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From Tomer Shiran <tshi...@maprtech.com>
Subject Re: [PROPOSAL] Drill for the Apache Incubator
Date Thu, 16 Aug 2012 07:18:25 GMT
Yes, we plan to support joins.

We are in the process of setting up the mailing lists.

On Thu, Aug 16, 2012 at 12:09 AM, karthik tunga <karthik.tunga@gmail.com>wrote:

> The proposal looks great. I was wondering what operations will drill
> support ?
> For example the dremel paper doesn't talk about joins, will drill support
> joins ?
>
> Sorry if I missed it, is there a dev mailing list I could subscribe to ?
>
> Cheers,
> Karthik
>
> On 13 August 2012 23:55, Bernd Fondermann <bernd.fondermann@gmail.com
> >wrote:
>
> > great proposal and a very promising mentor lineup.
> >
> > Have fun,
> >
> >   Bernd
> >
> > On Thu, Aug 2, 2012 at 11:40 PM, Ted Dunning <tdunning@apache.org>
> wrote:
> > > Abstract
> > > ========
> > > Drill is a distributed system for interactive analysis of large-scale
> > > datasets, inspired by Google’s Dremel (
> > > http://research.google.com/pubs/pub36632.html).
> > >
> > > Proposal
> > > ========
> > > Drill is a distributed system for interactive analysis of large-scale
> > > datasets. Drill is similar to Google’s Dremel, with the additional
> > > flexibility needed to support a broader range of query languages, data
> > > formats and data sources. It is designed to efficiently process nested
> > > data. It is a design goal to scale to 10,000 servers or more and to be
> > able
> > > to process petabyes of data and trillions of records in seconds.
> > >
> > > Background
> > > ==========
> > > Many organizations have the need to run data-intensive applications,
> > > including batch processing, stream processing and interactive analysis.
> > In
> > > recent years open source systems have emerged to address the need for
> > > scalable batch processing (Apache Hadoop) and stream processing (Storm,
> > > Apache S4). In 2010 Google published a paper called “Dremel:
> Interactive
> > > Analysis of Web-Scale Datasets,” describing a scalable system used
> > > internally for interactive analysis of nested data. No open source
> > project
> > > has successfully replicated the capabilities of Dremel.
> > >
> > > Rationale
> > > =========
> > > There is a strong need in the market for low-latency interactive
> analysis
> > > of large-scale datasets, including nested data (eg, JSON, Avro,
> Protocol
> > > Buffers). This need was identified by Google and addressed internally
> > with
> > > a system called Dremel.
> > >
> > > In recent years open source systems have emerged to address the need
> for
> > > scalable batch processing (Apache Hadoop) and stream processing (Storm,
> > > Apache S4). Apache Hadoop, originally inspired by Google’s internal
> > > MapReduce system, is used by thousands of organizations processing
> > > large-scale datasets. Apache Hadoop is designed to achieve very high
> > > throughput, but is not designed to achieve the sub-second latency
> needed
> > > for interactive data analysis and exploration. Drill, inspired by
> > Google’s
> > > internal Dremel system, is intended to address this need.
> > >
> > > It is worth noting that, as explained by Google in the original paper,
> > > Dremel complements MapReduce-based computing. Dremel is not intended
> as a
> > > replacement for MapReduce and is often used in conjunction with it to
> > > analyze outputs of MapReduce pipelines or rapidly prototype larger
> > > computations. Indeed, Dremel and MapReduce are both used by thousands
> of
> > > Google employees.
> > >
> > > Like Dremel, Drill supports a nested data model with data encoded in a
> > > number of formats such as JSON, Avro or Protocol Buffers. In many
> > > organizations nested data is the standard, so supporting a nested data
> > > model eliminates the need to normalize the data. With that said, flat
> > data
> > > formats, such as CSV files, are naturally supported as a special case
> of
> > > nested data.
> > >
> > > The Drill architecture consists of four key components/layers:
> > > * Query languages: This layer is responsible for parsing the user’s
> query
> > > and constructing an execution plan.  The initial goal is to support the
> > > SQL-like language used by Dremel and Google BigQuery (
> > > https://developers.google.com/bigquery/docs/query-reference), which we
> > call
> > > DrQL. However, Drill is designed to support other languages and
> > programming
> > > models, such as the Mongo Query Language (
> > > http://www.mongodb.org/display/DOCS/Mongo+Query+Language), Cascading (
> > > http://www.cascading.org/) or Plume (https://github.com/tdunning/Plume
> ).
