronously using
> region barrier synchronization instead of global barrier
> synchronization, and trains large-scale neural network model using
> assigned data sets in BSP paradigm. Thus, we achieve data and model
> parallelism. This architecture is inspired by Google's !DistBelief
> (Jeff Dean et al, 2012).
>
> == Initial Goals ==
>
> Some current goals include:
>
>  * builds new community
>  * provides more intuitive programming APIs
>  * needs both data and model parallelism support
>  * must run natively on both Hama and Hadoop2
>  * needs also GPUs and InfiniBand support (FPGAs if possible)
>
> == Current Status ==
>
> === Meritocracy ===
>
> The core developers understand what it means to have a process based
> on meritocracy. We will provide continuous efforts to build an
> environment that supports this, encouraging community members to
> contribute.
>
> === Community ===
>
> A small community has formed within the Apache Hama project community,
> universities, and companies such as deep learning startup, instant
> messenger service company, and mobile manufacturing company. And many
> people are interested in the large-scale deep learning platform
> itself. By bringing Horn into Apache, we believe that the community
> will grow even bigger.
>
> === Core Developers ===
>
> Edward J. Yoon, Thomas Jungblut, Jungin Lee, and Minho Kim
>
> == Known Risks ==
>
> === Orphaned Products ===
>
> Apache Hama is already a core open source component at Samsung
> Electronics, and Horn also will be used by Samsung Electronics and
> Cldi Inc., and so there is no direct risk for this project to be
> orphaned.
>
> === Inexperience with Open Source ===
>
> Some are very new and the others have experience using and/or working
> on Apache open source projects.
>
> === Homogeneous Developers ===
>
> The initial committers are from different organizations such as,
> Microsoft, Samsung Electronics, Seoul National University, Technical
> University of Munich, KAIST, LINE plus, and Cldi Inc.
>
> === Reliance on Salaried Developers ===
>
> Few will be worked as a full-time open source developer. Other
> developers will also start working on the project in their spare time.
>
> === Relationships with Other Apache Products ===
>
>  * Horn is based on Apache Hama
>  * Apache Zookeeper is used for distributed locking service
>  * Natively run on Apache Hadoop and Mesos
>  * Horn can be somewhat overlapped with Singa podling (If possible,
> we'd also like to use Singa or Caffe to do the heavy lifting part).
>
> === An Excessive Fascination with the Apache Brand ===
>
> Horn itself will hopefully have benefits from Apache, in terms of
> attracting a community and establishing a solid group of developers,
> but also the relation with Apache Hadoop, Zookeeper, and Hama. These
> are the main reasons for us to send this proposal.
>
> == Documentation ==
>
> Initial plan about Horn can be found at
> 

Re: [VOTE] Accept Horn into the ASF incubator

[JongYoon Lim]

+1

2015-09-01 9:54 GMT+09:00 John D. Ament :

