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