Timeline

Wed July 03	Podling reports due by end of day
Sun July 07	Shepherd reviews due by end of day
Sun July 07	Summary due by end of day
Tue July 09	Mentor signoff due by end of day
Wed July 10	Report submitted to Board
Wed July 17	Board meeting

Shepherd Assignments

Dave Fisher	Livy
Dave Fisher	TVM
Drew Farris	MXNet
Drew Farris	Milagro
Justin Mclean	Tuweni
P. Taylor Goetz	Amaterasu
P. Taylor Goetz	DataSketches
P. Taylor Goetz	Gobblin
Timothy Chen	BRPC
Timothy Chen	BatchEE
Timothy Chen	DLab
	Annotator
	Flagon
	Hudi
	Iceberg
	Rya
	Weex

Incubator PMC report for July 2019

The Apache Incubator is the entry path into the ASF for projects and codebases wishing to become part of the Foundation's efforts.

TODO add arrative

Podlings that failed to report, expected next month

Graduations

list podling here

The board has motions for the following:

Your podling here?

Releases

The following releases entered distribution during the month of June:

Credits

Table of Contents Amaterasu Annotator BatchEE BRPC DataSketches DLab Flagon Gobblin Hudi Iceberg Livy Milagro MXNet Rya Tuweni TVM Weex

Amaterasu

Apache Amaterasu is a framework providing continuous deployment for Big Data pipelines.

Amaterasu has been incubating since 2017-09-07.

Three most important unfinished issues to address before graduating:

Are there any issues that the IPMC or ASF Board need to be aware of?

How has the community developed since the last report?

How has the project developed since the last report?

How would you assess the podling's maturity?

Please feel free to add your own commentary.

Initial setup
Working towards first release
Community building
Nearing graduation
Other:

When were the last committers or PPMC members elected?

Have your mentors been helpful and responsive?

Are things falling through the cracks? If so, please list any open issues that need to be addressed.

Signed-off-by:

(amaterasu) Jean-Baptiste Onofré Comments:
(amaterasu) Olivier Lamy Comments:
(amaterasu) Davor Bonaci Comments:

Annotator

Annotator provides annotation enabling code for browsers, servers, and humans.

Annotator has been incubating since 2016-08-30.

Three most important unfinished issues to address before graduating:

Are there any issues that the IPMC or ASF Board need to be aware of?

How has the community developed since the last report?

How has the project developed since the last report?

How would you assess the podling's maturity?

Please feel free to add your own commentary.

Initial setup
Working towards first release
Community building
Nearing graduation
Other:

When were the last committers or PPMC members elected?

Have your mentors been helpful and responsive?

Are things falling through the cracks? If so, please list any open issues that need to be addressed.

Signed-off-by:

(annotator) Nick Kew Comments:
(annotator) Steve Blackmon Comments:
(annotator) Tommaso Teofili Comments:

BatchEE

BatchEE projects aims to provide a JBatch implementation (aka JSR352) and a set of useful extensions for this specification.

BatchEE has been incubating since 2013-10-03.

Three most important unfinished issues to address before graduating:

Are there any issues that the IPMC or ASF Board need to be aware of?

How has the community developed since the last report?

Not much and we agreed to move the project under geronimo responsability to exit the incubator.

How has the project developed since the last report?

How would you assess the podling's maturity?

Please feel free to add your own commentary.

Initial setup
Working towards first release
Community building
Nearing graduation
Other: exiting the incubator as a subproject of Apache Geronimo.

When were the last committers or PPMC members elected?

2019-24-01

Have your mentors been helpful and responsive?

Are things falling through the cracks? If so, please list any open issues that need to be addressed.

Signed-off-by:

(batchee) Jean-Baptiste Onofré Comments:
(batchee) Olivier Lamy Comments:
(batchee) Mark Struberg Comments:

BRPC

brpc is an industrial-grade RPC framework for building reliable and high- performance services.

BRPC has been incubating since 2018-11-13.

Three most important unfinished issues to address before graduating:

Check all third-party dependency, and remove unused NSPR files
update all source files to add unify header
plan to have a offline forum on Shanghai to prompt brpc

Are there any issues that the IPMC or ASF Board need to be aware of?

No

How has the community developed since the last report?

It is very near to its first apache release.

How has the project developed since the last report?

We have made a large progress toward apache release, and planed a forum to attract more users.

How would you assess the podling's maturity?

Please feel free to add your own commentary.

