Google Fusion Tables aims to support an ecosystem of structured data on the Web by providing a tool for managing and visualizing data on the one hand, and for searching and exploring for data on the other. This paper describes a few recent developments in our efforts to further the ecosystem.

We consider the problem of finding related tables in a large corpus of heterogenous tables. Detecting related tables provides users a powerful tool for enhancing their tables with additional data and enables effective reuse of available public data. Our first contribution is a framework that captures several types of relatedness, including tables that are candidates for joins and tables that are candidates for union. Our second contribution is a set of algorithms for detecting related tables that can be either unioned or joined. We describe a set of experiments that demonstrate that our algorithms produce highly related tables. We also show that we can often improve the results of table search by pulling up tables that are ranked much lower based on their relatedness to top-ranked tables. Finally, we describe how to scale up our algorithms and show the results of running it on a corpus of over a million tables extracted from Wikipedia.

Many data-driven social and Web applications involve collaboration and coordination. The vision of Declarative Data-Driven Coordination (D3C), proposed in Kot et al. [2010], is to support coordination in the spirit of data management: to make it data-centric and to specify it using convenient declarative languages. This article introduces entangled queries , a language that extends SQL by constraints that allow for the coordinated choice of result tuples across queries originating from different users or applications. It is nontrivial to define a declarative coordination formalism without arriving at the general (NP-complete) Constraint Satisfaction Problem from AI. In this article, we propose an efficiently enforceable syntactic safety condition that we argue is at the sweet spot where interesting declarative power meets applicability in large-scale data management systems and applications. The key computational problem of D3C is to match entangled queries to achieve coordination. We present an efficient matching algorithm which statically analyzes query workloads and merges coordinating entangled queries into compound SQL queries. These can be sent to a standard database system and return only coordinated results. We present the overall architecture of an implemented system that contains our evaluation algorithm. We also describe a proof-of-concept Facebook application we have built on top of this system to allow friends to coordinate flight plans. Finally, we evaluate the performance of the matching algorithm experimentally on realistic coordination workloads.

In a previous paper, we laid out the vision of declarative data-driven coordination (D3C) where users are provided with novel abstractions that enable them to communicate and coordinate through declarative specifications [3].

Many data-driven social and Web applications involve collaboration and coordination. The vision of declarative data-driven coordination (D3C), proposed in [9], is to support coordination in the spirit of data management: to make it data-centric and to specify it using convenient declarative languages. This paper introduces entangled queries, a language that extends SQL by constraints that allow for the coordinated choice of result tuples across queries originating from different users or applications.

In this paper, we propose a distributed model for massive scalability in net-VEs. Our model inherits concepts from distributed databases, where the application logic and transaction processing take place at the client machine. The key feature of our model is its novel transaction model, which exploits application semantics to reduce the number of messages needed to maintain consistency. Our proposed model imposes no major restrictions on the interaction between participants located in different parts of the world, and so can be easily adapted to a wide range of net-VEs.

We propose to demonstrate SGL, a language and system for writing computer games using data management techniques. We will demonstrate a complete game built using the system, and show how complex game behavior can be expressed in a declarative scripting language. The demo will also illustrate the workflow necessary to modify a game and include a visualization of the relational operations that are executed as the game runs.

We propose to demonstrate SEMMO, a consistency server for MMOs. The key features of SEMMO are its novel distributed consistency protocol and system architecture. The distributed nature of the engine allows the clients to perform all computations locally; the only computation that the central server performs is to determine the serialization order of game actions.

An emerging trend in Social Networking sites and Web portals is the opening up of their APIs to external application developers. For example, the Facebook Platform, Google Gadgets and Yahoo! Widgets allow developers to design their own applications, which can then can be integrated with the platform and shared with other users. However, current APIs are targeted towards developers with programming expertise and database knowledge; they are not accessible to a large class of users who do not have a programming/database background, but would nevertheless like to create new applications. To address this need, we have developed the AppForge system, which provides a WYSIWYG application development platform. Users can graphically specify the components of webpages inside a Web browser, and the corresponding database schema and application logic will be automatically generated on the fly by the system. The WYSIWYG interface gives instantaneous feedback on what users have created and allows them to run, test and continuously refine their applications. AppForge has been used to create prototype versions of a variety of applications such as an event planning system, a recruiting system, an item trading system and an online course management system. We have also conducted a small and preliminary user study to identify and fix some of the usability aspects of AppForge.

The popularity of XML as a data exchange standard has led to the emergence of powerful XML query languages like XQuery and studies on XML query optimization. Of late, there is considerable interest in analytical processing of XML data. As pointed out by Borkar and Carey, even for data integration, there is a compelling need for performing various group-by style aggregate operations. A core operator needed for analytics is the group-by operator, which is widely used in relational as well as OLAP database applications. XQuery requires group-by operations to be simulated using nesting.

We describe a novel programming model for building, extending, and personalizing web-based data-driven applications.

Data-driven web applications are usually structured in three tiers with different programming models at each tier. This division forces developers to manually partition application functionality across the tiers, resulting in complex logic, suboptimal partitioning, and expensive re-partitioning of applications. In this paper, we introduce a unified platform for automatic partitioning of data-driven web applications. Our approach is based on Hilda[41, 46], a high-level declarative programming language with a unified data and programming model for all the layers of the application. Based on run-time properties of the application, Hilda's run time system automatically partitions the application between the tiers to improve response time while adhering to memory and/ or processing constraints at the clients. We evaluate our methodology with traces from a real application and with TPC-W, and our results show that automatic partitioning outperforms manual partitioning without the associated development overhead.