Jihad Boulos

MYSTIQ: a system for finding more answers by using probabilities

MystiQ is a system that uses probabilistic query semantics [3] to find answers in large numbers of data sources of less than perfect quality. There are many reasons why the data originating from many different sources may be of poor quality, and therefore difficult to query: the same data item may have different representation in different sources; the schema alignments needed by a query system are imperfect and noisy; different sources may contain contradictory information, and, in particular, their combined data may violate some global integrity constraints; fuzzy matches between objects from different sources may return false positives or negatives. Even in such environment, users some-times want to ask complex, structurally rich queries, using query constructs typically found in SQL queries: joins, subqueries, existential/universal quantifiers, aggregate and group-by queries: for example scientists may use such queries to query multiple scientific data sources, or a law enforcement agency may use it in order to find rare associations from multiple data sources. If standard query semantics were applied to such queries, all but the most trivial queries will return an empty answer.

Cost estimation of user-defined methods in object-relational database systems

In this paper we present a novel technique for cost estimation of user-defined methods in advanced database systems. This technique is based on multi-dimensional histograms. We explain how the system collects statistics on the method that a database user defines and adds to the system. From these statistics a multi-dimensional histogram is built. Afterwards, this histrogram can be used for estimating the cost of the target method whenever this method is referenced in a query. This cost estimation is needed by the optimizer of the database system since this cost estimation needs to know the cost of a method in order to place it at its optimal position in the Query Execution Plan (QEP). We explain here how our technique works and we provide an example to better verify its functionality.

A new design for a native XML storage and indexing manager

This paper describes the design and implementation of an XML storage manager for fast and interactive XPath expressions evaluation. This storage manager has two main parts: the XML data storage structure and the index over this data. The system is designed in such a way that it minimizes the number of page reads for retrieving any XPath expression results while avoiding the shortcomings of previous work on storing XML data where the index must adapt to the most frequent queries. Hence, the main advantage of our index is that it can handle any new XPath expression without any need for adaptation. We show comparable performance of our design by presenting path evaluation results of our index against those of the currently most known index on documents of different sizes.

Continuous Data Management on Tape-Based Tertiary Storage Systems

Video-on-Demand (VOD) servers are becoming feasible. These servers have voluminous data to store and manage. A tape-based tertiary storage system seems to be a reasonable solution to lowering the cost of storage and management of this continuous data. In this paper we address the issues of decomposing and placing continuous data blocks on tapes, and the scheduling of multiple requests for materializing objects from tapes to disks. We first study different policies for continuous object decomposition and blocks placement on tapes under different characteristics of the tertiary storage drives. Afterwards, we propose a scheduling algorithm for object materialization.

XQueryViz: an XQuery visualization tool

We present in this demo the description of XQueryViz: an XQuery visualization tool. This graphical tool can parse one or more XML documents and/or schemas and visualizes them as trees with zooming, expansion and contraction functionality. The tool can also parse a textual XQuery and visualizes it as a DAG within two different windows: the first for the querying part (i.e. For-Let-Where clauses) and the second for the “Return” clause. More importantly, users can build XQuery queries with this graphical tool by pointing and clicking on the visual XML trees to build the XPath parts of an XQuery and then build the whole XQuery using visual constructs and connectors. A textual XQuery is then generated.

XQueryViz: A Visual Dataflow XQuery Tool

In this paper we introduce a dataflow-like visual syntax for writing XQueries. We also describe the functionalities, capabilities and pitfalls of the environment/prototype that supports the construction of visual XQueries. Our prototype allows users to visualize an XML schema, and makes use of its visual representation, using direct manipulation, to build the XPath of an XQuery. It also supports a round trip conversion; that is it converts a textual XQuery to a visual one and vice versa. To evaluate the usability of our visual syntax and the prototype in which the visual XQuery can be built, we have designed a case study to detect the strength and weaknesses of our approach. The results of the subjects we studied show that our approach of writing visual XQueries, using a visual dataflow-like syntax suffers from the lack of strict dataflow syntax and semantics. In future work we intend to address this issue and further improve on what we now have.

VOD data management on tape-based tertiary storage systems

Video-on-Demand servers are becoming feasible. These servers have voluminous data to store and manage. If only disk-based secondary storage systems are used to store and manage this huge amount of data the system cost would be extensively high. A tape-based tertiary storage system seems to be a reasonable solution to lowering the cost of storage and management of this continuous data. However, the usage of a tertiary storage system to store large continuous data introduces several issues. These are mainly the replacement policy on disks, the decomposition and the placement of continuous data chunks on tapes, and the scheduling of multiple requests for materializing objects from tapes to disks. In this paper we address these issues and we proposed solutions based on some heuristics we experimented in a simulator. We first extend a replacement policy that has been proposed for a single user environment to a multi-user one with several servicing streams. We then study different policies for continuous object decomposition and chunks placement on tapes under different characteristics of the tertiary storage drives. Finally, we propose a scheduling algorithm for object materialization; this algorithm guarantees the materialization on disks of all chunks of an object at their service deadlines in a pipelined service. We present the results of some simulations we made to measure the impacts of our proposed algorithms on the average latency time of the system.

Performance evaluation of the OLVP (online video processing) system

The paper discusses how the OLVP system, an innovative video-on-demand system, can be used to efficiently support video delivery applications over an asynchronous transfer mode (ATM) network. We show how the OLVP system provided a high quality of service (QoS) to video applications executing over a set of distributed and heterogeneous system resources. System architecture is described. Key functionality, including distributed video storage management, real-time admission control strategy and resource allocation routing mechanism, traffic management and routing algorithms (both in the ATM network and in the OLVP system) are investigated. To illustrate the success of our approach, we provide a performance evaluation based on simulations of the system.