Anomaly detection is an important problem that has been researched within diverse research areas and application domains. Many anomaly detection techniques have been specifically developed for certain application domains, while others are more generic. This survey tries to provide a structured and comprehensive overview of the research on anomaly detection. We have grouped existing techniques into different categories based on the underlying approach adopted by each technique. For each category we have identified key assumptions, which are used by the techniques to differentiate between normal and anomalous behavior. When applying a given technique to a particular domain, these assumptions can be used as guidelines to assess the effectiveness of the technique in that domain. For each category, we provide a basic anomaly detection technique, and then show how the different existing techniques in that category are variants of the basic technique. This template provides an easier and more succinct understanding of the techniques belonging to each category. Further, for each category, we identify the advantages and disadvantages of the techniques in that category. We also provide a discussion on the computational complexity of the techniques since it is an important issue in real application domains. We hope that this survey will provide a better understanding of the different directions in which research has been done on this topic, and how techniques developed in one area can be applied in domains for which they were not intended to begin with.

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Anomaly detection: A survey

XML is quickly becoming the de facto standard for data exchange over the Internet. This is creating a new set of data management requirements involving XML, such as the need to store and query XML documents. Researchers have proposed using relational database systems to satisfy these requirements by devising ways to "shred" XML documents into relations, and translate XML queries into SQL queries over these relations. However, a key issue with such an approach, which has largely been ignored in the research literature, is how (and whether) the ordered XML data model can be efficiently supported by the unordered relational data model. This paper shows that XML's ordered data model can indeed be efficiently supported by a relational database system. This is accomplished by encoding order as a data value. We propose three order encoding methods that can be used to represent XML order in the relational data model, and also propose algorithms for translating ordered XPath expressions into SQL using these encoding methods. Finally, we report the results of an experimental study that investigates the performance of the proposed order encoding methods on a workload of ordered XML queries and updates.

http://db.ucsd.edu/static/cse232b-archive/papers/tatarinov02.pdf

Storing and querying ordered XML using a relational database system

https://www.cse.unsw.edu.au/~cs9314/07s1/lectures/Lin_CS9314_References/cm-latin.pdf

An improved data stream summary: the count-min sketch and its applications

Graph database models can be defined as those in which data structures for the schema and instances are modeled as graphs or generalizations of them, and data manipulation is expressed by graph-oriented operations and type constructors. These models took off in the eighties and early nineties alongside object-oriented models. Their influence gradually died out with the emergence of other database models, in particular geographical, spatial, semistructured, and XML. Recently, the need to manage information with graph-like nature has reestablished the relevance of this area. The main objective of this survey is to present the work that has been conducted in the area of graph database modeling, concentrating on data structures, query languages, and integrity constraints.

/pdf/survey-of-graph-database-models-2ssdmgcn9a.pdf

Survey of graph database models

The problem of answering queries using views is to find efficient methods of answering a query using a set of previously defined materialized views over the database, rather than accessing the database relations. The problem has recently received significant attention because of its relevance to a wide variety of data management problems. In query optimization, finding a rewriting of a query using a set of materialized views can yield a more efficient query execution plan. To support the separation of the logical and physical views of data, a storage schema can be described using views over the logical schema. As a result, finding a query execution plan that accesses the storage amounts to solving the problem of answering queries using views. Finally, the problem arises in data integration systems, where data sources can be described as precomputed views over a mediated schema. This article surveys the state of the art on the problem of answering queries using views, and synthesizes the disparate works into a coherent framework. We describe the different applications of the problem, the algorithms proposed to solve it and the relevant theoretical results.

/pdf/answering-queries-using-views-a-survey-4aug5icc6d.pdf

Answering queries using views: A survey

XML is fast emerging as the dominant standard for representing data in the World Wide Web. Sophisticated query engines that allow users to effectively tap the data stored in XML documents will be crucial to exploiting the full power of XML. While there has been a great deal of activity recently proposing new semistructured data models and query languages for this purpose, this paper explores the more conservative approach of using traditional relational database engines for processing XML documents conforming to Document Type Descriptors (DTDs). To this end, we have developed algorithms and implemented a prototype system that converts XML documents to relational tuples, translates semi-structured queries over XML documents to SQL queries over tables, and converts the results to XML. We have qualitatively evaluated this approach using several real DTDs drawn from diverse domains. It turns out that the relational approach can handle most (but not all) of the semantics of semi-structured queries over XML data, but is likely to be effective only in some cases. We identify the causes for these limitations and propose certain extensions to the relational model that would make it more appropriate for processing queries over XML documents.

