The telco industry is gradually shifting from using monolithic software packages deployed on custom hardware to using modular virtualized software functions deployed on cloudified data centers using commodity hardware. This transformation is referred to as Network Function Virtualization (NFV). The scalability of the databases (DBs) underlying the virtual network functions is the cornerstone for reaping the benefits from the NFV transformation. This paper presents an industrial experience of applying shared-nothing techniques in order to achieve the scalability of a DB in an NFV setup. The special combination of requirements in NFV DBs are not easily met with conventional execution models. Therefore, we designed a special shared-nothing architecture that is based on cooperative multi-tasking using user-level threads (fibers). We further show that the fiber-based approach outperforms the approach built using conventional multi-threading and meets the variable deployment needs of the NFV transformation. Furthermore, fibers yield a simpler-to-maintain software and enable controlling a trade-off between long-duration computations and real-time requests.

The increasing amount of graph like data from social networks, science and the web has grown an interest in analyzing the relationships between different entities. New specialized solutions in the form of graph databases, which are generic and able to adapt to any schema as an alternative to RDBMS, have appeared to manage attributed multigraphs efficiently. In this paper, we describe the internals of DEX graph database, which is based on a representation of the graph and its attributes as maps and bitmap structures that can be loaded and unloaded efficiently from memory. We also present the internal operations used in DEX to manipulate these structures. We show that by using these structures, DEX scales to graphs with billions of vertices and edges with very limited memory requirements. Finally, we compare our graph-oriented approach to other approaches showing that our system is better suited for out-of-core typical graph-like operations.

In this demonstration we show the Bibliographic Exploration tool BIBEX. BIBEX is based on the graph database query engine DEX and integrates both the Citeseer and DBLP databases. BIBEX can be found in our web site at www.dama.upc.edu/bibex.

Link and graph analysis tools are important devices to boost the richness of information retrieval systems. Internet and the existing social networking portals are just a couple of situations where the use of these tools would be beneficial and enriching for the users and the analysts. However, the need for integrating different data sources and, even more important, the need for high performance generic tools, is at odds with the continuously growing size and number of data repositories.

Record Linkage (RL) is an important component of data cleansing and integration. For years, many efforts have focused on improving the performance of the RL process, either by reducing the number of record comparisons or by reducing the number of attribute comparisons, which reduces the computational time, but very often decreases the quality of the results. However, the real bottleneck of RL is the post-process, where the results have to be reviewed by experts that decide which pairs or groups of records are real links and which are false hits. In this paper, we show that exploiting the relationships (e.g. foreign key) established between one or more data sources, makes it possible to find a new sort of semantic blocking method that improves the number of hits and reduces the amount of review effort.