> +1
>
> On Mon, Aug 31, 2015 at 7:13 PM Edward J. Yoon 
> wrote:
>
> > Hi folks,
> >
> > I would like to call a vote to accept Horn, as a new Apache Incubator
> > project. The full proposal is available at the end of this mail and as
> > a https://wiki.apache.org/incubator/HornProposal (the changes from
> > initial discussion draft are addition of 2 committers from cldi-kaist
> > team and Rich as a mentor).
> >
> > The VOTE is open for at least the next 72 hours:
> >
> > [ ] +1 Accept Horn into the Apache Incubator
> > [ ] 0
> > [ ] -1 Do not accept Horn into the Apache Incubator bc ..
> >
> > I'd like to get the voting started w/ my own +1
> >
> > Thanks!
> >
> > == Abstract ==
> >
> > Horn [hɔ:n] (korean meaning of Horn is a "Spirit") is a neuron-centric
> > programming APIs and execution framework for large-scale deep
> > learning, built on top of Apache Hama.
> >
> > == Proposal ==
> >
> > It is a goal of the Horn to provide a neuron-centric programming APIs
> > which allows user to easily define the characteristic of artificial
> > neural network model and its structure, and its execution framework
> > that leverages the heterogeneous resources on Hama and Hadoop YARN
> > cluster.
> >
> > == Background ==
> >
> > The initial ANN code was developed at Apache Hama project by a
> > committer, Yexi Jiang (Facebook) in 2013. The motivation behind this
> > work is to build a framework that provides more intuitive programming
> > APIs like Google's MapReduce or Pregel and supports applications
> > needing large model with huge memory consumptions in distributed way.
> >
> > == Rationale ==
> >
> > While many of deep learning open source softwares such as Caffe,
> > DeepDist, DL4j, and NeuralGiraph are still data or model parallel
> > only, we aim to support both data and model parallelism and also
> > fault-tolerant system design. The basic idea of data and model
> > parallelism is use of the remote parameter server to parallelize model
> > creation and distribute training across machines, and the BSP
> > framework of Apache Hama for performing asynchronous mini-batches.
> > Within single BSP job, each task group works asynchronously using
> > region barrier synchronization instead of global barrier
> > synchronization, and trains large-scale neural network model using
> > assigned data sets in BSP paradigm. Thus, we achieve data and model
> > parallelism. This architecture is inspired by Google's !DistBelief
> > (Jeff Dean et al, 2012).
> >
> > == Initial Goals ==
> >
> > Some current goals include:
> >
> >  * builds new community
> >  * provides more intuitive programming APIs
> >  * needs both data and model parallelism support
> >  * must run natively on both Hama and Hadoop2
> >  * needs also GPUs and InfiniBand support (FPGAs if possible)
> >
> > == Current Status ==
> >
> > === Meritocracy ===
> >
> > The core developers understand what it means to have a process based
> > on meritocracy. We will provide continuous efforts to build an
> > environment that supports this, encouraging community members to
> > contribute.
> >
> > === Community ===
> >
> > A small community has formed within the Apache Hama project community,
> > universities, and companies such as deep learning startup, instant
> > messenger service company, and mobile manufacturing company. And many
> > people are interested in the large-scale deep learning platform
> > itself. By bringing Horn into Apache, we believe that the community
> > will grow even bigger.
> >
> > === Core Developers ===
> >
> > Edward J. Yoon, Thomas Jungblut, Jungin Lee, and Minho Kim
> >
> > == Known Risks ==
> >
> > === Orphaned Products ===
> >
> > Apache Hama is already a core open source component at Samsung
> > Electronics, and Horn also will be used by Samsung Electronics and
> > Cldi Inc., and so there is no direct risk for this project to be
> > orphaned.
> >
> > === Inexperience with Open Source ===
> >
> > Some are very new and the others have experience using and/or working
> > on Apache open source projects.
> >
> > === Homogeneous Developers ===
> >
> > The initial committers are from different organizations such as,
> > Microsoft, Samsung Electronics, Seoul National University, Technical
> > University of Munich, KAIST, LINE plus, and Cldi Inc.
> >
> > === Reliance on Salaried Developers ===
> >
> > Few will be worked as a full-time open source developer. Other
> > developers will also start working on the project in their spare time.
> >
> > === Relationships with Other Apache Products ===
> >
> >  * Horn is based on Apache Hama
> >  * Apache Zookeeper is used for distributed locking service
> >  * Natively run on Apache Hadoop and Mesos
> >  * Horn can be somewhat overlapped with Singa podling (If possible,
> > we'd also like to use Singa or Caffe to do the heavy lifting part).
> >
> > === An Excessive Fascination with the Apache Brand ===
> >
> > Horn 

Re: [VOTE] Accept HAWQ into the Apache Incubator

[Chris Douglas]

