git commit: First commit

[td...@apache.org]

Updated Branches:
  refs/heads/master [created] 9229caa45


First commit

Project: http://git-wip-us.apache.org/repos/asf/incubator-drill/repo
Commit: http://git-wip-us.apache.org/repos/asf/incubator-drill/commit/9229caa4
Tree: http://git-wip-us.apache.org/repos/asf/incubator-drill/tree/9229caa4
Diff: http://git-wip-us.apache.org/repos/asf/incubator-drill/diff/9229caa4

Branch: refs/heads/master
Commit: 9229caa45a32dc06625f2443b6a5d84ab0a4df10
Parents: 
Author: Ted Dunning <te...@gmail.com>
Authored: Mon Sep 3 13:21:32 2012 -0700
Committer: Ted Dunning <te...@gmail.com>
Committed: Mon Sep 3 13:21:32 2012 -0700

----------------------------------------------------------------------
 README.md |  127 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 files changed, 127 insertions(+), 0 deletions(-)
----------------------------------------------------------------------


http://git-wip-us.apache.org/repos/asf/incubator-drill/blob/9229caa4/README.md
----------------------------------------------------------------------
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..51772a9
--- /dev/null
+++ b/README.md
@@ -0,0 +1,127 @@
+= Drill =
+
+This is a copy of the original proposal for Drill, for now.  Please edit and update as appropriate.
+
+== 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. Check out the [[attachment:Drill slides.pdf|attached slides]].
+
+== 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
+

Re: 答复: git commit: First commit

[Ted Dunning <te...@gmail.com>]

Yes.  This was just a test to see if git was working.

On Mon, Sep 3, 2012 at 6:41 PM, 周大 <zh...@chinamobile.com> wrote:

> Is there only README?
>
>
> Da Zhou (周大)
> ------------------------------------------------
> China Mobile Research Institute
> No.32 Xuanwumen West Street,
> XiCheng District
> Beijing 100053, P.R. China
> Mobile: +86 13910309724
> Office: +86 15801696688 - 35989
> -------------------------------------------------
>
> -----邮件原件-----
> 发件人: Michael Hausenblas [mailto:michael.hausenblas@gmail.com]
> 发送时间: 2012年9月4日 5:23
> 收件人: drill-dev@incubator.apache.org
> 主题: Re: git commit: First commit
>
> Ted,
>
> > First commit
>
> Cool ;)
>
> Tried to clone and got:
>
>  git clone git://git-wip-us.apache.org/repos/asf?p=incubator-drill.gitrepo
>  Cloning into repo...
>  git-wip-us.apache.org[0: 140.211.11.121]: errno=Operation timed out
>  fatal: unable to connect a socket (Operation timed out)
>
> Also, it seems to not been listed on http://git.apache.org/ yet - could
> that
> be the reason for me not being able to clone it?
>
> Cheers,
>            Michael
>
> --
> Michael Hausenblas
> Ireland, Europe
> http://mhausenblas.info/
>
> On 3 Sep 2012, at 22:09, tdunning@apache.org wrote:
>
> > Updated Branches:
> >  refs/heads/master [created] 9229caa45
> >
> >
> > First commit
> >
> > Project: http://git-wip-us.apache.org/repos/asf/incubator-drill/repo
> > Commit:
> http://git-wip-us.apache.org/repos/asf/incubator-drill/commit/9229caa4
> > Tree:
> http://git-wip-us.apache.org/repos/asf/incubator-drill/tree/9229caa4
> > Diff:
> http://git-wip-us.apache.org/repos/asf/incubator-drill/diff/9229caa4
> >
> > Branch: refs/heads/master
> > Commit: 9229caa45a32dc06625f2443b6a5d84ab0a4df10
> > Parents:
> > Author: Ted Dunning <te...@gmail.com>
> > Authored: Mon Sep 3 13:21:32 2012 -0700
> > Committer: Ted Dunning <te...@gmail.com>
> > Committed: Mon Sep 3 13:21:32 2012 -0700
> >
> > ----------------------------------------------------------------------
> > README.md |  127 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++
> > 1 files changed, 127 insertions(+), 0 deletions(-)
> > ----------------------------------------------------------------------
> >
> >
> >
> http://git-wip-us.apache.org/repos/asf/incubator-drill/blob/9229caa4/README
> .
> md
> > ----------------------------------------------------------------------
> > diff --git a/README.md b/README.md
> > new file mode 100644
> > index 0000000..51772a9
> > --- /dev/null
> > +++ b/README.md
> > @@ -0,0 +1,127 @@
> > += Drill =
> > +
> > +This is a copy of the original proposal for Drill, for now.  Please edit
> and update as appropriate.
> > +
> > +== 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. Check out the [[attachment:Drill slides.pdf|attached
> slides]].
> > +
> > +== 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
> > +
> >
>
>

