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 <[email protected]>
Authored: Mon Sep 3 13:21:32 2012 -0700
Committer: Ted Dunning <[email protected]>
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
+