> > > * Low-latency distributed execution engine: This layer is responsible
> for
> > > executing the physical plan. It provides the scalability and fault
> > > tolerance needed to efficiently query petabytes of data on 10,000
> > servers.
> > > Drill’s execution engine is based on research in distributed execution
> > > engines (eg, Dremel, Dryad, Hyracks, CIEL, Stratosphere) and columnar
> > > storage, and can be extended with additional operators and connectors.
> > > * Nested data formats: This layer is responsible for supporting various
> > > data formats. The initial goal is to support the column-based format
> used
> > > by Dremel. Drill is designed to support schema-based formats such as
> > > Protocol Buffers/Dremel, Avro/AVRO-806/Trevni and CSV, and schema-less
> > > formats such as JSON, BSON or YAML. In addition, it is designed to
> > support
> > > column-based formats such as Dremel, AVRO-806/Trevni and RCFile, and
> > > row-based formats such as Protocol Buffers, Avro, JSON, BSON and CSV. A
> > > particular distinction with Drill is that the execution engine is
> > flexible
> > > enough to support column-based processing as well as row-based
> > processing.
> > > This is important because column-based processing can be much more
> > > efficient when the data is stored in a column-based format, but many
> > large
> > > data assets are stored in a row-based format that would require
> > conversion
> > > before use.
> > > * Scalable data sources: This layer is responsible for supporting
> various
> > > data sources. The initial focus is to leverage Hadoop as a data source.
> > >
> > > It is worth noting that no open source project has successfully
> > replicated
> > > the capabilities of Dremel, nor have any taken on the broader goals of
> > > flexibility (eg, pluggable query languages, data formats, data sources
> > and
> > > execution engine operators/connectors) that are part of Drill.
> > >
> > > Initial Goals
> > > =============
> > > The initial goals for this project are to specify the detailed
> > requirements
> > > and architecture, and then develop the initial implementation including
> > the
> > > execution engine and DrQL.
> > > Like Apache Hadoop, which was built to support multiple storage systems
> > > (through the FileSystem API) and file formats (through the
> > > InputFormat/OutputFormat APIs), Drill will be built to support multiple
> > > query languages, data formats and data sources. The initial
> > implementation
> > > of Drill will support the DrQL and a column-based format similar to
> > Dremel.
> > >
> > > Current Status
> > > ==============
> > > Significant work has been completed to identify the initial
> requirements
> > > and define the overall system architecture. The next step is to
> implement
> > > the four components described in the Rationale section, and we intend
> to
> > do
> > > that development as an Apache project.
> > >
> > > Meritocracy
> > > ===========
> > > We plan to invest in supporting a meritocracy. We will discuss the
> > > requirements in an open forum. Several companies have already expressed
> > > interest in this project, and we intend to invite additional developers
> > to
> > > participate. We will encourage and monitor community participation so
> > that
> > > privileges can be extended to those that contribute. Also, Drill has an
> > > extensible/pluggable architecture that encourages developers to
> > contribute
> > > various extensions, such as query languages, data formats, data sources
> > and
> > > execution engine operators and connectors. While some companies will
> > surely
> > > develop commercial extensions, we also anticipate that some companies
> and
> > > individuals will want to contribute such extensions back to the
> project,
> > > and we look forward to fostering a rich ecosystem of extensions.
> > >
> > > Community
> > > =========
> > > The need for a system for interactive analysis of large datasets in the
> > > open source is tremendous, so there is a potential for a very large
> > > community. We believe that Drill’s extensible architecture will further
> > > encourage community participation. Also, related Apache projects (eg,
> > > Hadoop) have very large and active communities, and we expect that over
> > > time Drill will also attract a large community.
> > >
> > > Core Developers
> > > ===============
> > > The developers on the initial committers list include experienced
> > > distributed systems engineers:
> > > * Tomer Shiran has experience developing distributed execution engines.
