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From Camuel Gilyadov <cam...@gmail.com>
Subject Re: Drill reading links
Date Sun, 26 Aug 2012 00:11:24 GMT
Hi everyone,

We have put together a design proposal for Apache Drill based on our
two-year experience with OpenDremel.

The proposal: http://www.slideshare.net/CamuelGilyadov/apache-drill-14071739.
It is veyr high-level and definitely needs more elaboration, I suggest
using this mailing list for that.

Regarding to the overall architecture described below, it seems consistent
with our proposed design. The storage-format component is part of query
compiler, or more accurately a code-template library which query compiler
uses to generate query plan. I think restricting it to DAG doesn't bring
any extra benefit, it hard to think of query plan which is not DAG but why
restrict backend without clear benefit? The main point behind proposed
design is to make nodes completely generic, capable of executing any
arbitrary code and it seems in line with mentioned Dryad architecture.

Please feel free to ask us any question regarding the proposed design or
OpenDremel/Dazo in general.

As time allows we would elaborate specific topics in our blog:
http://bigdatacraft.com with crosslink here.

Looking forward for a design document...

On Sun, Aug 26, 2012 at 2:36 AM, Jason Frantz <jfrantz@maprtech.com> wrote:

> Hi everyone,
> Before sending out an architecture doc, I wanted to send out a set of links
> to systems or research that have been influencing our design. Google's
> Dremel paper [1] does a good job at summarizing the use case of fast
> analytics, but is quite short on the actual system structure. In addition,
> we'd like to support some data models and execution patterns outside of
> what's mentioned in that paper.
> The overall picture can be very roughly broken down into three overlapping
> components. The first is the query language and data model exposed to the
> user. Our inspirations here are
> - SQL
> - BigQuery [2], which has a SQL-like language wrapped around a protocol
> buffer data model [3]
> - MongoDB, which has a JSON-derived data model
> The second component is the execution engine. The basic model is that each
> query is a data flow program structured as a DAG of execution nodes, as
> expressed in Microsoft's Dryad paper [4]. Each node in the DAG is an
> operator that may be run across many machines. For examples of operators,
> see SQL Server [5].
> The third component is the storage format. There are several distinct types
> of formats we want to support:
> - Row-based w/o schema, e.g. JSON, CSV
> - Row-based w/ schema, e.g. traditional SQL, protobufs
> - Columnar-based w/ schema, e.g. columnar databases [6], Dremel, RCFile
> Rather than relying on the user carefully creating a series of prebuilt
> indexes for anything they want to query, we'd like to rely on in-situ
> processing whenever possible. This includes adaptive indexing techniques
> like "database cracking" [7] as well as the ability to efficiently process
> "raw data" [8]. In addition, since we want to support several distinct data
> formats we need to transfer between those formats. One example is varying
> between JSON, which doesn't have a consistent "schema" from one row to the
> next, and protobufs, which do. Another example is the conversion from
> columnar format to row format [9].
> Please feel free to chime in with other references that the project should
> be looking into.
> -Jason
> [1] http://research.google.com/pubs/pub36632.html
> [2] https://developers.google.com/bigquery/docs/query-reference
> [3] https://developers.google.com/protocol-buffers/docs/proto
> [4] http://research.microsoft.com/en-us/projects/dryad/
> [5] http://msdn.microsoft.com/en-us/library/ms191158.aspx
> [6] http://db.csail.mit.edu/projects/cstore/
> [7] http://pdf.aminer.org/000/094/728/database_cracking.pdf
> [8] http://homepages.cwi.nl/~idreos/NoDBsigmod2012.pdf
> [9] http://db.csail.mit.edu/projects/cstore/abadiicde2007.pdf

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