Commercial Database Management Systems Research Articles

Evaluation of an Implementation of Cross-Row Constraints Using Materialized Views

SQL assertions are a powerful means used to specify cross-row constraints, and have been available in the SQL standard since 1992. Unfortunately, assertions are not supported in commercial database management systems. Although triggers and application programs can be efficiently used to constrain database content, they are more complex to write and more error-prone. The objective of this paper is to analyze whether the use of materialized views could be a viable solution as regards the automatic implementation of SQL assertions. Materialized views are views that physically store the result of a query and are periodically updated. The method consists of defining a materialized view which contains the number of tuples that violate the condition expressed in the assertion. The materialized view will contain a CHECK constraint that guarantees that the number of tuples that violate the assertion is equal to zero. The proposed method is an easy and automatic means of implementing the integrity constraints described using assertions. We have carried out a series of tests, and although triggers perform better than materialized views in most situations, there are some in which materialized views would be an efficient option. They are easily automatable and less error prone than triggers.

CypherDB: A Novel Architecture for Outsourcing Secure Database Processing

CypherDB addresses the problem of protecting the confidentiality of database stored externally in a cloud and enabling efficient computation over it to thwart any curious-but-honest cloud computing service provider. It works by encrypting the entire outsourced database and executing queries over the encrypted data using our novel CypherDB secure processor architecture. To optimize computational efficiency, our proposed processor architecture provides tightly-coupled datapaths that avoid information leakage during database access and query execution. Our simulation using a well-known database benchmark TPC-H over a commercial grade Database Management System (SQLite) demonstrates that our proposed architecture incurs an average of about 10 percent overhead when compared with the same set of operations without secure database processing.

Extending the Kernel of a Relational DBMS with Comprehensive Support for Sequenced Temporal Queries

Many databases contain temporal, or time-referenced, data and use intervals to capture the temporal aspect. While SQL-based database management systems (DBMSs) are capable of supporting the management of interval data, the support they offer can be improved considerably. A range of proposed temporal data models and query languages offer ample evidence to this effect. Natural queries that are very difficult to formulate in SQL are easy to formulate in these temporal query languages. The increased focus on analytics over historical data where queries are generally more complex exacerbates the difficulties and thus the potential benefits of a temporal query language. Commercial DBMSs have recently started to offer limited temporal functionality in a step-by-step manner, focusing on the representation of intervals and neglecting the implementation of the query evaluation engine. This article demonstrates how it is possible to extend the relational database engine to achieve a full-fledged, industrial-strength implementation of sequenced temporal queries, which intuitively are queries that are evaluated at each time point. Our approach reduces temporal queries to nontemporal queries over data with adjusted intervals, and it leaves the processing of nontemporal queries unaffected. Specifically, the approach hinges on three concepts: interval adjustment , timestamp propagation , and attribute scaling . Interval adjustment is enabled by introducing two new relational operators, a temporal normalizer and a temporal aligner, and the latter two concepts are enabled by the replication of timestamp attributes and the use of so-called scaling functions. By providing a set of reduction rules, we can transform any temporal query, expressed in terms of temporal relational operators, to a query expressed in terms of relational operators and the two new operators. We prove that the size of a transformed query is linear in the number of temporal operators in the original query. An integration of the new operators and the transformation rules, along with query optimization rules, into the kernel of PostgreSQL is reported. Empirical studies with the resulting temporal DBMS are covered that offer insights into pertinent design properties of the article's proposal. The new system is available as open-source software.

Enhancing User Authentication and Encrypting Lob Data in OLE DB Provider for Database

Database is widely used in computer systems currently, and OLE DB is the main method for applications to access database on Microsoft's system. In order to store sensitive data in commercial database management system, application often encrypt the data before keeping it into database. UDF (User Defined Function) is helpful for applications in encrypting procedure, but it can't handle Lob (Long object) data. A secure OLE DB provider for enhancing user authentication and encrypting Lob data in database is proposed. By adding necessary attributes of user authentication and cipher algorithm to encrypt Lob data in OLE DB provider, the security of data stored in database is improved. Experiments show that the proposed OLE DB provider is transparent, efficient, easy to implement and reliable.