Initial setup
Working towards first release
Community building
Nearing graduation
Other:

Date of last release:

Still working on the first release

When were the last committers or PPMC members elected?

Have your mentors been helpful and responsive?

Are things falling through the cracks? If so, please list any open issues that need to be addressed.

Signed-off-by:

(brpc) Kevin A. McGrail Comments:
(brpc) Jean-Baptiste Onofré Comments:
(brpc) Von Gosling Comments:

DataSketches is an open source, high-performance library of stochastic streaming algorithms commonly called "sketches" in the data sciences. Sketches are small, stateful programs that process massive data as a stream and can provide approximate answers, with mathematical guarantees, to computationally difficult queries orders-of-magnitude faster than traditional, exact methods.

DataSketches has been incubating since 2019-03-30.

Three most important unfinished issues to address before graduating:

Complete a successful 1st release of Memory repo to DIST and Nexus. This is a blocking issue.
Finish refactoring/releasing the other repos, which depend on #1.
Move, refactor Website.

Are there any issues that the IPMC or ASF Board need to be aware of?

As a newbie podling, my experience so far has been exasperating. Finding how to accomplish key tasks is difficult. The information is spread all over and seems to always be couched in language written by lawyers not developers. As a result the essential details are often missing.

I have run into multiple roadblocks, especially with regards to permissions.
I have to keep filing new tickets with INFRA to setup access to infrastructure that should have all been automatically setup once we were accepted as a podling.

How has the community developed since the last report?

Not much. I wish I could spend more time on this, but I can't get off first-base getting the migration done.

How has the project developed since the last report?

We continue to evolve the project's functionality with commits to our GitHub repos.

How would you assess the podling's maturity?

Please feel free to add your own commentary.

Initial setup
Working towards first release
Community building
Nearing graduation
Other:

Date of last release:

No releases yet.

When were the last committers or PPMC members elected?

At the initial incubation date.

Have your mentors been helpful and responsive?

Are things falling through the cracks? If so, please list any open issues that need to be addressed.

I have open INFRA issues that have not yet been addressed and there will be more to come.
I could REALLY use some 1:1 help from an experienced release engineer (perhaps from another project), that is very familiar with the Apache/Maven release process and POM to get us off the ground. Once we have created our first release, we can continue from there. But getting this first one is out is turning out to be quite a challenge. I don't think we need more than an hour with an experienced Apache release engineer, our project just isn't that complicated.

Signed-off-by:

(datasketches) Liang Chen Comments:
(datasketches) Kenneth Knowles Comments:
(datasketches) Furkan Kamaci Comments:

IPMC/Shepherd notes:

DLab

DLab is a platform for creating self-service, exploratory data science environments in the cloud using best-of-breed data science tools.

DLab has been incubating since 2018-08-20.

Three most important unfinished issues to address before graduating:

Are there any issues that the IPMC or ASF Board need to be aware of?

How has the community developed since the last report?

How has the project developed since the last report?

How would you assess the podling's maturity?

Please feel free to add your own commentary.

Initial setup
Working towards first release
Community building
Nearing graduation
Other:

Date of last release:

XXXX-XX-XX

When were the last committers or PPMC members elected?

Have your mentors been helpful and responsive?

Are things falling through the cracks? If so, please list any open issues that need to be addressed.

Signed-off-by:

(dlab) P. Taylor Goetz Comments:
(dlab) Henry Saputra Comments:
(dlab) Konstantin I Boudnik Comments:

IPMC/Shepherd notes:

Flagon

Flagon is a software tool usability testing platform

Flagon has been incubating since 2016-07-13.

Three most important unfinished issues to address before graduating:

Are there any issues that the IPMC or ASF Board need to be aware of?

How has the community developed since the last report?

How has the project developed since the last report?

How would you assess the podling's maturity?

Please feel free to add your own commentary.

Initial setup
Working towards first release
Community building
Nearing graduation
Other:

Date of last release:

XXXX-XX-XX

When were the last committers or PPMC members elected?

Have your mentors been helpful and responsive?

Are things falling through the cracks? If so, please list any open issues that need to be addressed.

Signed-off-by:

(flagon) Lewis John McGibbney Comments:
(flagon) David Meikle Comments:
(flagon) Atri Sharma Comments:

IPMC/Shepherd notes:

Gobblin

Gobblin is a distributed data integration framework that simplifies common aspects of big data integration such as data ingestion, replication, organization and lifecycle management for both streaming and batch data ecosystems.