> > He
> > > developed Parallel DataSeries, a data-parallel version of the open
> source
> > > DataSeries system (http://tesla.hpl.hp.com/opensource/). He is also
> the
> > > author of Applying Idealized Lower-bound Runtime Models to Understand
> > > Inefficiencies in Data-intensive Computing (SIGMETRICS 2011). Tomer
> > worked
> > > as a software developer and researcher at IBM Research, Microsoft and
> HP
> > > Labs, and is now at MapR Technologies. He has been active in the Hadoop
> > > community since 2009.
> > > * Jason Frantz was at Clustrix, where he designed and developed the
> first
> > > scale-out SQL database based on MySQL. Jason developed the distributed
> > > query optimizer that powered Clustrix. He is now a software engineer
> and
> > > architect at MapR Technologies.
> > > * Ted Dunning is a PMC member for Apache ZooKeeper and Apache Mahout,
> and
> > > has a history of over 30 years of contributions to open source. He is
> now
> > > at MapR Technologies. Ted has been very active in the Hadoop community
> > > since the project’s early days.
> > > * MC Srivas is the co-founder and CTO of MapR Technologies. While at
> > Google
> > > he worked on Google’s scalable search infrastructure. MC Srivas has
> been
> > > active in the Hadoop community since 2009.
> > > * Chris Wensel is the founder and CEO of Concurrent. Prior to founding
> > > Concurrent, he developed Cascading, an Apache-licensed open source
> > > application framework enabling Java developers to quickly and easily
> > > develop robust Data Analytics and Data Management applications on
> Apache
> > > Hadoop. Chris has been involved in the Hadoop community since the
> > project's
> > > early days.
> > > * Keys Botzum was at IBM, where he worked on security and distributed
> > > systems, and is currently at MapR Technologies.
> > > * Gera Shegalov was at Oracle, where he worked on networking, storage
> and
> > > database kernels, and is currently at MapR Technologies.
> > > * Ryan Rawson is the VP Engineering of Drawn to Scale where he
> developed
> > > Spire, a real-time operational database for Hadoop. He is also a
> > committer
> > > and PMC member for Apache HBase, and has a long history of
> contributions
> > to
> > > open source. Ryan has been involved in the Hadoop community since the
> > > project's early days.
> > >
> > > We realize that additional employer diversity is needed, and we will
> work
> > > aggressively to recruit developers from additional companies.
> > >
> > > Alignment
> > > =========
> > > The initial committers strongly believe that a system for interactive
> > > analysis of large-scale datasets will gain broader adoption as an open
> > > source, community driven project, where the community can contribute
> not
> > > only to the core components, but also to a growing collection of query
> > > languages and optimizers, data formats, data formats, and execution
> > engine
> > > operators and connectors. Drill will integrate closely with Apache
> > Hadoop.
> > > First, the data will live in Hadoop. That is, Drill will support Hadoop
> > > FileSystem implementations and HBase. Second, Hadoop-related data
> formats
> > > will be supported (eg, Apache Avro, RCFile). Third, MapReduce-based
> tools
> > > will be provided to produce column-based formats. Fourth, Drill tables
> > can
> > > be registered in HCatalog. Finally, Hive is being considered as the
> basis
> > > of the DrQL implementation.
> > >
> > > Known Risks
> > > ===========
> > >
> > > Orphaned Products
> > > =================
> > > The contributors are leading vendors in this space, with significant
> open
> > > source experience, so the risk of being orphaned is relatively low. The
> > > project could be at risk if vendors decided to change their strategies
> in
> > > the market. In such an event, the current committers plan to continue
> > > working on the project on their own time, though the progress will
> likely
> > > be slower. We plan to mitigate this risk by recruiting additional
> > > committers.
> > >
> > > Inexperience with Open Source
> > > =============================
> > > The initial committers include veteran Apache members (committers and
> PMC
> > > members) and other developers who have varying degrees of experience
> with
> > > open source projects. All have been involved with source code that has
> > been
> > > released under an open source license, and several also have experience
> > > developing code with an open source development process.
> > >
> > > Homogenous Developers
> > > =====================
> > > The initial committers are employed by a number of companies, including
> > > MapR Technologies, Concurrent and Drawn to Scale. We are committed to
> > > recruiting additional committers from other companies.