GLAP : A Global Loopback Anomaly Prevention Mechanism for Multi-Level Distributed Transactions

The multi-level/hierarchical distributed transaction execution model is currently the model specified in the database standards and practiced in the implementations of commercial database management systems. In this model, a transaction may execute more than one subtransaction with different origins at a participating site, causing the same transaction to appear more than once at the participating site. This system state is well recognized in the literature and is commonly known as a “loopback”. When a loopback occurs at a site, certain types of anomalies may arise. The effects of these anomalies on the system behaviour vary depending on the type of the anomaly. In an extreme case, a loopback anomaly may lead to non-serializable executions of transactions, sacrificing the consistency of the entire distributed database system. Thus, it is imperative to characterize the different types of loopback anomalies and to provide a practical and efficient solution to those that are most devastating on the system behaviour. This is the focus of this article.

Using Constraint Programming in Selection Operators for Constraint Databases

Constraint Databases represent complex data by means of formulas described by constraints (equations, inequations or Boolean combinations of both). Commercial database management systems allow the storage and efficient retrieval of classic data, but for complex data a made-to-measure solution combined with expert systems for each type of problem are necessary. Therefore, in the same way as commercial solutions of relational databases permit storing and querying classic data, we propose an extension of the Selection Operator for complex data stored, and an extension of SQL language for the case where both classic and constraint data need to be managed. This extension shields the user from unnecessary details on how the information is stored and how the queries are evaluated, thereby enlarging the capacity of expressiveness for any commercial database management system. In order to minimize the selection time, a set of strategies have been proposed, which combine the advantages of relational algebra and constraint data representation.

Schema of Enhancing User Authentication and Encrypting Lob Data in ODBC Driver for Database

For commercial database management system is not suitable for storing sensitive data, the data is often encrypted in application before keeping into database. Using UDF (User Defined Function) can simplify the encrypting procedure, but it can't handle Lob (Long object) data. A schema of enhancing user authentication and encrypting Lob data in ODBC (Open Database Connection) driver for database is prosed. By adding necessary attributes of user authentication and cipher algorithm to encrypt Lob data in ODBC driver, the security of data stored in database is improved. Experiments show that the schema is transparent, efficient, easy to implement and reliable.

Database Analytics: A Reconfigurable-Computing Approach

Businesses are experiencing a growing need for performing real-time analytics on ever-increasing enterprise data. While providing useful business insights and improved market responsiveness, analytics also adds a computational burden on traditional online transaction processing (OLTP) systems and could adversely affect the performance of OLTP workloads. The authors present a highly pipelined, high-throughput query-processing engine on a field-programmable gate array (FPGA) to offload expensive queries for database analytics. The proposed solution provides a mechanism for a database management system (DBMS) to seamlessly harness the FPGA accelerator without requiring any changes in the application or the existing data layout. The authors' system, which uses an off-the-shelf server and a PCIe-attached FPGA card and is integrated into a commercial DBMS platform, achieves an order-of-magnitude speedup on various real-life queries.

On Deferred Constraints in Distributed Database Systems

An atomic commit protocol (ACP) is a distributed algorithm used to ensure the atomicity property of transactions in distributed database systems. Although ACPs are designed to guarantee atomicity, they add a significant extra cost to each transaction execution time. This added cost is due to the overhead of the required coordination messages and log writes at each involved database site to achieve atomicity. For this reason, the continuing research efforts led to a number of optimizations that reduce the aforementioned cost. The most commonly adopted optimizations in the database standards and commercial database management systems are those designed around the early release of read locks of transactions. In this type of optimizations, certain participating sites may start releasing the read locks held by transactions before they are fully terminated across all participants. Hence, greatly enhancing concurrency among executing transactions and, consequently, the overall system performance. However, this type of optimizations introduces possible “execution infections” in the presence of deferred consistency constraints; a devastating complication that may lead to non-serializable executions of transactions. Thus, this type of optimizations could be considered useless, given the importance of preserving the consistency of the database in presence of deferred constraints, unless this complication is resolved in a practical and efficient manner. This is the essence of the “unsolicited deferred consistency constraints validation” mechanism presented in this paper.

