In this demonstration, we will showcase Myria, our novel cloud service for big data management and analytics designed to improve productivity. Myria's goal is for users to simply upload their data and for the system to help them be self-sufficient data science experts on their data -- self-serve analytics. Using a web browser, Myria users can upload data, author efficient queries to process and explore the data, and debug correctness and performance issues. Myria queries are executed on a scalable, parallel cluster that uses both state-of-the-art and novel methods for distributed query processing. Our interactive demonstration will guide visitors through an exploration of several key Myria features by interfacing with the live system to analyze big datasets over the web.

Traditional indexing techniques are not well suited for complex data types such as spatial, spatio-temporal, and multimedia data types, where an instance is a composite of multiple components. In this paper we propose two indexing techniques that allow the parts of a composite object to be indexed separately, called multiple entry indexing and double indexing. We present the implementation of these approaches in the SECONDO extensible database system. The improvements in terms of performance of both approaches presented in this paper are shown in an experimental evaluation.

One of the most important kind of queries in spatial data-bases to support location-based services (LBS) is the continuous nearest neighbors (CNN) query. Given a spatial data set of points of interest and a moving query point q, the CNN query partitions q into a set of adjacent disjoint intervals associated with their nearest points of interest. Existing solutions to this problem are known to be sub-optimal in terms of disk accesses. In this paper, we present an algorithm to compute the CNN query that is I/O optimal. With an experimental evaluation, we show that not only the number of disk accesses is reduced with the optimal algorithm, but also the CPU performance is improved, in some cases.

In the real world, lots of objects with changing position can be found. Some of them repeat the same movement several times, called periodic movements. Examples include airplanes, trains, planets, and marine turtles. This paper describes a model for representing the periodic movements to be stored in a database system, exploiting the information about the repetitions. The model is generic enough to represent any kind of movement, not being restricted to objects with repetitions in their movement. We present algorithms to detect the repetitions and to convert to the periodic representation as well as the implementation of some operations on such representation. We show, in an experimental evaluation against the so-called flat representation, that the approach presented in this paper significantly improves the performance of query processing in a database system when dealing with objects with some periodic movement. We also show that, for the worst case where the objects do not follow any periodic movement at all, our approach still performs acceptably.

Representing descriptions of movements in databases and querying them is a basic capability required in mobile data management. In this demonstration, we show for the first time a prototype implementing a data model and query language for moving objects (trajectories) completely integrated into a DBMS environment, including query optimization and user interface issues such as animation.

The goal of SECONDO is to provide a "generic" database system frame that can be filled with implementations of various DBMS data models. SECONDO was intended originally as a platform for implementing and experimenting with new kinds of data models, especially to support spatial, spatio-temporal, and graph database models. We now feel, SECONDO has a clean architecture, and it strike a reasonable balance between simplicity and sophistication. Since all the source code is accessible and to a large extent comprehensible for students, we believe it is also an excellent tool for teaching database architecture and implementation concepts. SECONDO runs on Windows, Linux, and Solaris platforms, and consists of three major components SECONDO kernel, optimizer, and graphical user interface.