Otis said his vote was 'blinding', not 'binding'. Doug On Aug 11, 2012 12:28 AM, "Ted Dunning" <ted.dunn...@gmail.com> wrote:
> This vote is now closed. > > In the responses to this thread, I count 15 binding positive votes and > 4 non-binding votes. The number of positive votes increases to 17 if > you count myself (the champion) and Isabel (a mentor) but neither of > us actually sent the key email to record a vote (oops). > > One of the non-binding votes was by Otis Gospadnetic who said that his > vote was binding, but I didn't find his name on the list of incubator > PMC members, so I counted it as non-binding. The list I used is at > http://people.apache.org/committers-by-project.html#incubator-pmc > > By any count, this vote to admit Drill to incubator therefore passes. > > This proposal includes mentors so this vote also constitutes > acceptance of the mentors by the Incubator PMC. All three of the > mentors (Grant, myself, and Isabel) are Apache members. > > This proposal as approved also includes an initial list of committers, > all of whom have ICLA's on file. > > I will coordinate with the other mentors and the committers to commit > the status file and perform other establishment activities necessary > to establish Drill as a project under incubation. I expect that this > will take several days. I will announce progress on this mailing list > to allow people to subscribe to the mailing lists. > > > On Thu, Aug 9, 2012 at 11:27 AM, Andrew Purtell <apurt...@apache.org> > wrote: > > +1 (non-binding) > > > > On Wed, Aug 8, 2012 at 8:11 AM, Ted Dunning <ted.dunn...@gmail.com> > wrote: > >> I would like to call a vote for accepting Drill for incubation in the > >> Apache Incubator. The full proposal is available below. Discussion > >> over the last few days has been quite positive. > >> > >> Please cast your vote: > >> > >> [ ] +1, bring Drill into Incubator > >> [ ] +0, I don't care either way, > >> [ ] -1, do not bring Drill into Incubator, because... > >> > >> This vote will be open for 72 hours and only votes from the Incubator > >> PMC are binding. The start of the vote is just before 3AM UTC on 8 > >> August so the closing time will be 3AM UTC on 11 August. > >> > >> Thank you for your consideration! > >> > >> Ted > >> > >> http://wiki.apache.org/incubator/DrillProposal > >> > >> = Drill = > >> > >> == Abstract == > >> Drill is a distributed system for interactive analysis of large-scale > >> datasets, inspired by > >> [[http://research.google.com/pubs/pub36632.html|Google's Dremel]]. > >> > >> == Proposal == > >> Drill is a distributed system for interactive analysis of large-scale > >> datasets. Drill is similar to Google's Dremel, with the additional > >> flexibility needed to support a broader range of query languages, data > >> formats and data sources. It is designed to efficiently process nested > >> data. It is a design goal to scale to 10,000 servers or more and to be > >> able to process petabyes of data and trillions of records in seconds. > >> > >> == Background == > >> Many organizations have the need to run data-intensive applications, > >> including batch processing, stream processing and interactive > >> analysis. In recent years open source systems have emerged to address > >> the need for scalable batch processing (Apache Hadoop) and stream > >> processing (Storm, Apache S4). In 2010 Google published a paper called > >> "Dremel: Interactive Analysis of Web-Scale Datasets," describing a > >> scalable system used internally for interactive analysis of nested > >> data. No open source project has successfully replicated the > >> capabilities of Dremel. > >> > >> == Rationale == > >> There is a strong need in the market for low-latency interactive > >> analysis of large-scale datasets, including nested data (eg, JSON, > >> Avro, Protocol Buffers). This need was identified by Google and > >> addressed internally with a system called Dremel. > >> > >> In recent years open source systems have emerged to address the need > >> for scalable batch processing (Apache Hadoop) and stream processing > >> (Storm, Apache S4). Apache Hadoop, originally inspired by Google's > >> internal MapReduce system, is used by thousands of organizations > >> processing large-scale datasets. Apache Hadoop is designed to achieve > >> very high throughput, but is not designed to achieve the sub-second > >> latency needed for interactive data analysis and exploration. Drill, > >> inspired by Google's internal Dremel system, is intended to address > >> this need. > >> > >> It is worth noting that, as explained by Google in the original paper, > >> Dremel complements MapReduce-based computing. Dremel is not intended > >> as a replacement for MapReduce and is often used in conjunction with > >> it to analyze outputs of MapReduce pipelines or rapidly prototype > >> larger computations. Indeed, Dremel and MapReduce are