Gobblin has been incubating since 2017-02-23.

Three most important unfinished issues to address before graduating:

Are there any issues that the IPMC or ASF Board need to be aware of?

How has the community developed since the last report?

How has the project developed since the last report?

How would you assess the podling's maturity?

Please feel free to add your own commentary.

Initial setup
Working towards first release
Community building
Nearing graduation
Other:

Date of last release:

XXXX-XX-XX

When were the last committers or PPMC members elected?

Have your mentors been helpful and responsive?

Are things falling through the cracks? If so, please list any open issues that need to be addressed.

Signed-off-by:

(gobblin) Jean-Baptiste Onofre Comments:
(gobblin) Olivier Lamy Comments:
(gobblin) Jim Jagielski Comments:

IPMC/Shepherd notes:

Hudi

Hudi provides atomic upserts and incremental data streams on Big Data

Hudi has been incubating since 2019-01-17.

Three most important unfinished issues to address before graduating:

Making sufficient number of releases in the Apache way
Legal/IP Clearance of software artifacts (LEGAL-461)
Growing community further by grooming contributors to committers

Are there any issues that the IPMC or ASF Board need to be aware of?

PODLINGNAMESEARCH-162 has been completed. But not reflected on whimsy
Software grant has been signed by Uber. But not reflected on whimsy

How has the community developed since the last report?

Mailing list subs grown to >50, 65 new mailing list threads
Slack is about 99 signups total (20-30 WAU), 39 total contributors on github, ~25 support issues closed on GitHub
3 new organizations reported usage onto the Hudi site

How has the project developed since the last report?

~66 commits from ~15 contributors/committers, across 2 releases
All development now happening on ASF infrastructure, with source code being prepared for ASF release
External talks on DataCouncil SF19 and SF BigAnalytics Meetup

How would you assess the podling's maturity?

Please feel free to add your own commentary.

Initial setup
Working towards first release
Community building
Nearing graduation
Other:

Date of last release:

N/A

When were the last committers or PPMC members elected?

During inception into incubator

Have your mentors been helpful and responsive?

Are things falling through the cracks? If so, please list any open issues that need to be addressed.

Signed-off-by:

(hudi) Thomas Weise Comments:
(hudi) Luciano Resende Comments:
(hudi) Kishore Gopalakrishnan Comments:
(hudi) Suneel Marthi Comments:

IPMC/Shepherd notes:

Iceberg

Iceberg is a table format for large, slow-moving tabular data.

Iceberg has been incubating since 2018-11-16.

Three most important unfinished issues to address before graduating:

Are there any issues that the IPMC or ASF Board need to be aware of?

How has the community developed since the last report?

How has the project developed since the last report?

How would you assess the podling's maturity?

Please feel free to add your own commentary.

Initial setup
Working towards first release
Community building
Nearing graduation
Other:

Date of last release:

XXXX-XX-XX

When were the last committers or PPMC members elected?

Have your mentors been helpful and responsive?

Are things falling through the cracks? If so, please list any open issues that need to be addressed.

Signed-off-by:

(iceberg) Ryan Blue Comments:
(iceberg) Julien Le Dem Comments:
(iceberg) Owen O'Malley Comments:
(iceberg) James Taylor Comments:
(iceberg) Carl Steinbach Comments:

IPMC/Shepherd notes:

Livy

Livy is web service that exposes a REST interface for managing long running Apache Spark contexts in your cluster. With Livy, new applications can be built on top of Apache Spark that require fine grained interaction with many Spark contexts.

Livy has been incubating since 2017-06-05.

Three most important unfinished issues to address before graduating:

Are there any issues that the IPMC or ASF Board need to be aware of?

How has the community developed since the last report?

How has the project developed since the last report?

How would you assess the podling's maturity?

Please feel free to add your own commentary.

Initial setup
Working towards first release
Community building
Nearing graduation
Other:

Date of last release:

XXXX-XX-XX

When were the last committers or PPMC members elected?

Have your mentors been helpful and responsive?

Are things falling through the cracks? If so, please list any open issues that need to be addressed.

Signed-off-by:

(livy) Bikas Saha Comments:
(livy) Brock Noland Comments:
(livy) Luciano Resende Comments:
(livy) Jean-Baptiste Onofre Comments:

IPMC/Shepherd notes:

Milagro

Milagro is core security infrastructure and crypto libraries for decentralized networks and distributed systems.

