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