both used by > >> thousands of Google employees. > >> > >> Like Dremel, Drill supports a nested data model with data encoded in a > >> number of formats such as JSON, Avro or Protocol Buffers. In many > >> organizations nested data is the standard, so supporting a nested data > >> model eliminates the need to normalize the data. With that said, flat > >> data formats, such as CSV files, are naturally supported as a special > >> case of nested data. > >> > >> The Drill architecture consists of four key components/layers: > >> * Query languages: This layer is responsible for parsing the user's > >> query and constructing an execution plan. The initial goal is to > >> support the SQL-like language used by Dremel and > >> [[https://developers.google.com/bigquery/docs/query-reference|Google > >> BigQuery]], which we call DrQL. However, Drill is designed to support > >> other languages and programming models, such as the > >> [[http://www.mongodb.org/display/DOCS/Mongo+Query+Language|Mongo Query > >> Language]], [[http://www.cascading.org/|Cascading]] or > >> [[https://github.com/tdunning/Plume|Plume]]. > >> * Low-latency distributed execution engine: This layer is responsible > >> for executing the physical plan. It provides the scalability and fault > >> tolerance needed to efficiently query petabytes of data on 10,000 > >> servers. Drill's execution engine is based on research in distributed > >> execution engines (eg, Dremel, Dryad, Hyracks, CIEL, Stratosphere) and > >> columnar storage, and can be extended with additional operators and > >> connectors. > >> * Nested data formats: This layer is responsible for supporting > >> various data formats. The initial goal is to support the column-based > >> format used by Dremel. Drill is designed to support schema-based > >> formats such as Protocol Buffers/Dremel, Avro/AVRO-806/Trevni and CSV, > >> and schema-less formats such as JSON, BSON or YAML. In addition, it is > >> designed to support column-based formats such as Dremel, > >> AVRO-806/Trevni and RCFile, and row-based formats such as Protocol > >> Buffers, Avro, JSON, BSON and CSV. A particular distinction with Drill > >> is that the execution engine is flexible enough to support > >> column-based processing as well as row-based processing. This is > >> important because column-based processing can be much more efficient > >> when the data is stored in a column-based format, but many large data > >> assets are stored in a row-based format that would require conversion > >> before use. > >> * Scalable data sources: This layer is responsible for supporting > >> various data sources. The initial focus is to leverage Hadoop as a > >> data source. > >> > >> It is worth noting that no open source project has successfully > >> replicated the capabilities of Dremel, nor have any taken on the > >> broader goals of flexibility (eg, pluggable query languages, data > >> formats, data sources and execution engine operators/connectors) that > >> are part of Drill. > >> > >> == Initial Goals == > >> The initial goals for this project are to specify the detailed > >> requirements and architecture, and then develop the initial > >> implementation including the execution engine and DrQL. > >> Like Apache Hadoop, which was built to support multiple storage > >> systems (through the FileSystem API) and file formats (through the > >> InputFormat/OutputFormat APIs), Drill will be built to support > >> multiple query languages, data formats and data sources. The initial > >> implementation of Drill will support the DrQL and a column-based > >> format similar to Dremel. > >> > >> == Current Status == > >> Significant work has been completed to identify the initial > >> requirements and define the overall system architecture. The next step > >> is to implement the four components described in the Rationale > >> section, and we intend to do that development as an Apache project. > >> > >> === Meritocracy === > >> We plan to invest in supporting a meritocracy. We will discuss the > >> requirements in an open forum. Several companies have already > >> expressed interest in this project, and we intend to invite additional > >> developers to participate. We will encourage and monitor community > >> participation so that privileges can be extended to those that > >> contribute. Also, Drill has an extensible/pluggable architecture that > >> encourages developers to contribute various extensions, such as query > >> languages, data formats, data sources and execution engine operators > >> and connectors. While some companies will surely develop commercial > >> extensions, we also anticipate that some companies and individuals > >> will want to contribute such extensions back to the project, and we > >> look forward to fostering a rich ecosystem of extensions. > >> > >> === Community === > >> The need for a system for interactive analysis of large