Jennifer Widom

Learn More
In this overview paper we motivate the need for and research issues arising from a new model of data processing. In this model, data does not take the form of persistent relations, but rather arrives in multiple, continuous, rapid, time-varying <i>data streams.</i> In addition to reviewing past work relevant to data stream systems and current projects in(More)
CQL, a continuous query language, is supported by the STREAM prototype data stream management system (DSMS) at Stanford. CQL is an expressive SQL-based declarative language for registering continuous queries against streams and stored relations. We begin by presenting an abstract semantics that relies only on “black-box” mappings among streams and(More)
Recent web search techniques augment traditional text matching with a global notion of "importance" based on the linkage structure of the web, such as in Google's PageRank algorithm. For more refined searches, this global notion of importance can be specialized to create personalized views of importance--for example, importance scores can be biased(More)
In semistructured databases there is no schema fixed in advance. To provide the benefits of a schema in such environments, we introduce DataGuides: concise and accurate structural summaries of semistructured databases. DataGuides serve as dynamic schemas, generated from the database; they are useful for browsing database structure, formulating queries,(More)
language, designed for querying semistructured data. Semistructured data is becoming more and more prevalent, e.g., in structured documents such as HTML and when performing simple integration of data from multiple sources. Traditional data models and query languages are inappropriate, since semistructured data often is irregular: some data is missing,(More)
STREAM is a general-purpose relational Data Stream Management System (DSMS). STREAM supports a declarative query language and flexible query execution plans. It is designed to cope with high data rates and large numbers of continuous queries through careful resource allocation and use, and by degrading gracefully to approximate answers as necessary. A(More)
The goal of the Tsimmis Project is to develop tools that facilitate the rapid integration of heterogeneous information sources that may include both structured and unstructured data This paper gives an overview of the project describ ing components that extract properties from unstructured objects that translate information into a common object model that(More)
<i>GPS</i> (for Graph Processing System) is a complete open-source system we developed for scalable, fault-tolerant, and easy-to-program execution of algorithms on extremely large graphs. This paper serves the dual role of describing the GPS system, and presenting techniques and experimental results for graph partitioning in distributed graph-processing(More)
Lore (for Lightweight Object Repository) is a DBMS designed specifically for managing semistructured information. Implementing Lore has required rethinking all aspects of a DBMS, including storage management, indexing, query processing and optimization, and user interfaces. This paper provides an overview of these aspects of the Lore system, as well as(More)