答复: git commit: First commit

[周大 <zh...@chinamobile.com>]

Is there only README?


Da Zhou (�ܴ�)
------------------------------------------------
China Mobile Research Institute
No.32 Xuanwumen West Street, 
XiCheng District
Beijing 100053, P.R. China
Mobile: +86 13910309724
Office: +86 15801696688 - 35989
------------------------------------------------- 

-----�ʼ�ԭ��-----
������: Michael Hausenblas [mailto:michael.hausenblas@gmail.com] 
����ʱ��: 2012��9��4�� 5:23
�ռ���: drill-dev@incubator.apache.org
����: Re: git commit: First commit

Ted,

> First commit

Cool ;)

Tried to clone and got:

 git clone git://git-wip-us.apache.org/repos/asf?p=incubator-drill.git repo 
 Cloning into repo...
 git-wip-us.apache.org[0: 140.211.11.121]: errno=Operation timed out
 fatal: unable to connect a socket (Operation timed out)

Also, it seems to not been listed on http://git.apache.org/ yet - could that
be the reason for me not being able to clone it?

Cheers,
	   Michael

--
Michael Hausenblas
Ireland, Europe
http://mhausenblas.info/

On 3 Sep 2012, at 22:09, tdunning@apache.org wrote:

> Updated Branches:
>  refs/heads/master [created] 9229caa45
> 
> 
> First commit
> 
> Project: http://git-wip-us.apache.org/repos/asf/incubator-drill/repo
> Commit:
http://git-wip-us.apache.org/repos/asf/incubator-drill/commit/9229caa4
> Tree: http://git-wip-us.apache.org/repos/asf/incubator-drill/tree/9229caa4
> Diff: http://git-wip-us.apache.org/repos/asf/incubator-drill/diff/9229caa4
> 
> Branch: refs/heads/master
> Commit: 9229caa45a32dc06625f2443b6a5d84ab0a4df10
> Parents: 
> Author: Ted Dunning <te...@gmail.com>
> Authored: Mon Sep 3 13:21:32 2012 -0700
> Committer: Ted Dunning <te...@gmail.com>
> Committed: Mon Sep 3 13:21:32 2012 -0700
> 
> ----------------------------------------------------------------------
> README.md |  127 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++
> 1 files changed, 127 insertions(+), 0 deletions(-)
> ----------------------------------------------------------------------
> 
> 
>
http://git-wip-us.apache.org/repos/asf/incubator-drill/blob/9229caa4/README.
md
> ----------------------------------------------------------------------
> diff --git a/README.md b/README.md
> new file mode 100644
> index 0000000..51772a9
> --- /dev/null
> +++ b/README.md
> @@ -0,0 +1,127 @@
> += Drill =
> +
> +This is a copy of the original proposal for Drill, for now.  Please edit
and update as appropriate.
> +
> +== 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. Check out the [[attachment:Drill slides.pdf|attached
slides]].
> +
> +== 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> �C Chief Application
Architect at MapR Technologies, Committer for Lucene, Mahout and ZooKeeper.
> + * Grant Ingersoll <grant at lucidimagination dot com> �C Chief Scientist
at Lucid Imagination, Committer for Lucene, Mahout and other projects.
> + * Isabel Drost <isabel at apache dot org> �C Software Developer at Nokia
Gate 5 GmbH, Committer for Lucene, Mahout and other projects.
> +
> +=== Sponsoring Entity ===
> +Incubator
> +
> 

Re: git commit: First commit

[Ted Dunning <te...@gmail.com>]

I am not sure why it isn't mirrored to git.a.o yet, but Jim's answer is
correct.

