incubator-general mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Roman Shaposhnik <...@apache.org>
Subject [VOTE] Accept HAWQ into the Apache Incubator
Date Mon, 31 Aug 2015 18:47:56 GMT
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 thousands of servers are running
mission-critical applications today on HAWQ managing over PBs of data.

== Rationale ==
Hadoop and HDFS-based data management architectures continue their
expansion into the enterprise. As the amount of data stored on Hadoop
clusters grows, unlocking the analytics capabilities and democratizing
access to that treasure trove of data becomes one of the key concerns.
While Hadoop has no shortage of purposefully designed analytical
frameworks, the easiest and most cost-effective way to onboard the
largest amount of data consumers is provided by offering SQL APIs for
data retrieval at scale. Of course, given the high velocity of
innovation happening in the underlying Hadoop ecosystem, any
SQL-on-Hadoop solution has to keep up with the community. We strongly
believe that in the Big Data space, this can be optimally achieved
through a vibrant, diverse, self-governed community collectively
innovating around a single codebase while at the same time
cross-pollinating with various other data management communities.
Apache Software Foundation is the ideal place to meet those ambitious
goals. We also believe that our initial experience of bringing Pivotal
GemfireⓇ into ASF as Apache Geode (incubating) could be leveraged thus
improving the chances of HAWQ becoming a vibrant Apache community.

== Initial Goals ==
Our initial goals are to bring HAWQ into the ASF, transition internal
engineering processes into the open, and foster a collaborative
development model according to the "Apache Way." Pivotal and its
partners plan to develop new functionality in an open,
community-driven way. To get there, the existing internal build, test
and release processes will be refactored to support open development.

== Current Status ==
Currently, the project code base is commercially licensed and is not
available to the general public. The documentation and wiki pages are
available at FIXME. Although Pivotal HAWQ was developed as a
proprietary, closed-source product, its roots are in the PostgreSQL
community and the internal engineering practices adopted by the
development team lend themselves well to an open, collaborative and
meritocratic environment.

The Pivotal HAWQ team has always focused on building a robust end user
community of paying and non-paying customers. The existing
documentation along with StackOverflow and other similar forums are
expected to facilitate conversions between our existing users so as to
transform them into an active community of HAWQ members, stakeholders
and developers.

=== Meritocracy ===
Our proposed list of initial committers include the current HAWQ R&D
team, Pivotal Field Engineers, and several existing partners. This
group will form a base for the broader community we will invite to
collaborate on the codebase. We intend to radically expand the initial
developer and user community by running the project in accordance with
the "Apache Way". Users and new contributors will be treated with
respect and welcomed. By participating in the community and providing
quality patches/support that move the project forward, contributors
will earn merit. They also will be encouraged to provide non-code
contributions (documentation, events, community management, etc.) and
will gain merit for doing so. Those with a proven support and quality
track record will be encouraged to become committers.

=== Community ===
If HAWQ is accepted for incubation, the primary initial goal will be
transitioning the core community towards embracing the Apache Way of
project governance. We would solicit major existing contributors to
become committers on the project from the start.

=== Core Developers ===

A few of HAWQ's core developers are skilled in working as part of
openly governed Apache communities (mainly around Hadoop ecosystem).
That said, most of the core developers are currently NOT affiliated
with the ASF and would require new ICLAs before committing to the
project.

=== Alignment ===
The following existing ASF projects can be considered when reviewing
HAWQ proposal:

Apache Hadoop is a distributed storage and processing framework for
very large datasets, focusing primarily on batch processing for
analytic purposes. HAWQ builds on top of two key pieces of Hadoop:
YARN and HDFS. HAWQ's community roadmap includes plans for
contributing Hadoop around HDFS features and increasing support for C
and C++ clients.

Apache Spark™ is a fast engine for processing large datasets,
typically from a Hadoop cluster, and performing batch, streaming,
interactive, or machine learning workloads.  Recently, Apache Spark
has embraced SQL-like APIs around DataFrames at its core. Because of
that we would expect a level of collaboration between the two projects
when it comes to query optimization and exposing HAWQ tables to Spark
analytical pipelines.

Apache Hive™ is a data warehouse software that facilitates querying
and managing large datasets residing in distributed storage. Hive
provides a mechanism to project structure onto this data and query the
data using a SQL-like language called HiveQL. Hive is also providing
HCatalog capabilities as table and storage management layer for
Hadoop, enabling users with different data processing tools to more
easily define structure for the data on the grid. Currently the core
Hive and HAWQ are viewed as complimentary solutions, but we expect
close integration with HCatalog given its dominant position for
metadata management on the Hadoop clusters.