Identification of Smallest Unacceptable Combinations of Simultaneous Component Failures in Information Systems

Large-scale disasters may cause simultaneous failures of many components in information systems. In the design for disaster recovery, operational procedures to recover from simultaneous component failures need to be determined so as to satisfy the time-to-recovery objective within the limited budget. For this purpose, it is beneficial to identify the smallest unacceptable combination of component failures (SUCCF) which exceeds the acceptable cost for recovering the system. This allows us to know the limitation of the recovery capability of the designed recovery operation procedure. In this paper, we propose a technique to identify the SUCCF by predicting the required cost for recovery from each combination of component failures with and without two-person cross-check of execution of recovery operations. We synthesize analytic models from the description of recovery operation procedure in the form of SysML Activity Diagram, and solve the models to predict the time-to-recovery and the cost. An example recovery operation procedure for a commercial database management system is used to demonstrate the proposed technique.

The integrated proactive surveillance system for prostate cancer.

In this paper, we present the design and implementation of the integrated proactive surveillance system for prostate cancer (PASS-PC). The integrated PASS-PC is a multi-institutional web-based system aimed at collecting a variety of data on prostate cancer patients in a standardized and efficient way. The integrated PASS-PC was commissioned by the Prostate Cancer Foundation (PCF) and built through the joint of efforts by a group of experts in medical oncology, genetics, pathology, nutrition, and cancer research informatics. Their main goal is facilitating the efficient and uniform collection of critical demographic, lifestyle, nutritional, dietary and clinical information to be used in developing new strategies in diagnosing, preventing and treating prostate cancer.The integrated PASS-PC is designed based on common industry standards – a three tiered architecture and a Service- Oriented Architecture (SOA). It utilizes open source software and programming languages such as HTML, PHP, CSS, JQuery, Drupal and MySQL. We also use a commercial database management system – Oracle 11g. The integrated PASS-PC project uses a “confederation model” that encourages participation of any interested center, irrespective of its size or location. The integrated PASS-PC utilizes a standardized approach to data collection and reporting, and uses extensive validation procedures to prevent entering erroneous data. The integrated PASS-PC controlled vocabulary is harmonized with the National Cancer Institute (NCI) Thesaurus. Currently, two cancer centers in the USA are participating in the integrated PASS-PC project.The final system has three main components: 1. National Prostate Surveillance Network (NPSN) website; 2. NPSN myConnect portal; 3. Proactive Surveillance System for Prostate Cancer (PASS-PC). PASS-PC is a cancer Biomedical Informatics Grid (caBIG) compatible product. The integrated PASS-PC provides a foundation for collaborative prostate cancer research. It has been built to meet the short term goal of gathering prostate cancer related data, but also with the prerequisites in place for future evolution into a cancer research informatics platform. In the future this will be vital for successful prostate cancer studies, care and treatment.

A novel automatic virtual metrology system architecture for TFT-LCD industry based on main memory database

The semiconductor and thin-film-transistor-liquid-crystal-display (TFT-LCD) industries widely value Automatic Virtual Metrology System (AVMS). AVMS needs to handle a large volume of VM-related data, which may cause poor internal database performance. In general, AVMS adopts efficient but expensive commercial database management systems (DBMSs) to yield good AVMS performance. This usually makes the AVMS construction cost very high. Therefore, the industries require a novel AVMS architecture with lower cost and greater efficiency in database. This paper proposes a novel AVMS architecture based on Main Memory Database (MMDB) technology. Specifically, the MMDB is used to improve the performance bottlenecks of the current Disk Resident Database (DRDB). Also, we design automatic data-backup and automatic data-query sources integration mechanisms to effectively relieve rapidly increased data volume in the original AVMS architecture. In addition, the novel AVMS architecture adopts a free commercial MMDB to significantly reduce total system cost. Integrated testing results show that the proposed AVMS architecture and developed technologies can enable the AVMS to have better data-storage efficiency, superior data-query performance, and lower database cost. The proposed AVMS architecture and research results in this paper can be a useful reference for TFT-LCD manufacturing companies in constructing their own AVM systems. The proposed AVMS architecture can also be applied in the semiconductor and solar-cell industries.

