3D Illustration

QUIS: Query Heterogeneous Data In-Situ

3D Illustration
Image: Adobe Stock | Ezume Images
Information

Startdate: 2011-09-01

Finishdate: 2017-12-31

Status: completed

Description

Data of interest are often found in a variety of data sources, many of which are not relational databases, but have their own data organization and query capabilities. To answer questions of interest, one has to run queries across data from these heterogeneous sources. The traditional approach is to perform multiple individual data transformation tasks, one per data source, to import the data into a common repository where they can be queried and analyzed. Drawbacks of this approach include the manual effort and the cost of transforming and importing potentially large data sets, and the lost opportunity to exploit any query facilities provided by the data sources.

QUIS (QUery In-Situ) proposes an approach for querying the data “in-situ” to the greatest extent possible, by taking the user query and transforming appropriate portions of it into corresponding query expressions on individual data sources. Realizing this approach requires the development of a unified query model. This model can extract sub-queries matching heterogeneous capabilities of individual sources, perform heterogeneous joins on intermediate results as necessary, and deal with barriers such as incompatible type systems en route.

Early experiments have shown that QUIS almost eliminates the time to prepare the data while paying only a small cost in query execution time compared to a fully integrated, indexed, and loaded relational database.

The system is an open source project maintained on GithubExternal link. It consists of a query execution engineExternal linkGUI and command line based clientsExternal link, and an R package, RQUISExternal link, to provide the functionality from inside R.

A set of executableExternal link versions and their documentationsExternal link are available online. Also, a Docker imageExternal link is provided for easy installation on Linux machines as well as on private or public clouds. You can pull the image by issuing this command on your terminal: docker pull javadch/rquis

Member:
Birgitta König-RiesExternal link
Barzan Mozafari
H.V. Jagadish

Former Member:
Javad Chamanara