Apache Phoenix is a high performance relational database layer over
HBase for low latency applications. Given Phoenix's exclusive focus on
HBase for its data management backend and its overall architecture
around HBase's co-processors, it is unlikely that there will be much
collaboration between the two projects.

== Known Risks ==
Development has been sponsored mostly by a single company (or its
predecessors) thus far and coordinated mainly by the core Pivotal HAWQ
team.

For the project to fully transition to the Apache Way governance
model, development must shift towards the meritocracy-centric model of
growing a community of contributors balanced with the needs for
extreme stability and core implementation coherency.

The tools and development practices in place for the Pivotal HAWQ
product are compatible with the ASF infrastructure and thus we do not
anticipate any on-boarding pains.

The project currently includes a modified version of PostgreSQL 8.3
source code. Given the ASF's position that the PostgreSQL License is
compatible with the Apache License version 2.0, we do NOT anticipate
any issues with licensing the code base. However, any new capabilities
developed by the HAWQ team once part of the ASF would need to be
consumed by the PostgreSQL community under the Apache License version
2.0.

=== Orphaned products ===
Pivotal is fully committed to maintaining its position as one of the
leading providers of SQL-on-Hadoop solutions and the corresponding
Pivotal commercial product will continue to be based on the HAWQ
project. Moreover, Pivotal has a vested interest in making HAWQ
successful by driving its close integration with both existing
projects contributed by Pivotal including Apache Geode (incubating)
and MADlib (which is requesting Incubation), and sister ASF projects.
We expect this to further reduces the risk of orphaning the product.

=== Inexperience with Open Source ===
Pivotal has embraced open source software since its formation by
employing contributors/committers and by shepherding open source
projects like Cloud Foundry, Spring, RabbitMQ and MADlib. Individuals
working at Pivotal have experience with the formation of vibrant
communities around open technologies with the Cloud Foundry
Foundation, and continuing with the creation of a community around
Apache Geode (incubating).  Although some of the initial committers
have not had the experience of developing entirely open source,
community-driven projects, we expect to bring to bear the open
development practices that have proven successful on longstanding
Pivotal open source projects to the HAWQ community.  Additionally,
several ASF veterans have agreed to mentor the project and are listed
in this proposal. The project will rely on their collective guidance
and wisdom to quickly transition the entire team of initial committers
towards practicing the Apache Way.

=== Homogeneous Developers ===
While most of the initial committers are employed by Pivotal, we have
already seen a healthy level of interest from existing customers and
partners. We intend to convert that interest directly into
participation and will be investing in activities to recruit
additional committers from other companies.

=== Reliance on Salaried Developers ===
Most of the contributors are paid to work in the Big Data space. While
they might wander from their current employers, they are unlikely to
venture far from their core expertise and thus will continue to be
engaged with the project regardless of their current employers.

=== Relationships with Other Apache Products ===
As mentioned in the Alignment section, HAWQ may consider various
degrees of integration and code exchange with Apache Hadoop, Apache
Spark and Apache Hive projects. We expect integration points to be
inside and outside the project. We look forward to collaborating with
these communities as well as other communities under the Apache
umbrella.

=== An Excessive Fascination with the Apache Brand ===
While we intend to leverage the Apache ‘branding’ when talking to
other projects as testament of our project’s ‘neutrality’, we have no
plans for making use of Apache brand in press releases nor posting
billboards advertising acceptance of HAWQ into Apache Incubator.

== Documentation ==
The documentation is currently available at http://hawq.docs.pivotal.io/

== Initial Source ==
Initial source code will be available immediately after Incubator PMC
approves HAWQ joining the Incubator and will be licensed under the
Apache License v2.

== Source and Intellectual Property Submission Plan ==
As soon as HAWQ is approved to join the Incubator, the source code
will be transitioned via an exhibit to Pivotal's current Software
Grant Agreement onto ASF infrastructure and in turn made available
under the Apache License, version 2.0.  We know of no legal
encumberments that would inhibit the transfer of source code to the
ASF.