Efficient tracking of moving objects using a relational database

Tracking uncooperative moving objects by means of radar is a complex task due to clutter and association problems in multi-target scenarios. An approach to solve this problem is probabilistic multiple hypothesis tracking (PMHT). This method combines classical track filtering with a likelihood ratio test for the estimation of the plot-to-track association. The basics of PMHT and similar algorithms have gained much attention recently. However, the efficient implementation of real world applications of this technique still represents a challenging task. Since a common requirement in this context is the reliable storage of track data in a database, an implementation of the tracker's calculation inside a database management system (DBMS) using SQL views is desirable. A naive implementation of PMHT using a commercial DBMS, however, usually leads to performance problems because of the high frequency of measurement updates. In this paper, we propose possible optimizations for solving these performance problems. Their usage leads to a dramatic run-time improvement in our sample case and makes the implementation of PMHT in a database context feasible.

A practical application of our MDD approach for modeling secure XML data warehouses

Data warehouses are systems that provide useful information to support the decision making process, thus improving organizations' business processes. These systems integrate heterogeneous sources which are not only limited to their internal business data but also include data from the Web, the latter of which have become increasingly more important in the decision making process in recent years. This has motivated the extensive use of XML in the implementation of data warehouses, in a manner which facilitates data and metadata interchange among the heterogeneous data sources from the Web and the data warehouse. However, the business information that data warehouses manage is crucial and highly sensitive, and must be carefully protected. Security is thus a key issue in the design of data warehouses, regardless of the implementation technology used. It is important to note that the data available on the Web requires particular security considerations which have been specifically tailored to these systems in order to permit their particularities to be captured correctly. Unfortunately, although security issues have been considered in the development of traditional data warehouses, current research lacks approaches with which to consider security when the target platform is based on XML technology.In order to deal with this situation, in this paper we propose a methodological approach for the model driven development of secure XML data warehouses. We also specify a set of transformation rules that are able to automatically generate not only the corresponding XML structure of the data warehouse from secure conceptual data warehouse models, but also the security rules specified within the data warehouse XML structure, thus allowing both aspects to be implemented simultaneously. We additionally introduce our secure XML DW development approach, in which the secure conceptual DW data model, the PIM, is transformed into a secure XML DW, as a PSM, by applying a set of transformation rules. Our proposal is validated through the practical application of our model driven development approach for Modeling Secure XML Data Warehouses to a case study, which is based on a central Airport DW. We first describe the transformation rules defined, then use a step by step illustration to show how they will be applied to the secure conceptual model of the case study to obtain the Secure XML Data Warehouse, thus demonstrating the benefits of our proposal, and finally we analyze how to achieve the secure implementation into commercial database management systems, providing details of the secure implementation in Oracle XML DB 11g.

Design and implementation of an audit trail in compliance with US regulations

Audit trails have been used widely to ensure quality of study data and have been implemented in computerized clinical trials data systems. Increasingly, there is a need to audit access to study participant identifiable information to provide assurance that study participant privacy is protected and confidentiality is maintained. In the United States, several federal regulations specify how the audit trail function should be implemented. To describe the development and implementation of a comprehensive audit trail system that meets the regulatory requirements of assuring data quality and integrity and protecting participant privacy and that is also easy to implement and maintain. The audit trail system was designed and developed after we examined regulatory requirements, data access methods, prevailing application architecture, and good security practices. Our comprehensive audit trail system was developed and implemented at the database level using a commercially available database management software product. It captures both data access and data changes with the correct user identifier. Documentation of access is initiated automatically in response to either data retrieval or data change at the database level. Currently, our system has been implemented only on one commercial database management system. Although our audit trail algorithm does not allow for logging aggregate operations, aggregation does not reveal sensitive private participant information. Careful consideration must be given to data items selected for monitoring because selection of all data items using our system can dramatically increase the requirements for computer disk space. Evaluating the criticality and sensitivity of individual data items selected can control the storage requirements for clinical trial audit trail records. Our audit trail system is capable of logging data access and data change operations to satisfy regulatory requirements. Our approach is applicable to virtually any data that can be stored in a relational database.