Milagro has been incubating since 2015-12-21.

Three most important unfinished issues to address before graduating:

Are there any issues that the IPMC or ASF Board need to be aware of?

How has the community developed since the last report?

How has the project developed since the last report?

How would you assess the podling's maturity?

Please feel free to add your own commentary.

Initial setup
Working towards first release
Community building
Nearing graduation
Other:

Date of last release:

XXXX-XX-XX

When were the last committers or PPMC members elected?

Have your mentors been helpful and responsive?

Are things falling through the cracks? If so, please list any open issues that need to be addressed.

Signed-off-by:

(milagro) Nick Kew Comments:
(milagro) Jean-Frederic Clere Comments:

IPMC/Shepherd notes:

MXNet

A Flexible and Efficient Library for Deep Learning

MXNet has been incubating since 2017-01-23.

Three most important unfinished issues to address before graduating:

Increase diversity in contributors, committers, and PMC members — NEAR COMPLETION.
Identify remaining ICLAs or SGAs that need signing – NEAR COMPLETION.
Revisit Apache Maturity Model Assessment — TODO.

Are there any issues that the IPMC or ASF Board need to be aware of?

Based on usability feedback from users, community has started a redesign of the website.

How has the community developed since the last report?

The number of GitHub contributors increased to currently 707 (2019-06-24; +3.7% since last report)
- Active discussions on user forums
  - https://discuss.mxnet.io/ (English, 1.8K registered users and 9.4K posts (+68% since last report))
  - https://discuss.gluon.ai/ (Chinese, 6.5K registered users and 37K posts(+93% since last report))
- Active blogs and social media presence
  - Medium (https://medium.com/apache-mxnet) w/ 1.4k followers
  - Twitter account (https://twitter.com/ApacheMXNet) w/ 2.1k followers
  - Meetup group (https://www.meetup.com/pro/deep-learning-with-apache-mxnet/) w/ 10 groups in 8 countries, 2141 members
  - (in China) Zhihu w/ 7.6k followers, WeChat official account w/ 4.2k followers. (+40% since last report)
Active video channels
- YouTube channel (https://www.youtube.com/apachemxnet) w/ 709 subscriber (+13% since last report)
- Chinese YouTube channel (https://www.youtube.com/channel/UCjeLwTKPMlDt2segkZzw2ZQ) w/ 4.4k subscribers
- (in China) bilibili space (https://space.bilibili.com/209599371) w/ 15k subscriber (+15% since last report)
Highlights in MXNet ecosystem
- MXNet Gluon book published (https://zh.d2l.ai/) first 21.5k hard copies
- MXNet Gluon book (www.d2l.ai, Dive into Deep Learning/D2L) released
  - v1.0.0-rc0 (https://github.com/d2l-ai/d2l-zh/releases/tag/v1.0.0-rc0) in Chinese
  - v0.6.0 (https://github.com/d2l-ai/d2l-en/releases/tag/v0.6.0) in English
- Dive into Deep Learning has 47.5K 28-day active users, and has attracted 11.5K stars & 200+ contributors on GitHub. It has been adopted as a textbook or reference book by 15+ universities in U.S., China, Spain, and Australia, such as UC Berkeley.
- GluonCV v0.4.0 release (https://github.com/dmlc/gluon-cv/releases/tag/v0.4.0)
- GluonNLP v0.6.0 release (https://github.com/dmlc/gluon-nlp/releases/tag/v0.6.0)
- GluonTS v0.1.4 release (https://github.com/awslabs/gluon-ts/releases/tag/v0.1.4) This is a new toolkit for deep-learning based time-series modeling.
- MXNet Model Server v1.0.4 release (https://github.com/awslabs/mxnet-model-server/releases/tag/v1.0.4)
- GluonFace (https://github.com/THUFutureLab/gluon-face)
- DeepInsight (https://github.com/deepinsight/insightface)

How has the project developed since the last report?