+1 -C

On Mon, Aug 31, 2015 at 11:47 AM, Roman Shaposhnik  wrote:
> Following the discussion earlier:
>http://s.apache.org/Gaf
>
> I would like to call a VOTE for accepting HAWQ
> as a new incubator project.
>
> The proposal is available at:
> https://wiki.apache.org/incubator/HAWQProposal
> and is also included at the bottom of this email.
>
> Vote is open until at least Thu, 3 September 2015, 23:59:00 PST
>
>  [ ] +1 accept HAWQ into the Apache Incubator
>  [ ] ±0
>  [ ] -1 because...
>
> Thanks,
> Roman.
>
> == Abstract ==
>
> HAWQ is an advanced enterprise SQL on Hadoop analytic engine built
> around a robust and high-performance massively-parallel processing
> (MPP) SQL framework evolved from Pivotal Greenplum DatabaseⓇ.
>
> HAWQ runs natively on Apache HadoopⓇ clusters by tightly integrating
> with HDFS and YARN. HAWQ supports multiple Hadoop file formats such as
> Apache Parquet, native HDFS, and Apache Avro. HAWQ is configured and
> managed as a Hadoop service in Apache Ambari. HAWQ is 100% ANSI SQL
> compliant (supporting ANSI SQL-92, SQL-99, and SQL-2003, plus OLAP
> extensions) and supports open database connectivity (ODBC) and Java
> database connectivity (JDBC), as well. Most business intelligence,
> data analysis and data visualization tools work with HAWQ out of the
> box without the need for specialized drivers.
>
> A unique aspect of HAWQ is its integration of statistical and machine
> learning capabilities that can be natively invoked from SQL or (in the
> context of PL/Python, PL/Java or PL/R) in massively parallel modes and
> applied to large data sets across a Hadoop cluster. These capabilities
> are provided through MADlib – an existing open source, parallel
> machine-learning library. Given the close ties between the two
> development communities, the MADlib community has expressed interest
> in joining HAWQ on its journey into the ASF Incubator and will be
> submitting a separate, concurrent proposal.
>
> HAWQ will provide more robust and higher performing options for Hadoop
> environments that demand best-in-class data analytics for business
> critical purposes. HAWQ is implemented in C and C++.
>
> HAWQ has a few runtime dependencies licensed under the Cat X list:
>   * gperf (GPL Version 3)
>   * libgsasl (LGPL Version 2.1)
>   * libuuid-2.26 (LGPL Version 2)
> However, given the runtime (dynamic linking) nature of these
> dependencies it doesn't represent a problem for HAWQ to be considered
> an ASF project.
>
> == Proposal ==
> The goal of this proposal is to bring the core of Pivotal Software,
> Inc.’s (Pivotal) Pivotal HAWQⓇ codebase into the Apache Software
> Foundation (ASF) in order to build a vibrant, diverse and
> self-governed open source community around the technology. Pivotal has
> agreed to transfer the brand name "HAWQ" to Apache Software Foundation
> and will stop using HAWQ to refer to this software if the project gets
> accepted into the ASF Incubator under the name of "Apache HAWQ
> (incubating)". Pivotal will continue to market and sell an analytic
> engine product that includes Apache HAWQ (incubating). While HAWQ is
> our primary choice for a name of the project, in anticipation of any
> potential issues with PODLINGNAMESEARCH we have come up with two
> alternative names: (1) Hornet; or (2) Grove.
>
> Pivotal is submitting this proposal to donate the HAWQ source code and
> associated artifacts (documentation, web site content, wiki, etc.) to
> the Apache Software Foundation Incubator under the Apache License,
> Version 2.0 and is asking Incubator PMC to establish an open source
> community.
>
> == Background ==
> While the ecosystem of open source SQL-on-Hadoop solutions is fairly
> developed by now, HAWQ has several unique features that will set it
> apart from existing ASF and non-ASF projects. HAWQ made its debut in
> 2013 as a closed source product leveraging a decade's worth of product
> development effort invested in Greenplum DatabaseⓇ. Since then HAWQ
> has rapidly gained a solid customer base and became available on
> non-Pivotal distributions of Hadoop.
> In 2015 HAWQ still leverages the rock solid foundation of Greenplum
> Database, while at the same time embracing elasticity and resource
> management native to Hadoop applications. This allows HAWQ to provide
> superior SQL on Hadoop performance, scalability and coverage while
> also providing massively-parallel machine learning capabilities and
> support for native Hadoop file formats. In addition, HAWQ's advanced
> features include support for complex joins, rich and compliant SQL
> dialect and industry-differentiating data federation capabilities.
> Dynamic pipelining and pluggable query optimizer architecture enable
> HAWQ to perform queries on Hadoop with the speed and scalability
> required for enterprise data warehouse (EDW) workloads. HAWQ provides
> strong support for low-latency analytic SQL queries, coupled with
> massively parallel machine learning 