On Mon, Sep 3, 2012 at 5:49 PM, Jim Donofrio <do...@gmail.com> wrote:

> use https://git-wip-us.apache.org/**repos/asf/incubator-drill.git<https://git-wip-us.apache.org/repos/asf/incubator-drill.git>
>
> On 09/03/2012 05:22 PM, Michael Hausenblas wrote:
>
>> Ted,
>>
>>  First commit
>>>
>> Cool ;)
>>
>> Tried to clone and got:
>>
>>   git clone git://git-wip-us.apache.org/**repos/asf?p=incubator-drill.**
>> git <http://git-wip-us.apache.org/repos/asf?p=incubator-drill.git> repo
>>   Cloning into repo...
>>   git-wip-us.apache.org[0: 140.211.11.121]: errno=Operation timed out
>>   fatal: unable to connect a socket (Operation timed out)
>>
>> Also, it seems to not been listed on http://git.apache.org/ yet - could
>> that be the reason for me not being able to clone it?
>>
>> Cheers,
>>            Michael
>>
>> --
>> Michael Hausenblas
>> Ireland, Europe
>> http://mhausenblas.info/
>>
>> On 3 Sep 2012, at 22:09, tdunning@apache.org wrote:
>>
>>  Updated Branches:
>>>   refs/heads/master [created] 9229caa45
>>>
>>>
>>> First commit
>>>
>>> Project: http://git-wip-us.apache.org/**repos/asf/incubator-drill/repo<http://git-wip-us.apache.org/repos/asf/incubator-drill/repo>
>>> Commit: http://git-wip-us.apache.org/**repos/asf/incubator-drill/**
>>> commit/9229caa4<http://git-wip-us.apache.org/repos/asf/incubator-drill/commit/9229caa4>
>>> Tree: http://git-wip-us.apache.org/**repos/asf/incubator-drill/**
>>> tree/9229caa4<http://git-wip-us.apache.org/repos/asf/incubator-drill/tree/9229caa4>
>>> Diff: http://git-wip-us.apache.org/**repos/asf/incubator-drill/**
>>> diff/9229caa4<http://git-wip-us.apache.org/repos/asf/incubator-drill/diff/9229caa4>
>>>
>>> Branch: refs/heads/master
>>> Commit: 9229caa45a32dc06625f2443b6a5d8**4ab0a4df10
>>> Parents:
>>> Author: Ted Dunning <te...@gmail.com>
>>> Authored: Mon Sep 3 13:21:32 2012 -0700
>>> Committer: Ted Dunning <te...@gmail.com>
>>> Committed: Mon Sep 3 13:21:32 2012 -0700
>>>
>>> ------------------------------**------------------------------**
>>> ----------
>>> README.md |  127 ++++++++++++++++++++++++++++++**
>>> ++++++++++++++++++++++++++
>>> 1 files changed, 127 insertions(+), 0 deletions(-)
>>> ------------------------------**------------------------------**
>>> ----------
>>>
>>>
>>> http://git-wip-us.apache.org/**repos/asf/incubator-drill/**
>>> blob/9229caa4/README.md<http://git-wip-us.apache.org/repos/asf/incubator-drill/blob/9229caa4/README.md>
>>> ------------------------------**------------------------------**
>>> ----------
>>> diff --git a/README.md b/README.md
>>> new file mode 100644
>>> index 0000000..51772a9
>>> --- /dev/null
>>> +++ b/README.md
>>> @@ -0,0 +1,127 @@
>>> += Drill =
>>> +
>>> +This is a copy of the original proposal for Drill, for now.  Please
>>> edit and update as appropriate.
>>> +
>>> +== Abstract ==
>>> +Drill is a distributed system for interactive analysis of large-scale
>>> datasets, inspired by [[http://research.google.com/**
>>> pubs/pub36632.html|Google's<http://research.google.com/pubs/pub36632.html%7CGoogle'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<https://developers.google.com/bigquery/docs/query-reference%7CGoogle>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<http://www.mongodb.org/display/DOCS/Mongo+Query+Language%7CMongo>Query Language]], [[
>>> http://www.cascading.org/|**Cascading<http://www.cascading.org/%7CCascading>]]
>>> or [[https://github.com/tdunning/**Plume|Plume]<https://github.com/tdunning/Plume%7CPlume%5D>
>>> ].
>>> + * 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<http://tesla.hpl.hp.com/opensource/%7CDataSeries>]]
>>> 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<http://research.google.com/pubs/pub36632.html%7Cpaper>]]
>>> 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. Check out the [[attachment:Drill slides.pdf|attached
>>> slides]].
>>> +
>>> +== 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
>>> +
>>>
>>>
>>
>

Re: git commit: First commit

[Michael Hausenblas <mi...@gmail.com>]

> use https://git-wip-us.apache.org/repos/asf/incubator-drill.git

Thanks, that worked.