/pdf/relational-databases-for-querying-xml-documents-limitations-1i9sh816c1.pdf

Relational Databases for Querying XML Documents: Limitations and Opportunities

Virtually all proposals for querying XML include a class of query we term “containment queries”. It is also clear that in the foreseeable future, a substantial amount of XML data will be stored in relational database systems. This raises the question of how to support these containment queries. The inverted list technology that underlies much of Information Retrieval is well-suited to these queries, but should we implement this technology (a) in a separate loosely-coupled IR engine, or (b) using the native tables and query execution machinery of the RDBMS? With option (b), more than twenty years of work on RDBMS query optimization, query execution, scalability, and concurrency control and recovery immediately extend to the queries and structures that implement these new operations. But all this will be irrelevant if the performance of option (b) lags that of (a) by too much. In this paper, we explore some performance implications of both options using native implementations in two commercial relational database systems and in a special purpose inverted list engine. Our performance study shows that while RDBMSs are generally poorly suited for such queries, under conditions they can outperform an inverted list engine. Our analysis further identifies two significant causes that differentiate the performance of the IR and RDBMS implementations: the join algorithms employed and the hardware cache utilization. Our results suggest that contrary to most expectations, with some modifications, a native implementations in an RDBMS can support this class of query much more efficiently.

/pdf/on-supporting-containment-queries-in-relational-database-2wtbusg70b.pdf

On supporting containment queries in relational database management systems

Physical database design is important for query performance in a shared-nothing parallel database system, in which data is horizontally partitioned among multiple independent nodes. We seek to automate the process of data partitioning. Given a workload of SQL statements, we seek to determine automatically how to partition the base data across multiple nodes to achieve overall optimal (or close to optimal) performance for that workload. Previous attempts use heuristic rules to make those decisions. These approaches fail to consider all of the interdependent aspects of query performance typically modeled by today's sophisticated query optimizers.We present a comprehensive solution to the problem that has been tightly integrated with the optimizer of a commercial shared-nothing parallel database system. Our approach uses the query optimizer itself both to recommend candidate partitions for each table that will benefit each query in the workload, and to evaluate various combinations of these candidates. We compare a rank-based enumeration method with a random-based one. Our experimental results show that the former is more effective.

/pdf/automating-physical-database-design-in-a-parallel-database-mywg847ygx.pdf

Automating physical database design in a parallel database

Many projections envision a future in which the Internet is populated with a vast number of Web-accessible XML files—a “World-Wide Database”. Recently, there has been a great deal of research into XML query languages to enable the execution of database-style queries over these XML files. However, merely being an XML query-processing engine does not render a system suitable for querying the Internet. A truly useful system must provide mechanisms to (a) find the XML files that are relevant to a given query, and (b) deal with remote data sources that either provide unpredictable data access and transfer rates, or are infinite streams, or both. The Niagara Internet Query System was designed from the bottom-up to provide these mechanisms. It finds relevant XML documents by using a novel collaboration between the Niagara XML-QL query processor and the Niagara “text-in-context” XML search engine. To handle infinite streams and data sources with unpredictable rates, it supports a “get partial” operation on blocking operators in order to produce partial query results, and inserts synchronization packets at critical points in the operator tree to guarantee the consistency of (partial) results. The Niagara Internet Query System is public domain software that can be found at http://www-db.cs.wisc.edu/niagara/. Category: Research.

/pdf/the-niagara-internet-query-system-17ktu9wu9v.pdf

Chun Zhang

Papers

Storing and querying ordered XML using a relational database system

Relational Databases for Querying XML Documents: Limitations and Opportunities

On supporting containment queries in relational database management systems

Automating physical database design in a parallel database

The Niagara Internet Query System.