Re: [DISCUSS] HAWQ Incubation Proposal

[Atri Sharma]

If everything is fine, should we call for a vote on proposal?

On Sun, Aug 30, 2015 at 3:06 PM, Bertrand Delacretaz  wrote:

> On Sat, Aug 29, 2015 at 7:54 PM, Justin Erenkrantz
>  wrote:
> > On Fri, Aug 28, 2015 at 7:45 PM, Roman Shaposhnik 
> wrote:
> >> ...With Justin volunteering at this point we've got 6 very active, very
> >> experienced mentors. I really don't think the # of committers should be
> >> a problem.
> >
> > I agree with Roman...
>
> Ok, I'll trust you guys on this then!
>
> -Bertrand
>
> -
> To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org
> For additional commands, e-mail: general-h...@incubator.apache.org
>
>

Re: [VOTE] Accept HAWQ into the Apache Incubator

[Luke Han]

+1 (non-binding)


Best Regards!
-

Luke Han

On Tue, Sep 1, 2015 at 9:41 AM, Chris Douglas  wrote:

> +1 -C
>
> On Mon, Aug 31, 2015 at 11:47 AM, Roman Shaposhnik  wrote:
> > Following the discussion earlier:
> >http://s.apache.org/Gaf
> >
> > I would like to call a VOTE for accepting HAWQ
> > as a new incubator project.
> >
> > The proposal is available at:
> > https://wiki.apache.org/incubator/HAWQProposal
> > and is also included at the bottom of this email.
> >
> > Vote is open until at least Thu, 3 September 2015, 23:59:00 PST
> >
> >  [ ] +1 accept HAWQ into the Apache Incubator
> >  [ ] ±0
> >  [ ] -1 because...
> >
> > Thanks,
> > Roman.
> >
> > == Abstract ==
> >
> > HAWQ is an advanced enterprise SQL on Hadoop analytic engine built
> > around a robust and high-performance massively-parallel processing
> > (MPP) SQL framework evolved from Pivotal Greenplum DatabaseⓇ.
> >
> > HAWQ runs natively on Apache HadoopⓇ clusters by tightly integrating
> > with HDFS and YARN. HAWQ supports multiple Hadoop file formats such as
> > Apache Parquet, native HDFS, and Apache Avro. HAWQ is configured and
> > managed as a Hadoop service in Apache Ambari. HAWQ is 100% ANSI SQL
> > compliant (supporting ANSI SQL-92, SQL-99, and SQL-2003, plus OLAP
> > extensions) and supports open database connectivity (ODBC) and Java
> > database connectivity (JDBC), as well. Most business intelligence,
> > data analysis and data visualization tools work with HAWQ out of the
> > box without the need for specialized drivers.
> >
> > A unique aspect of HAWQ is its integration of statistical and machine
> > learning capabilities that can be natively invoked from SQL or (in the
> > context of PL/Python, PL/Java or PL/R) in massively parallel modes and
> > applied to large data sets across a Hadoop cluster. These capabilities
> > are provided through MADlib – an existing open source, parallel
> > machine-learning library. Given the close ties between the two
> > development communities, the MADlib community has expressed interest
> > in joining HAWQ on its journey into the ASF Incubator and will be
> > submitting a separate, concurrent proposal.
> >
> > HAWQ will provide more robust and higher performing options for Hadoop
> > environments that demand best-in-class data analytics for business
> > critical purposes. HAWQ is implemented in C and C++.
> >
> > HAWQ has a few runtime dependencies licensed under the Cat X list:
> >   * gperf (GPL Version 3)
> >   * libgsasl (LGPL Version 2.1)
> >   * libuuid-2.26 (LGPL Version 2)
> > However, given the runtime (dynamic linking) nature of these
> > dependencies it doesn't represent a problem for HAWQ to be considered
> > an ASF project.
> >
> > == Proposal ==
> > The goal of this proposal is to bring the core of Pivotal Software,
> > Inc.’s (Pivotal) Pivotal HAWQⓇ codebase into the Apache Software
> > Foundation (ASF) in order to build a vibrant, diverse and
> > self-governed open source community around the technology. Pivotal has
> > agreed to transfer the brand name "HAWQ" to Apache Software Foundation
> > and will stop using HAWQ to refer to this software if the project gets
> > accepted into the ASF Incubator under the name of "Apache HAWQ
> > (incubating)". Pivotal will continue to market and sell an analytic
> > engine product that includes Apache HAWQ (incubating). While HAWQ is
> > our primary choice for a name of the project, in anticipation of any
> > potential issues with PODLINGNAMESEARCH we have come up with two
> > alternative names: (1) Hornet; or (2) Grove.
> >
> > Pivotal is submitting this proposal to donate the HAWQ source code and
> > associated artifacts (documentation, web site content, wiki, etc.) to
> > the Apache Software Foundation Incubator under the Apache License,
> > Version 2.0 and is asking Incubator PMC to establish an open source
> > community.
> >
> > == Background ==
> > While the ecosystem of open source SQL-on-Hadoop solutions is fairly
> > developed by now, HAWQ has several unique features that will set it
> > apart from existing ASF and non-ASF projects. HAWQ made its debut in
> > 2013 as a closed source product leveraging a decade's worth of product
> > development effort invested in Greenplum DatabaseⓇ. Since then HAWQ
> > has rapidly gained a solid customer base and became available on
> > non-Pivotal distributions of Hadoop.
> > In 2015 HAWQ still leverages the rock solid foundation of Greenplum
> > Database, while at the same time embracing elasticity and resource
> > management native to Hadoop applications. This allows HAWQ to provide
> > superior SQL on Hadoop performance, scalability and coverage while
> > also providing massively-parallel machine learning capabilities and
> > support for native Hadoop file formats. In addition, HAWQ's advanced
> > features include support for complex joins, rich and compliant SQL
> > dialect and industry-differentiating data federation 

Re: [VOTE] Accept HAWQ into the Apache Incubator

[Don Bosco Durai]

+1 (non-binding)

Bosco

On 8/31/15, 7:55 PM, "Thejas Nair"  wrote:

>+1
>
>On Mon, Aug 31, 2015 at 7:01 PM, Luke Han  wrote:
>> +1 (non-binding)
>>
>>
>> Best Regards!
>> -
>>
>> Luke Han
>>
>> On Tue, Sep 1, 2015 at 9:41 AM, Chris Douglas 
>>wrote:
>>
>>> +1 -C
>>>
>>> On Mon, Aug 31, 2015 at 11:47 AM, Roman Shaposhnik 
>>>wrote:
>>> > Following the discussion earlier:
>>> >http://s.apache.org/Gaf
>>> >
>>> > I would like to call a VOTE for accepting HAWQ
>>> > as a new incubator project.
>>> >
>>> > The proposal is available at:
>>> > https://wiki.apache.org/incubator/HAWQProposal
>>> > and is also included at the bottom of this email.
>>> >
>>> > Vote is open until at least Thu, 3 September 2015, 23:59:00 PST
>>> >
>>> >  [ ] +1 accept HAWQ into the Apache Incubator
>>> >  [ ] ±0
>>> >  [ ] -1 because...
>>> >
>>> > Thanks,
>>> > Roman.
>>> >
>>> > == Abstract ==
>>> >
>>> > HAWQ is an advanced enterprise SQL on Hadoop analytic engine built
>>> > around a robust and high-performance massively-parallel processing
>>> > (MPP) SQL framework evolved from Pivotal Greenplum Database?.
>>> >
>>> > HAWQ runs natively on Apache Hadoop? clusters by tightly integrating
>>> > with HDFS and YARN. HAWQ supports multiple Hadoop file formats such
>>>as
>>> > Apache Parquet, native HDFS, and Apache Avro. HAWQ is configured and
>>> > managed as a Hadoop service in Apache Ambari. HAWQ is 100% ANSI SQL
>>> > compliant (supporting ANSI SQL-92, SQL-99, and SQL-2003, plus OLAP
>>> > extensions) and supports open database connectivity (ODBC) and Java
>>> > database connectivity (JDBC), as well. Most business intelligence,
>>> > data analysis and data visualization tools work with HAWQ out of the
>>> > box without the need for specialized drivers.
>>> >
>>> > A unique aspect of HAWQ is its integration of statistical and machine
>>> > learning capabilities that can be natively invoked from SQL or (in
>>>the
>>> > context of PL/Python, PL/Java or PL/R) in massively parallel modes
>>>and
>>> > applied to large data sets across a Hadoop cluster. These
>>>capabilities
>>> > are provided through MADlib ­ an existing open source, parallel
>>> > machine-learning library. Given the close ties between the two
>>> > development communities, the MADlib community has expressed interest
>>> > in joining HAWQ on its journey into the ASF Incubator and will be
>>> > submitting a separate, concurrent proposal.
>>> >
>>> > HAWQ will provide more robust and higher performing options for
>>>Hadoop
>>> > environments that demand best-in-class data analytics for business
>>> > critical purposes. HAWQ is implemented in C and C++.
>>> >
>>> > HAWQ has a few runtime dependencies licensed under the Cat X list:
>>> >   * gperf (GPL Version 3)
>>> >   * libgsasl (LGPL Version 2.1)
>>> >   * libuuid-2.26 (LGPL Version 2)
>>> > However, given the runtime (dynamic linking) nature of these
>>> > dependencies it doesn't represent a problem for HAWQ to be considered
>>> > an ASF project.
>>> >
>>> > == Proposal ==
>>> > The goal of this proposal is to bring the core of Pivotal Software,
>>> > Inc.’s (Pivotal) Pivotal HAWQ? codebase into the Apache Software
>>> > Foundation (ASF) in order to build a vibrant, diverse and
>>> > self-governed open source community around the technology. Pivotal
>>>has
>>> > agreed to transfer the brand name "HAWQ" to Apache Software
>>>Foundation
>>> > and will stop using HAWQ to refer to this software if the project
>>>gets
>>> > accepted into the ASF Incubator under the name of "Apache HAWQ
>>> > (incubating)". Pivotal will continue to market and sell an analytic
>>> > engine product that includes Apache HAWQ (incubating). While HAWQ is
>>> > our primary choice for a name of the project, in anticipation of any
>>> > potential issues with PODLINGNAMESEARCH we have come up with two
>>> > alternative names: (1) Hornet; or (2) Grove.
>>> >
>>> > Pivotal is submitting this proposal to donate the HAWQ source code
>>>and
>>> > associated artifacts (documentation, web site content, wiki, etc.) to
>>> > the Apache Software Foundation Incubator under the Apache License,
>>> > Version 2.0 and is asking Incubator PMC to establish an open source
>>> > community.
>>> >
>>> > == Background ==
>>> > While the ecosystem of open source SQL-on-Hadoop solutions is fairly
>>> > developed by now, HAWQ has several unique features that will set it
>>> > apart from existing ASF and non-ASF projects. HAWQ made its debut in
>>> > 2013 as a closed source product leveraging a decade's worth of
>>>product
>>> > development effort invested in Greenplum Database?. Since then HAWQ
>>> > has rapidly gained a solid customer base and became available on
>>> > non-Pivotal distributions of Hadoop.
>>> > In 2015 HAWQ still leverages the rock solid foundation of Greenplum
>>> > Database, while at the same time embracing elasticity and resource
>>> > management 

Re: [VOTE] Accept Horn into the ASF incubator

[Tommaso Teofili]

+1

Tommaso

2015-09-01 1:13 GMT+02:00 Edward J. Yoon :