Cheers,
	   Michael

--
Michael Hausenblas
Ireland, Europe
http://mhausenblas.info/

On 3 Sep 2012, at 22:49, Jim Donofrio wrote:

> use https://git-wip-us.apache.org/repos/asf/incubator-drill.git
> 
> On 09/03/2012 05:22 PM, Michael Hausenblas wrote:
>> Ted,
>> 
>>> First commit
>> Cool ;)
>> 
>> Tried to clone and got:
>> 
>>  git clone git://git-wip-us.apache.org/repos/asf?p=incubator-drill.git repo
>>  Cloning into repo...
>>  git-wip-us.apache.org[0: 140.211.11.121]: errno=Operation timed out
>>  fatal: unable to connect a socket (Operation timed out)
>> 
>> Also, it seems to not been listed on http://git.apache.org/ yet - could that be the reason for me not being able to clone it?
>> 
>> Cheers,
>> 	   Michael
>> 
>> --
>> Michael Hausenblas
>> Ireland, Europe
>> http://mhausenblas.info/
>> 
>> On 3 Sep 2012, at 22:09, tdunning@apache.org wrote:
>> 
>>> Updated Branches:
>>>  refs/heads/master [created] 9229caa45
>>> 
>>> 
>>> First commit
>>> 
>>> Project: http://git-wip-us.apache.org/repos/asf/incubator-drill/repo
>>> Commit: http://git-wip-us.apache.org/repos/asf/incubator-drill/commit/9229caa4
>>> Tree: http://git-wip-us.apache.org/repos/asf/incubator-drill/tree/9229caa4
>>> Diff: http://git-wip-us.apache.org/repos/asf/incubator-drill/diff/9229caa4
>>> 
>>> Branch: refs/heads/master
>>> Commit: 9229caa45a32dc06625f2443b6a5d84ab0a4df10
>>> Parents:
>>> Author: Ted Dunning <te...@gmail.com>
>>> Authored: Mon Sep 3 13:21:32 2012 -0700
>>> Committer: Ted Dunning <te...@gmail.com>
>>> Committed: Mon Sep 3 13:21:32 2012 -0700
>>> 
>>> ----------------------------------------------------------------------
>>> README.md |  127 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++
>>> 1 files changed, 127 insertions(+), 0 deletions(-)
>>> ----------------------------------------------------------------------
>>> 
>>> 
>>> http://git-wip-us.apache.org/repos/asf/incubator-drill/blob/9229caa4/README.md
>>> ----------------------------------------------------------------------
>>> diff --git a/README.md b/README.md
>>> new file mode 100644
>>> index 0000000..51772a9
>>> --- /dev/null
>>> +++ b/README.md
>>> @@ -0,0 +1,127 @@
>>> += Drill =
>>> +
>>> +This is a copy of the original proposal for Drill, for now.  Please edit and update as appropriate.
>>> +
>>> +== 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. Check out the [[attachment:Drill slides.pdf|attached slides]].
>>> +
>>> +== 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
>>> +
>>> 
>> 
> 

Re: git commit: First commit

[Jim Donofrio <do...@gmail.com>]