Performance of Short-Commit in Extreme Database Environment

Atomic commit protocols are used where data integrity is more important than data availability. Two-Phase commit (2PC) is a standard commit protocol for commercial database management systems. To reduce certain drawbacks in 2PC protocol people have suggested different variance of this protocol. Short-Commit protocol is developed with an objective to achieve low cost transaction commitment cost with non-blocking capability. In this paper we have briefly explained short-commit protocol executing pattern. Experimental analysis and results are presented to support the claim that short-commit can work efficiently in extreme database environment.

Report from the 6th Workshop on Extremely Large Databases

Industrial and scientific datasets have been growing enormously in size and complexity in recent years. The largest transactional databases and data warehouses can no longer be hosted cost-effectively in off-the-shelf commercial database management systems. There are other forums for discussing databases and data warehouses, but they typically deal with problems occurring at smaller scales and do not always focus on practical solutions or influencing DBMS vendors. Given the relatively small (but highly influential and growing) number of users with these databases and the relatively small number of opportunities to exchange practical information related to DBMSes at extremely large scale, a workshop on extremely large databases was organized. This paper is the final report of the discussions and activities at the workshop.

Experimenting with recursive queries in database and logic programming systems

AbstractThis article considers the problem of reasoning on massive amounts of (possibly distributed) data. Presently, existing proposals show some limitations: (i) the quantity of data that can be handled contemporarily is limited, because reasoning is generally carried out in main-memory; (ii) the interaction with external (and independent) Database Management Systems is not trivial and, in several cases, not allowed at all; and (iii) the efficiency of present implementations is still not sufficient for their utilization in complex reasoning tasks involving massive amounts of data. This article provides a contribution in this setting; it presents a new system, called DLVDB, which aims to solve these problems. Moreover, it reports the results of a thorough experimental analysis we have carried out for comparing our system with several state-of-the-art systems (both logic and databases) on some classical deductive problems; the other tested systems are LDL++, XSB, Smodels, and three top-level commercial Database Management Systems. DLVDB significantly outperforms even the commercial database systems on recursive queries.

A B [formula omitted]-tree based indexing technique for fuzzy numerical data

This paper proposes an indexing technique for fuzzy numerical data which increases the performance of query processing when the query involves an atomic possibility measured flexible condition. The proposal is based on a classical indexing mechanism for numerical crisp data, B + -tree, which is implemented in most commercial database management systems (DBMS). This makes the proposed technique a good candidate for integration in a fuzzy DBMS when it is developed as an extension of a crisp DBMS. The efficiency of the proposal is contrasted with another indexing method for similar data and queries, G-tree, which is specifically designed to index multidimensional data. Results show that the proposal performance is similar to and more stable than the measured for G-tree when used for indexing fuzzy numbers.

Method of adaptive controllable parallel execution of operations in object database management systems

The design of parallel database management systems (DBMSs) normally implies using special-purpose multiprocessor computing systems. Most often, a DBMS is supposed to work in an exclusive mode of operation. However, in the class of x86-based multiprocessor computing systems designed for mass usage, the exclusive mode of DBMS operation with respect to other software is often not secured. In addition, the legacy software for this class of computing systems is often not designed for mass parallel usage. When the exclusive mode requirement is ignored and the resources of the computing system are not used in low-load DBMS regimes, the efficiency of using resources of the computing system as a whole reduces. This paper considers a method of program organization of controlled parallelism at the level of internal DBMS operations, allowing for their controlled execution based on the state of the entire computing system. This method made it possible to significantly reduce the time of response for low densities of query arrival in the ODB-Jupiter commercial object DBMS developed in the Inteltec Plus scientific manufacturing center. The method of controlled parallel execution can be used in a wide class of program systems.