datasets in > >> the open source is tremendous, so there is a potential for a very > >> large community. We believe that Drill's extensible architecture will > >> further encourage community participation. Also, related Apache > >> projects (eg, Hadoop) have very large and active communities, and we > >> expect that over time Drill will also attract a large community. > >> > >> === Core Developers === > >> The developers on the initial committers list include experienced > >> distributed systems engineers: > >> * Tomer Shiran has experience developing distributed execution > >> engines. He developed Parallel DataSeries, a data-parallel version of > >> the open source [[http://tesla.hpl.hp.com/opensource/|DataSeries]] > >> system. He is also the author of Applying Idealized Lower-bound > >> Runtime Models to Understand Inefficiencies in Data-intensive > >> Computing (SIGMETRICS 2011). Tomer worked as a software developer and > >> researcher at IBM Research, Microsoft and HP Labs, and is now at MapR > >> Technologies. He has been active in the Hadoop community since 2009. > >> * Jason Frantz was at Clustrix, where he designed and developed the > >> first scale-out SQL database based on MySQL. Jason developed the > >> distributed query optimizer that powered Clustrix. He is now a > >> software engineer and architect at MapR Technologies. > >> * Ted Dunning is a PMC member for Apache ZooKeeper and Apache Mahout, > >> and has a history of over 30 years of contributions to open source. He > >> is now at MapR Technologies. Ted has been very active in the Hadoop > >> community since the project's early days. > >> * MC Srivas is the co-founder and CTO of MapR Technologies. While at > >> Google he worked on Google's scalable search infrastructure. MC Srivas > >> has been active in the Hadoop community since 2009. > >> * Chris Wensel is the founder and CEO of Concurrent. Prior to > >> founding Concurrent, he developed Cascading, an Apache-licensed open > >> source application framework enabling Java developers to quickly and > >> easily develop robust Data Analytics and Data Management applications > >> on Apache Hadoop. Chris has been involved in the Hadoop community > >> since the project's early days. > >> * Keys Botzum was at IBM, where he worked on security and distributed > >> systems, and is currently at MapR Technologies. > >> * Gera Shegalov was at Oracle, where he worked on networking, storage > >> and database kernels, and is currently at MapR Technologies. > >> * Ryan Rawson is the VP Engineering of Drawn to Scale where he > >> developed Spire, a real-time operational database for Hadoop. He is > >> also a committer and PMC member for Apache HBase, and has a long > >> history of contributions to open source. Ryan has been involved in the > >> Hadoop community since the project's early days. > >> > >> We realize that additional employer diversity is needed, and we will > >> work aggressively to recruit developers from additional companies. > >> > >> === Alignment === > >> The initial committers strongly believe that a system for interactive > >> analysis of large-scale datasets will gain broader adoption as an open > >> source, community driven project, where the community can contribute > >> not only to the core components, but also to a growing collection of > >> query languages and optimizers, data formats, data formats, and > >> execution engine operators and connectors. Drill will integrate > >> closely with Apache Hadoop. First, the data will live in Hadoop. That > >> is, Drill will support Hadoop FileSystem implementations and HBase. > >> Second, Hadoop-related data formats will be supported (eg, Apache > >> Avro, RCFile). Third, MapReduce-based tools will be provided to > >> produce column-based formats. Fourth, Drill tables can be registered > >> in HCatalog. Finally, Hive is being considered as the basis of the > >> DrQL implementation. > >> > >> == Known Risks == > >> > >> === Orphaned Products === > >> The contributors are leading vendors in this space, with significant > >> open source experience, so the risk of being orphaned is relatively > >> low. The project could be at risk if vendors decided to change their > >> strategies in the market. In such an event, the current committers > >> plan to continue working on the project on their own time, though the > >> progress will likely be slower. We plan to mitigate this risk by > >> recruiting additional committers. > >> > >> === Inexperience with Open Source === > >> The initial committers include veteran Apache members (committers and > >> PMC members) and other developers who have varying degrees of > >> experience with open source projects. All have been involved with > >> source code that has been released under an open source license, and > >> several also have experience developing code with an open source > >> development process. > >> > >> === Homogenous