== External Dependencies ==

Runtime dependencies:
  * gimli (BSD)
  * openldap (The OpenLDAP Public License)
  * openssl (OpenSSL License and the Original SSLeay License, BSD style)
  * proj (MIT)
  * yaml (Creative Commons Attribution 2.0 License)
  * python (Python Software Foundation License Version 2)
  * apr-util (Apache Version 2.0)
  * bzip2 (BSD-style License)
  * curl (MIT/X Derivate License)
  * gperf (GPL Version 3)
  * protobuf (Google)
  * libevent (BSD)
  * json-c (https://github.com/json-c/json-c/blob/master/COPYING)
  * krb5 (MIT)
  * pcre (BSD)
  * libedit (BSD)
  * libxml2 (MIT)
  * zlib (Permissive Free Software License)
  * libgsasl (LGPL Version 2.1)
  * thrift (Apache Version 2.0)
  * snappy (Apache Version 2.0 (up to 1.0.1)/New BSD)
  * libuuid-2.26 (LGPL Version 2)
  * apache hadoop (Apache Version 2.0)
  * apache avro (Apache Version 2.0)
  * glog (BSD)
  * googlemock (BSD)

Build only dependencies:
  * ant (Apache Version 2.0)
  * maven (Apache Version 2.0)
  * cmake (BSD)

Test only dependencies:
  * googletest (BSD)

Cryptography N/A

== Required Resources ==

=== Mailing lists ===
  * private@hawq.incubator.apache.org (moderated subscriptions)
  * commits@hawq.incubator.apache.org
  * dev@hawq.incubator.apache.org
  * issues@hawq.incubator.apache.org
  * user@hawq.incubator.apache.org

=== Git Repository ===
https://git-wip-us.apache.org/repos/asf/incubator-hawq.git

=== Issue Tracking ===
JIRA Project HAWQ (HAWQ)

=== Other Resources ===

Means of setting up regular builds for HAWQ on builds.apache.org will
require integration with Docker support.

== Initial Committers ==
  * Lirong Jian
  * Hubert Huan Zhang
  * Radar Da Lei
  * Ivan Yanqing Weng
  * Zhanwei Wang
  * Yi Jin
  * Lili Ma
  * Jiali Yao
  * Zhenglin Tao
  * Ruilong Huo
  * Ming Li
  * Wen Lin
  * Lei Chang
  * Alexander V Denissov
  * Newton Alex
  * Oleksandr Diachenko
  * Jun Aoki
  * Bhuvnesh Chaudhary
  * Vineet Goel
  * Shivram Mani
  * Noa Horn
  * Sujeet S Varakhedi
  * Junwei (Jimmy) Da
  * Ting (Goden) Yao
  * Mohammad F (Foyzur) Rahman
  * Entong Shen
  * George C Caragea
  * Amr El-Helw
  * Mohamed F Soliman
  * Venkatesh (Venky) Raghavan
  * Carlos Garcia
  * Zixi (Jesse) Zhang
  * Michael P Schubert
  * C.J. Jameson
  * Jacob Frank
  * Ben Calegari
  * Shoabe Shariff
  * Rob Day-Reynolds
  * Mel S Kiyama
  * Charles Alan Litzell
  * David Yozie
  * Ed Espino
  * Caleb Welton
  * Parham Parvizi
  * Dan Baskette
  * Christian Tzolov
  * Tushar Pednekar
  * Greg Chase
  * Chloe Jackson
  * Michael Nixon
  * Roman Shaposhnik
  * Alan Gates
  * Owen O'Malley
  * Thejas Nair
  * Don Bosco Durai
  * Konstantin Boudnik
  * Sergey Soldatov
  * Atri Sharma

== Affiliations ==
  * Barclays:  Atri Sharma
  * Bloomberg: Justin Erenkrantz
  * Hortonworks: Alan Gates, Owen O'Malley, Thejas Nair, Don Bosco Durai
  * WANDisco: Konstantin Boudnik, Sergey Soldatov
  * Pivotal: everyone else on this proposal

== Sponsors ==

=== Champion ===
Roman Shaposhnik

=== Nominated Mentors ===

The initial mentors are listed below:
  * Alan Gates - Apache Member, Hortonworks
  * Owen O'Malley - Apache Member, Hortonworks
  * Thejas Nair - Apache Member, Hortonworks
  * Konstantin Boudnik - Apache Member, WANDisco
  * Roman Shaposhnik - Apache Member, Pivotal
  * Justin Erenkrantz - Apache Member, Bloomberg

=== Sponsoring Entity ===
We would like to propose Apache incubator to sponsor this project.

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


Mime
View raw message