> > >
> > > Reliance on Salaried Developers
> > > ===============================
> > > It is expected that Drill development will occur on both salaried time
> > and
> > > on volunteer time, after hours. The majority of initial committers are
> > paid
> > > by their employer to contribute to this project. However, they are all
> > > passionate about the project, and we are confident that the project
> will
> > > continue even if no salaried developers contribute to the project. We
> are
> > > committed to recruiting additional committers including non-salaried
> > > developers.
> > >
> > > Relationships with Other Apache Products
> > > ========================================
> > > As mentioned in the Alignment section, Drill is closely integrated with
> > > Hadoop, Avro, Hive and HBase in a numerous ways. For example, Drill
> data
> > > lives inside a Hadoop environment (Drill operates on in situ data). We
> > look
> > > forward to collaborating with those communities, as well as other
> Apache
> > > communities.
> > >
> > > An Excessive Fascination with the Apache Brand
> > > ==============================================
> > > Drill solves a real problem that many organizations struggle with, and
> > has
> > > been proven within Google to be of significant value. The architecture
> is
> > > based on academic and industry research. Our rationale for developing
> > Drill
> > > as an Apache project is detailed in the Rationale section. We believe
> > that
> > > the Apache brand and community process will help us attract more
> > > contributors to this project, and help establish ubiquitous APIs. In
> > > addition, establishing consensus among users and developers of a
> > > Dremel-like tool is a key requirement for success of the project.
> > >
> > > Documentation
> > > =============
> > > Drill is inspired by Google’s Dremel. Google has published a paper
> > > highlighting Dremel’s innovative nested column-based data format and
> > > execution engine: http://research.google.com/pubs/pub36632.html
> > >
> > > High-level slides have been published by MapR: TODO
> > >
> > > Initial Source
> > > ==============
> > > There is no initial source code. All source code will be developed
> within
> > > the Apache Incubator.
> > >
> > > Cryptography
> > > ============
> > > Drill will eventually support encryption on the wire. This is not one
> of
> > > the initial goals, and we do not expect Drill to be a controlled export
> > > item due to the use of encryption.
> > >
> > > Required Resources
> > > ==================
> > >
> > > Mailing List
> > > ============
> > > * drill-private
> > > * drill-dev
> > > * drill-user
> > >
> > > Subversion Directory
> > > ====================
> > > Git is the preferred source control system: git://git.apache.org/drill
> > >
> > > Issue Tracking
> > > ==============
> > > JIRA Drill (DRILL)
> > >
> > > Initial Committers
> > > ==================
> > > * Tomer Shiran (tshiran at maprtech dot com)
> > > * Ted Dunning (tdunning at apache dot org)
> > > * Jason Frantz (jfrantz at maprtech dot com)
> > > * MC Srivas (mcsrivas at maprtech dot com)
> > > * Chris Wensel (chris and concurrentinc dot com)
> > > * Keys Botzum (kbotzum at maprtech dot com)
> > > * Gera Shegalov (gshegalov at maprtech dot com)
> > > * Ryan Rawson (ryan at drawntoscale dot com)
> > >
> > > Affiliations
> > > ============
> > > The initial committers are employees of MapR Technologies, Drawn to
> Scale
> > > and Concurrent. The nominated mentors are employees of MapR
> Technologies,
> > > Lucid Imagination and Nokia.
> > >
> > > Sponsors
> > > ========
> > >
> > > Champion
> > > ========
> > > Ted Dunning (tdunning at apache dot org)
> > >
> > > Nominated Mentors
> > > =================
> > > * Ted Dunning (tdunning at apache dot org) – Chief Application
> Architect
> > at
> > > MapR Technologies, Committer for Lucene, Mahout and ZooKeeper.
> > > * Grant Ingersoll (grant at lucidimagination dot com) – Chief Scientist
> > at
> > > Lucid Imagination, Committer for Lucene, Mahout and other projects.
> > > * Isabel Drost (Isabel at apache dot org) – Software Developer at Nokia
> > > Gate 5 GmbH, Committer for Lucene, Mahout and other projects.
> > >
> > > Sponsoring Entity
> > > =================
> > > Incubator
> >
> > ---------------------------------------------------------------------
> > To unsubscribe, e-mail: general-unsubscribe@incubator.apache.org
> > For additional commands, e-mail: general-help@incubator.apache.org
> >
> >
>



-- 
Tomer Shiran
Director of Product Management | MapR Technologies | 650-804-8657

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