> Hi folks,
>
> I would like to call a vote to accept Horn, as a new Apache Incubator
> project. The full proposal is available at the end of this mail and as
> a https://wiki.apache.org/incubator/HornProposal (the changes from
> initial discussion draft are addition of 2 committers from cldi-kaist
> team and Rich as a mentor).
>
> The VOTE is open for at least the next 72 hours:
>
> [ ] +1 Accept Horn into the Apache Incubator
> [ ] 0
> [ ] -1 Do not accept Horn into the Apache Incubator bc ..
>
> I'd like to get the voting started w/ my own +1
>
> Thanks!
>
> == Abstract ==
>
> Horn [hɔ:n] (korean meaning of Horn is a "Spirit") is a neuron-centric
> programming APIs and execution framework for large-scale deep
> learning, built on top of Apache Hama.
>
> == Proposal ==
>
> It is a goal of the Horn to provide a neuron-centric programming APIs
> which allows user to easily define the characteristic of artificial
> neural network model and its structure, and its execution framework
> that leverages the heterogeneous resources on Hama and Hadoop YARN
> cluster.
>
> == Background ==
>
> The initial ANN code was developed at Apache Hama project by a
> committer, Yexi Jiang (Facebook) in 2013. The motivation behind this
> work is to build a framework that provides more intuitive programming
> APIs like Google's MapReduce or Pregel and supports applications
> needing large model with huge memory consumptions in distributed way.
>
> == Rationale ==
>
> While many of deep learning open source softwares such as Caffe,
> DeepDist, DL4j, and NeuralGiraph are still data or model parallel
> only, we aim to support both data and model parallelism and also
> fault-tolerant system design. The basic idea of data and model
> parallelism is use of the remote parameter server to parallelize model
> creation and distribute training across machines, and the BSP
> framework of Apache Hama for performing asynchronous mini-batches.
> Within single BSP job, each task group works asynchronously using
> region barrier synchronization instead of global barrier
> synchronization, and trains large-scale neural network model using
> assigned data sets in BSP paradigm. Thus, we achieve data and model
> parallelism. This architecture is inspired by Google's !DistBelief
> (Jeff Dean et al, 2012).
>
> == Initial Goals ==
>
> Some current goals include:
>
>  * builds new community
>  * provides more intuitive programming APIs
>  * needs both data and model parallelism support
>  * must run natively on both Hama and Hadoop2
>  * needs also GPUs and InfiniBand support (FPGAs if possible)
>
> == Current Status ==
>
> === Meritocracy ===
>
> The core developers understand what it means to have a process based
> on meritocracy. We will provide continuous efforts to build an
> environment that supports this, encouraging community members to
> contribute.
>
> === Community ===
>
> A small community has formed within the Apache Hama project community,
> universities, and companies such as deep learning startup, instant
> messenger service company, and mobile manufacturing company. And many
> people are interested in the large-scale deep learning platform
> itself. By bringing Horn into Apache, we believe that the community
> will grow even bigger.
>
> === Core Developers ===
>
> Edward J. Yoon, Thomas Jungblut, Jungin Lee, and Minho Kim
>
> == Known Risks ==
>
> === Orphaned Products ===
>
> Apache Hama is already a core open source component at Samsung
> Electronics, and Horn also will be used by Samsung Electronics and
> Cldi Inc., and so there is no direct risk for this project to be
> orphaned.
>
> === Inexperience with Open Source ===
>
> Some are very new and the others have experience using and/or working
> on Apache open source projects.
>
> === Homogeneous Developers ===
>
> The initial committers are from different organizations such as,
> Microsoft, Samsung Electronics, Seoul National University, Technical
> University of Munich, KAIST, LINE plus, and Cldi Inc.
>
> === Reliance on Salaried Developers ===
>
> Few will be worked as a full-time open source developer. Other
> developers will also start working on the project in their spare time.
>
> === Relationships with Other Apache Products ===
>
>  * Horn is based on Apache Hama
>  * Apache Zookeeper is used for distributed locking service
>  * Natively run on Apache Hadoop and Mesos
>  * Horn can be somewhat overlapped with Singa podling (If possible,
> we'd also like to use Singa or Caffe to do the heavy lifting part).
>
> === An Excessive Fascination with the Apache Brand ===
>
> Horn itself will hopefully have benefits from Apache, in terms of
> attracting a community and establishing a solid group of developers,
> but also the relation with Apache Hadoop, Zookeeper, and Hama. These
> are the main reasons for us to send this proposal.
>
> == Documentation ==
>
> Initial plan about Horn can be found at
> 

Re: [VOTE] Accept Horn into the ASF incubator

[moon soo Lee]

+1 (non binding)

On Mon, Aug 31, 2015 at 10:43 PM Atri Sharma  wrote:

> +1 (non binding)
> On 1 Sep 2015 04:43, "Edward J. Yoon"  wrote:
>
> > Hi folks,
> >
> > I would like to call a vote to accept Horn, as a new Apache Incubator
> > project. The full proposal is available at the end of this mail and as
> > a https://wiki.apache.org/incubator/HornProposal (the changes from
> > initial discussion draft are addition of 2 committers from cldi-kaist
> > team and Rich as a mentor).
> >
> > The VOTE is open for at least the next 72 hours:
> >
> > [ ] +1 Accept Horn into the Apache Incubator
> > [ ] 0
> > [ ] -1 Do not accept Horn into the Apache Incubator bc ..
> >
> > I'd like to get the voting started w/ my own +1
> >
> > Thanks!
> >
> > == Abstract ==
> >
> > Horn [hɔ:n] (korean meaning of Horn is a "Spirit") is a neuron-centric
> > programming APIs and execution framework for large-scale deep
> > learning, built on top of Apache Hama.
> >
> > == Proposal ==
> >
> > It is a goal of the Horn to provide a neuron-centric programming APIs
> > which allows user to easily define the characteristic of artificial
> > neural network model and its structure, and its execution framework
> > that leverages the heterogeneous resources on Hama and Hadoop YARN
> > cluster.
> >
> > == Background ==
> >
> > The initial ANN code was developed at Apache Hama project by a
> > committer, Yexi Jiang (Facebook) in 2013. The motivation behind this
> > work is to build a framework that provides more intuitive programming
> > APIs like Google's MapReduce or Pregel and supports applications
> > needing large model with huge memory consumptions in distributed way.
> >
> > == Rationale ==
> >
> > While many of deep learning open source softwares such as Caffe,
> > DeepDist, DL4j, and NeuralGiraph are still data or model parallel
> > only, we aim to support both data and model parallelism and also
> > fault-tolerant system design. The basic idea of data and model
> > parallelism is use of the remote parameter server to parallelize model
> > creation and distribute training across machines, and the BSP
> > framework of Apache Hama for performing asynchronous mini-batches.
> > Within single BSP job, each task group works asynchronously using
> > region barrier synchronization instead of global barrier
> > synchronization, and trains large-scale neural network model using
> > assigned data sets in BSP paradigm. Thus, we achieve data and model
> > parallelism. This architecture is inspired by Google's !DistBelief
> > (Jeff Dean et al, 2012).
> >
> > == Initial Goals ==
> >
> > Some current goals include:
> >
> >  * builds new community
> >  * provides more intuitive programming APIs
> >  * needs both data and model parallelism support
> >  * must run natively on both Hama and Hadoop2
> >  * needs also GPUs and InfiniBand support (FPGAs if possible)
> >
> > == Current Status ==
> >
> > === Meritocracy ===
> >
> > The core developers understand what it means to have a process based
> > on meritocracy. We will provide continuous efforts to build an
> > environment that supports this, encouraging community members to
> > contribute.
> >
> > === Community ===
> >
> > A small community has formed within the Apache Hama project community,
> > universities, and companies such as deep learning startup, instant
> > messenger service company, and mobile manufacturing company. And many
> > people are interested in the large-scale deep learning platform
> > itself. By bringing Horn into Apache, we believe that the community
> > will grow even bigger.
> >
> > === Core Developers ===
> >
> > Edward J. Yoon, Thomas Jungblut, Jungin Lee, and Minho Kim
> >
> > == Known Risks ==
> >
> > === Orphaned Products ===
> >
> > Apache Hama is already a core open source component at Samsung
> > Electronics, and Horn also will be used by Samsung Electronics and
> > Cldi Inc., and so there is no direct risk for this project to be
> > orphaned.
> >
> > === Inexperience with Open Source ===
> >
> > Some are very new and the others have experience using and/or working
> > on Apache open source projects.
> >
> > === Homogeneous Developers ===
> >
> > The initial committers are from different organizations such as,
> > Microsoft, Samsung Electronics, Seoul National University, Technical
> > University of Munich, KAIST, LINE plus, and Cldi Inc.
> >
> > === Reliance on Salaried Developers ===
> >
> > Few will be worked as a full-time open source developer. Other
> > developers will also start working on the project in their spare time.
> >
> > === Relationships with Other Apache Products ===
> >
> >  * Horn is based on Apache Hama
> >  * Apache Zookeeper is used for distributed locking service
> >  * Natively run on Apache Hadoop and Mesos
> >  * Horn can be somewhat overlapped with Singa podling (If possible,
> > we'd also like to use Singa or Caffe to do the heavy lifting part).
> >
> > === An Excessive Fascination with the Apache 

Re: [VOTE] Accept Horn into the ASF incubator

[Atri Sharma]

+1 (non binding)
On 1 Sep 2015 04:43, "Edward J. Yoon"  wrote:

> Hi folks,
>
> I would like to call a vote to accept Horn, as a new Apache Incubator
> project. The full proposal is available at the end of this mail and as
> a https://wiki.apache.org/incubator/HornProposal (the changes from
> initial discussion draft are addition of 2 committers from cldi-kaist
> team and Rich as a mentor).
>
> The VOTE is open for at least the next 72 hours:
>
> [ ] +1 Accept Horn into the Apache Incubator
> [ ] 0
> [ ] -1 Do not accept Horn into the Apache Incubator bc ..
>
> I'd like to get the voting started w/ my own +1
>
> Thanks!
>
> == Abstract ==
>
> Horn [hɔ:n] (korean meaning of Horn is a "Spirit") is a neuron-centric
> programming APIs and execution framework for large-scale deep
> learning, built on top of Apache Hama.
>
> == Proposal ==
>
> It is a goal of the Horn to provide a neuron-centric programming APIs
> which allows user to easily define the characteristic of artificial
> neural network model and its structure, and its execution framework
> that leverages the heterogeneous resources on Hama and Hadoop YARN
> cluster.
>
> == Background ==
>
> The initial ANN code was developed at Apache Hama project by a
> committer, Yexi Jiang (Facebook) in 2013. The motivation behind this
> work is to build a framework that provides more intuitive programming
> APIs like Google's MapReduce or Pregel and supports applications
> needing large model with huge memory consumptions in distributed way.
>
> == Rationale ==
>
> While many of deep learning open source softwares such as Caffe,
> DeepDist, DL4j, and NeuralGiraph are still data or model parallel
> only, we aim to support both data and model parallelism and also
> fault-tolerant system design. The basic idea of data and model
> parallelism is use of the remote parameter server to parallelize model
> creation and distribute training across machines, and the BSP
> framework of Apache Hama for performing asynchronous mini-batches.
> Within single BSP job, each task group works asynchronously using
> region barrier synchronization instead of global barrier
> synchronization, and trains large-scale neural network model using
> assigned data sets in BSP paradigm. Thus, we achieve data and model
> parallelism. This architecture is inspired by Google's !DistBelief
> (Jeff Dean et al, 2012).
>
> == Initial Goals ==
>
> Some current goals include:
>
>  * builds new community
>  * provides more intuitive programming APIs
>  * needs both data and model parallelism support
>  * must run natively on both Hama and Hadoop2
>  * needs also GPUs and InfiniBand support (FPGAs if possible)
>
> == Current Status ==
>
> === Meritocracy ===
>
> The core developers understand what it means to have a process based
> on meritocracy. We will provide continuous efforts to build an
> environment that supports this, encouraging community members to
> contribute.
>
> === Community ===
>
> A small community has formed within the Apache Hama project community,
> universities, and companies such as deep learning startup, instant
> messenger service company, and mobile manufacturing company. And many
> people are interested in the large-scale deep learning platform
> itself. By bringing Horn into Apache, we believe that the community
> will grow even bigger.
>
> === Core Developers ===
>
> Edward J. Yoon, Thomas Jungblut, Jungin Lee, and Minho Kim
>
> == Known Risks ==
>
> === Orphaned Products ===
>
> Apache Hama is already a core open source component at Samsung
> Electronics, and Horn also will be used by Samsung Electronics and
> Cldi Inc., and so there is no direct risk for this project to be
> orphaned.
>
> === Inexperience with Open Source ===
>
> Some are very new and the others have experience using and/or working
> on Apache open source projects.
>
> === Homogeneous Developers ===
>
> The initial committers are from different organizations such as,
> Microsoft, Samsung Electronics, Seoul National University, Technical
> University of Munich, KAIST, LINE plus, and Cldi Inc.
>
> === Reliance on Salaried Developers ===
>
> Few will be worked as a full-time open source developer. Other
> developers will also start working on the project in their spare time.
>
> === Relationships with Other Apache Products ===
>
>  * Horn is based on Apache Hama
>  * Apache Zookeeper is used for distributed locking service
>  * Natively run on Apache Hadoop and Mesos
>  * Horn can be somewhat overlapped with Singa podling (If possible,
> we'd also like to use Singa or Caffe to do the heavy lifting part).
>
> === An Excessive Fascination with the Apache Brand ===
>
> Horn itself will hopefully have benefits from Apache, in terms of
> attracting a community and establishing a solid group of developers,
> but also the relation with Apache Hadoop, Zookeeper, and Hama. These
> are the main reasons for us to send this proposal.
>
> == Documentation ==
>
> Initial plan about Horn can be found 

Incubator PMC/Board report for Sep 2015 ([ppmc])

[Marvin]

Dear podling,

This email was sent by an automated system on behalf of the Apache Incubator 
PMC.
It is an initial reminder to give you plenty of time to prepare your quarterly
board report.

The board meeting is scheduled for Wed, 16 September 2015, 10:30 am PST. The 
report 
for your podling will form a part of the Incubator PMC report. The Incubator 
PMC 
requires your report to be submitted 2 weeks before the board meeting, to allow 
sufficient time for review and submission (Wed, Sep 2nd).

Please submit your report with sufficient time to allow the incubator PMC, and 
subsequently board members to review and digest. Again, the very latest you 
should submit your report is 2 weeks prior to the board meeting.

Thanks,

The Apache Incubator PMC

Submitting your Report
--

Your report should contain the following:

 * Your project name
 * A brief description of your project, which assumes no knowledge of the 
project
   or necessarily of its field
 * A list of the three most important issues to address in the move towards 
   graduation.
 * Any issues that the Incubator PMC or ASF Board might wish/need to be aware of
 * How has the community developed since the last report
 * How has the project developed since the last report.
 
This should be appended to the Incubator Wiki page at:

  http://wiki.apache.org/incubator/September2015

Note: This is manually populated. You may need to wait a little before this page
  is created from a template.

Mentors
---
Mentors should review reports for their project(s) and sign them off on the 
Incubator wiki page. Signing off reports shows that you are following the 
project - projects that are not signed may raise alarms for the Incubator PMC.

Incubator PMC


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Re: [VOTE] Apache Johnzon 0.9.1-incubating release

[Jean-Louis MONTEIRO]

Looks good.
+1 Binding

Le dim. 30 août 2015 à 00:57, Justin Mclean  a écrit :

> Hi,
>
> +1 binding
>
> I checked:
> - signatures and hashes good
> - DISCLAIMER exits
> - LICENSE and NOTICE good
> - No unexpected binary files
> - All source files have headers
> - Can compile from source
>
> Minor thing to consider changing is signing the release with an Apache
> email address.
>
> Thanks,
> Justin
> -
> To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org
> For additional commands, e-mail: general-h...@incubator.apache.org
>
>