use https://git-wip-us.apache.org/repos/asf/incubator-drill.git

On 09/03/2012 05:22 PM, Michael Hausenblas wrote:
> Ted,
>
>> First commit
> Cool ;)
>
> Tried to clone and got:
>
>   git clone git://git-wip-us.apache.org/repos/asf?p=incubator-drill.git repo
>   Cloning into repo...
>   git-wip-us.apache.org[0: 140.211.11.121]: errno=Operation timed out
>   fatal: unable to connect a socket (Operation timed out)
>
> Also, it seems to not been listed on http://git.apache.org/ yet - could that be the reason for me not being able to clone it?
>
> Cheers,
> 	   Michael
>
> --
> Michael Hausenblas
> Ireland, Europe
> http://mhausenblas.info/
>
> On 3 Sep 2012, at 22:09, tdunning@apache.org wrote:
>
>> Updated Branches:
>>   refs/heads/master [created] 9229caa45
>>
>>
>> First commit
>>
>> Project: http://git-wip-us.apache.org/repos/asf/incubator-drill/repo
>> Commit: http://git-wip-us.apache.org/repos/asf/incubator-drill/commit/9229caa4
>> Tree: http://git-wip-us.apache.org/repos/asf/incubator-drill/tree/9229caa4
>> Diff: http://git-wip-us.apache.org/repos/asf/incubator-drill/diff/9229caa4
>>
>> Branch: refs/heads/master
>> Commit: 9229caa45a32dc06625f2443b6a5d84ab0a4df10
>> Parents:
>> Author: Ted Dunning <te...@gmail.com>
>> Authored: Mon Sep 3 13:21:32 2012 -0700
>> Committer: Ted Dunning <te...@gmail.com>
>> Committed: Mon Sep 3 13:21:32 2012 -0700
>>
>> ----------------------------------------------------------------------
>> README.md |  127 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++
>> 1 files changed, 127 insertions(+), 0 deletions(-)
>> ----------------------------------------------------------------------
>>
>>
>> http://git-wip-us.apache.org/repos/asf/incubator-drill/blob/9229caa4/README.md
>> ----------------------------------------------------------------------
>> diff --git a/README.md b/README.md
>> new file mode 100644
>> index 0000000..51772a9
>> --- /dev/null
>> +++ b/README.md
>> @@ -0,0 +1,127 @@
>> += Drill =
>> +
>> +This is a copy of the original proposal for Drill, for now.  Please edit and update as appropriate.
>> +
>> +== 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. Check out the [[attachment:Drill slides.pdf|attached slides]].
>> +
>> +== 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
>> +
>>
>

Re: git commit: First commit

[Michael Hausenblas <mi...@gmail.com>]

Ted,

> First commit

Cool ;)

Tried to clone and got:

 git clone git://git-wip-us.apache.org/repos/asf?p=incubator-drill.git repo 
 Cloning into repo...
 git-wip-us.apache.org[0: 140.211.11.121]: errno=Operation timed out
 fatal: unable to connect a socket (Operation timed out)

Also, it seems to not been listed on http://git.apache.org/ yet - could that be the reason for me not being able to clone it?

Cheers,
	   Michael

--
Michael Hausenblas
Ireland, Europe
http://mhausenblas.info/

On 3 Sep 2012, at 22:09, tdunning@apache.org wrote:

> Updated Branches:
>  refs/heads/master [created] 9229caa45
> 
> 
> First commit
> 
> Project: http://git-wip-us.apache.org/repos/asf/incubator-drill/repo
> Commit: http://git-wip-us.apache.org/repos/asf/incubator-drill/commit/9229caa4
> Tree: http://git-wip-us.apache.org/repos/asf/incubator-drill/tree/9229caa4
> Diff: http://git-wip-us.apache.org/repos/asf/incubator-drill/diff/9229caa4
> 
> Branch: refs/heads/master
> Commit: 9229caa45a32dc06625f2443b6a5d84ab0a4df10
> Parents: 
> Author: Ted Dunning <te...@gmail.com>
> Authored: Mon Sep 3 13:21:32 2012 -0700
> Committer: Ted Dunning <te...@gmail.com>
> Committed: Mon Sep 3 13:21:32 2012 -0700
> 
> ----------------------------------------------------------------------
> README.md |  127 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++
> 1 files changed, 127 insertions(+), 0 deletions(-)
> ----------------------------------------------------------------------
> 
> 
> http://git-wip-us.apache.org/repos/asf/incubator-drill/blob/9229caa4/README.md
> ----------------------------------------------------------------------
> diff --git a/README.md b/README.md
> new file mode 100644
> index 0000000..51772a9
> --- /dev/null
> +++ b/README.md
> @@ -0,0 +1,127 @@
> += Drill =
> +
> +This is a copy of the original proposal for Drill, for now.  Please edit and update as appropriate.
> +
> +== 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. Check out the [[attachment:Drill slides.pdf|attached slides]].
> +
> +== 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
> +
>