1.4.1 patch release: https://github.com/apache/incubator-mxnet/releases/tag/1.4.1
1.5.0 release in progress (pre-release v1.5.0.rc1): https://github.com/apache/incubator-mxnet/releases/tag/1.5.0.rc1 with over 750 patches of new features, improvements, and fixes.
Roadmap discussion on 2.0 in progress https://github.com/apache/incubator-mxnet/issues/9686
Code donation from dmlc/mshadow in progress.
Many ongoing projects:
- numpy-compatbile deep learning: https://github.com/apache/incubator-mxnet/projects/14;
- CPU performance and quantization: https://github.com/apache/incubator-mxnet/projects/15;
- Mixed precision GPU training (AMP): https://github.com/apache/incubator-mxnet/pull/14173, etc.
Github statistics of last month:

May 24, 2019 – June 24, 2019: Excluding merges, 16 authors have pushed 88 commits to master and 140 commits to all branches. On master, 250 files have changed and there have been 12,939 additions and 9,919 deletions.

How would you assess the podling's maturity?

Please feel free to add your own commentary.

Initial setup
Working towards first release
Community building
Nearing graduation
Other:

Date of last release:

2019-04-29

When were the last committers or PPMC members elected?

2019-05-20

Have your mentors been helpful and responsive?

Are things falling through the cracks? If so, please list any open issues that need to be addressed.

Mentors have been providing helps per requests from community.

Signed-off-by:

(mxnet) Henri Yandell Comments:
(mxnet) Markus Weimer Comments:
(mxnet) Michael Wall Comments:
(mxnet) Bob Paulin Comments:
(mxnet) Jason Dai Comments:

IPMC/Shepherd notes:

Rya

Rya (pronounced "ree-uh" /rēə/) is a cloud-based RDF triple store that supports SPARQL queries. Rya is a scalable RDF data management system built on top of Accumulo. Rya uses novel storage methods, indexing schemes, and query processing techniques that scale to billions of triples across multiple nodes. Rya provides fast and easy access to the data through SPARQL, a conventional query mechanism for RDF data.

Rya has been incubating since 2015-09-18.

Three most important unfinished issues to address before graduating:

Are there any issues that the IPMC or ASF Board need to be aware of?

How has the community developed since the last report?

How has the project developed since the last report?

How would you assess the podling's maturity?

Please feel free to add your own commentary.

Initial setup
Working towards first release
Community building
Nearing graduation
Other:

Date of last release:

XXXX-XX-XX

When were the last committers or PPMC members elected?

Have your mentors been helpful and responsive?

Are things falling through the cracks? If so, please list any open issues that need to be addressed.

Signed-off-by:

(rya) Josh Elser Comments:
(rya) Billie Rinaldi Comments:

IPMC/Shepherd notes:

Tuweni

Tuweni is a set of libraries and other tools to aid development of blockchain and other decentralized software in Java and other JVM languages.

Tuweni has been incubating since 2019-03-25.

Three most important unfinished issues to address before graduating:

Are there any issues that the IPMC or ASF Board need to be aware of?

How has the community developed since the last report?

How has the project developed since the last report?

How would you assess the podling's maturity?

Please feel free to add your own commentary.

Initial setup
Working towards first release
Community building
Nearing graduation
Other:

Date of last release:

XXXX-XX-XX

When were the last committers or PPMC members elected?

Have your mentors been helpful and responsive?

Are things falling through the cracks? If so, please list any open issues that need to be addressed.

Signed-off-by:

(tuweni) Jim Jagielski Comments:
(tuweni) Dave Fisher Comments:
(tuweni) Kenneth Knowles Comments:
(tuweni) Jean-Baptiste Onofré Comments:
(tuweni) Michael Wall Comments:
(tuweni) Furkan Kamaci Comments:

IPMC/Shepherd notes:

TVM

TVM is a full stack open deep learning compiler stack for CPUs, GPUs, and specialized accelerators. It aims to close the gap between the productivity- focused deep learning frameworks, and the performance- or efficiency- oriented hardware backends.

TVM has been incubating since 2019-03-06.

Three most important unfinished issues to address before graduating:

Are there any issues that the IPMC or ASF Board need to be aware of?

How has the community developed since the last report?

How has the project developed since the last report?

How would you assess the podling's maturity?

Please feel free to add your own commentary.

Initial setup
Working towards first release
Community building
Nearing graduation
Other:

(tvm) Byung-Gon Chun Comments:
(tvm) Sebastian Schelter Comments:
(tvm) Henry Saputra Comments:
(tvm) Timothy Chen Comments:
(tvm) Furkan Kamaci Comments:

Initial setup
Working towards first release
Community building
Nearing graduation
Other:

(weex) Willem Ning Jiang Comments:
(weex) Myrle Krantz Comments:
(weex) Jan Piotrowski Comments:

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Shepherd Assignments