21401289
Parallelism in Relational Database Management Systems
In order to provide real-time responses to complex queries involving large volumes of data, it has become necessary to exploit parallelism in query processing. This paper addresses the issues and solutions relating to intraquery parallelism in a relational database management system (DBMS). We provide a broad framework for the study of the numerous issues that need to be addressed in supporting parallelism efficiently and flexibly. The alternatives for a parallel architecture system are discussed, followed by the focus on how a query can be parallelized and how that affects load balancing of the different tasks created. The final part of the paper contains information about how the IBM DATABASE 2™ (DB2®) Version 3 product provides support for I/O parallelism to reduce response time for data-intensive queries.
6838561
High Level Indexing of User-Defined Types
35134245
Single Table Access Using Multiple Indexes: Optimization, Execution, and Concurrency Control Techniques
Many data base management systems' query optimizers choose at most one index for accessing the records of a table in a given query, even though many indexes may exist on the table. In spite of the fact that there are some systems which use multiple indexes, very little has been published about the concurrency control or query optimization implications (e.g., deciding how many indexes to use) of using multiple indexes. This paper addresses these issues and presents solutions to the associated problems. Techniques are presented for the efficient handling of record ID lists, elimination of some locking, and determination of how many and which indexes to use. The techniques are adaptive in the sense that the execution strategies may be modified at run-time (e.g., not use some indexes which were to have been used), if the assumptions made at optimization-time (e.g., about selectivities) turn out to be wrong. Opportunities for exploiting parallelism are also identified. A subset of our ideas have been implemented in IBM's DB2 V2R2 relational data base management system.
58268816
Query Optimization in the IBM DB2 Family.
206780897
An efficient hybrid join algorithm: a DB2 prototype
A new join method, called hybrid join, is proposed which uses the join-index filtering and the skip sequential prefetch mechanism for efficient data access. With this method, the outer table is sorted on the join column. Then, the outer is joined with the index on the join column of the inner. The inner tuple is represented by its surrogate, equivalent of its physical disk address, which is carried in the index. The partial join result is sorted on the surrogate and then the inner table is accessed sequentially to complete the join result. Local predicate filtering can also be applied before the access of the inner relation through the index AND/ORing. Efficient methods for skip sequential access and prefetching of logically discontiguous leaf pages of B/sup +/-tree indexes are also presented.<<ETX>>
20214518
Extensible Indexing Support in DB2 Universal Database
Publisher Summary Emerging database (DB) applications require the scalable management of a large quantity of complex data, together with traditional business data and flexible querying capabilities for business intelligence. Object-relational databases or universal servers are component database management systems (DBMSs) developed to support applications. They leverage the mature relational database technology that provides scalability, reliability, and recovery. They enable users to introduce application-specific types and methods into a database. These extensibility features can be seen as infrastructure for providing plug-in components that extend the built-in repertoire of database types and functions with support for additional, nonstandard data types. Tables in a database may contain user-defined objects such as geographical shapes, images, and semi-structured or unstructured text documents. This chapter presents a high-level framework of indexing for user-defined types. The framework allows users to concentrate on the semantics of applications and user-defined predicates without being concerned with the low-level details of locking, recovery, buffer management, or balanced search-tree updates. It is tightly integrated with the database engine and enhances the value of underlying access methods, built-in or user-defined, in a database system by supporting indexing on new data types and indexed scans using new predicates.
18897982
An Efficient SAN-Level Caching Method Based on Chunk-Aging
SAN-level caching can manage caching within a global view so that global hot data can be identified and cached. However, two problems may be encountered in the existing SAN-level caching methods: first, too many migrations from disks to cache resulting from cache thrashing; second, too few cache hits resulting from insufficient caching. This paper proposes a SAN-level caching method employing chunk-aging to control the migrations of chunks of data from disks to cache, which takes the temporal distribution of chunk accesses into account and solves the two problems above. Then by employing two LRU lists to manage the cache replacement, this method separates and manages two types of hot data chunks, one of which have burst accesses and the other have long-term frequent accesses, thus preventing them from interfering with each other in cache. The simulation results demonstrate that our method can achieve a high hit ratio while maintaining a relatively low migration rate.
6934721
A dynamic conditional random field model for foreground and shadow segmentation
This paper proposes a dynamic conditional random field (DCRF) model for foreground object and moving shadow segmentation in indoor video scenes. Given an image sequence, temporal dependencies of consecutive segmentation fields and spatial dependencies within each segmentation field are unified by a dynamic probabilistic framework based on the conditional random field (CRF). An efficient approximate filtering algorithm is derived for the DCRF model to recursively estimate the segmentation field from the history of observed images. The foreground and shadow segmentation method integrates both intensity and gradient features. Moreover, models of background, shadow, and gradient information are updated adaptively for nonstationary background processes. Experimental results show that the proposed approach can accurately detect moving objects and their cast shadows even in monocular grayscale video sequences.
15156880
Adaptive Foreground and Shadow Detection in Image Sequences
This paper presents a novel method of foreground segmentation that distinguishes moving objects from their moving cast shadows in monocular image sequences. The models of background, edge information, and shadow are set up and adaptively updated. A Bayesian belief network is proposed to describe the relationships among the segmentation label, background, intensity, and edge information. The notion of Markov random field is used to encourage the spatial connectivity of the segmented regions. The solution is obtained by maximizing the posterior possibility density of the segmentation field.
19667746
Study on the Harmonious Operation of Logistics Finance Management of Supply Chain in Ports-Hinterland Based on System Dynamics
Abstract-Taking China's ports-hinterland logistics system as an example, the paper discusses the harmonious operation of logistics finance management of supply chain which is composed of the functional entity activities such as transportation, warehousing, packaging, circulation and information transmission, as well as the goods movement of all sectors of the logistics process. The logistics finance management is complex operating system with dynamics features, which is established on the basis of a "virtual organization" made up by nodes in supply chain. In order to provide a new research perspective on the coordination development of ports-hinterland logistics system, a dynamics model of logistics finance management of supply chain was set up based on the theory of system dynamics.
32478144
Experience from a real life query optimizer
DB2 is a major relational database system on IBM main frames, it has over six thousand licenses over the world to support a very large number of major applications for customer business, Optimizer in DB2 is a critical component for the query processing, it inherited system R technologies and has been improved in very many aspects from numerous valuable real life experiences on customer applications. The major DB2 optimizer enhancements will be discussed with the backgrounds and examples. A wish list for future enhancements as well as some trend and direction of DB2 optimizer will also be discussed.