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From Ted Dunning <>
Subject Re: [VOTE] Accept Drill into the Apache Incubator
Date Sat, 11 Aug 2012 07:27:32 GMT
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

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 <> wrote:
> +1 (non-binding)
> On Wed, Aug 8, 2012 at 8:11 AM, Ted Dunning <> 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
>> = Drill =
>> == Abstract ==
>> Drill is a distributed system for interactive analysis of large-scale
>> datasets, inspired by
>> [[|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
>> [[|Google
>> BigQuery]], which we call DrQL. However, Drill is designed to support
>> other languages and programming models, such as the
>> [[|Mongo Query
>> Language]], [[|Cascading]] or
>> [[|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 [[|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
>> [[|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://
>> === 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
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> --
> Best regards,
>    - Andy
> Problems worthy of attack prove their worth by hitting back. - Piet
> Hein (via Tom White)
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