Developers === > >> The initial committers are employed by a number of companies, > >> including MapR Technologies, Concurrent and Drawn to Scale. We are > >> committed to recruiting additional committers from other companies. > >> > >> === Reliance on Salaried Developers === > >> It is expected that Drill development will occur on both salaried time > >> and on volunteer time, after hours. The majority of initial committers > >> are paid by their employer to contribute to this project. However, > >> they are all passionate about the project, and we are confident that > >> the project will continue even if no salaried developers contribute to > >> the project. We are committed to recruiting additional committers > >> including non-salaried developers. > >> > >> === Relationships with Other Apache Products === > >> As mentioned in the Alignment section, Drill is closely integrated > >> with Hadoop, Avro, Hive and HBase in a numerous ways. For example, > >> Drill data lives inside a Hadoop environment (Drill operates on in > >> situ data). We look forward to collaborating with those communities, > >> as well as other Apache communities. > >> > >> === An Excessive Fascination with the Apache Brand === > >> Drill solves a real problem that many organizations struggle with, and > >> has been proven within Google to be of significant value. The > >> architecture is based on academic and industry research. Our rationale > >> for developing Drill as an Apache project is detailed in the Rationale > >> section. We believe that the Apache brand and community process will > >> help us attract more contributors to this project, and help establish > >> ubiquitous APIs. In addition, establishing consensus among users and > >> developers of a Dremel-like tool is a key requirement for success of > >> the project. > >> > >> == Documentation == > >> Drill is inspired by Google's Dremel. Google has published a > >> [[http://research.google.com/pubs/pub36632.html|paper]] highlighting > >> Dremel's innovative nested column-based data format and execution > >> engine. > >> > >> == Initial Source == > >> The requirement and design documents are currently stored in MapR > >> Technologies' source code repository. They will be checked in as part > >> of the initial code dump. > >> > >> == Cryptography == > >> Drill will eventually support encryption on the wire. This is not one > >> of the initial goals, and we do not expect Drill to be a controlled > >> export item due to the use of encryption. > >> > >> == Required Resources == > >> > >> === Mailing List === > >> * drill-private > >> * drill-dev > >> * drill-user > >> > >> === Subversion Directory === > >> Git is the preferred source control system: git://git.apache.org/drill > >> > >> === Issue Tracking === > >> JIRA Drill (DRILL) > >> > >> == Initial Committers == > >> * Tomer Shiran <tshiran at maprtech dot com> > >> * Ted Dunning <tdunning at apache dot org> > >> * Jason Frantz <jfrantz at maprtech dot com> > >> * MC Srivas <mcsrivas at maprtech dot com> > >> * Chris Wensel <chris and concurrentinc dot com> > >> * Keys Botzum <kbotzum at maprtech dot com> > >> * Gera Shegalov <gshegalov at maprtech dot com> > >> * Ryan Rawson <ryan at drawntoscale dot com> > >> > >> == Affiliations == > >> The initial committers are employees of MapR Technologies, Drawn to > >> Scale and Concurrent. The nominated mentors are employees of MapR > >> Technologies, Lucid Imagination and Nokia. > >> > >> == Sponsors == > >> > >> === Champion === > >> Ted Dunning (tdunning at apache dot org) > >> > >> === Nominated Mentors === > >> * Ted Dunning <tdunning at apache dot org> – Chief Application > >> Architect at MapR Technologies, Committer for Lucene, Mahout and > >> ZooKeeper. > >> * Grant Ingersoll <grant at lucidimagination dot com> – Chief > >> Scientist at Lucid Imagination, Committer for Lucene, Mahout and other > >> projects. > >> * Isabel Drost <isabel at apache dot org> – Software Developer at > >> Nokia Gate 5 GmbH, Committer for Lucene, Mahout and other projects. > >> > >> === Sponsoring Entity === > >> Incubator > >> > >> --------------------------------------------------------------------- > >> To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org > >> For additional commands, e-mail: general-h...@incubator.apache.org > > > > -- > > Best regards, > > > > - Andy > > > > Problems worthy of attack prove their worth by hitting back. - Piet > > Hein (via Tom White) > > > > --------------------------------------------------------------------- > > To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org > > For additional commands, e-mail: general-h...@incubator.apache.org > > > > --------------------------------------------------------------------- > To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org > For additional commands, e-mail: general-h...@incubator.apache.org > >
