The adaptive-hash join algorithm for a hypercube multicomputer

The cube adaptive-hash join algorithm, which combines the merits of nested-loop and hybrid-hash, is presented. The performance of these algorithms is compared through analytical cost modeling. The nonuniform data value distribution of the inner relation is shown to have a greater impact than that of the outer relation. The cube adaptive-hash algorithm outperforms the cube hybrid-hash algorithm when bucket overflow occurs. In the worst case, this algorithm converges to the cube nested-loop-hash algorithm. When there is no hash table overflow, the cube adaptive-hash algorithm converges to the cube hybrid-hash algorithm. Since the cube adaptive-hash algorithm adapts itself depending on the characteristics of the relations, it is relatively immune to the data distribution     

Differential induction of cytochrome P450 gene expression by 4n-alkyl-methylenedioxybenzenes in primary rat hepatocyte cultures

A well-characterized primary rat hepatocyte culture system was used to examine induction patterns of cytochrome 450 gene expression by a series of 4-n-alkyl-methylenedioxybenzene (MDBs) derivatives. Hepatocytes were treated for 24, 48, or 72 hours with 0-500 microM of the MDB compounds, and total cellular RNA and protein from each treatment was evaluated by hybridization and immunochemical techniques. Exposure to MDB congeners possessing increasing 4-n-alkyl side-chain length (C0-C8) resulted in dose- and structure-dependent activation of CYP2B1, 2B2, 3A1, 1A1, and 1A2 gene expression. At equivalent 100 microM concentrations, the C6 and C8 MDB congeners were more effective than the prototypical inducer phenobarbital (PB) with respect to induction potency of CYP2B1, CYP2B2, and CYP3A1 gene expression. In contrast to PB, longer side-chain-substituted MDBs effectively induced CYP1A1 and CYP1A2 gene expression, in addition to the CYP2B and CYP3A genes. At equivalent molar concentrations, the catechol derivative of C6-MDB was ineffective in its ability to induce CYP gene expression, indicating the importance of the intact methylenedioxy bridge in the induction mechanism. Levels of MDB-inducible CYP2B1 and CYP2B2 mRNA were highly correlated with CYP2B1/2 apoprotein levels, ascertained by immunoblot analysis of cultured hepatocyte S9 fractions. Compared with results from previous in vivo analysis (12), the current data indicate that pharmacodynamic factors may influence MDB induction profiles and that differences in MDB effects on CYP gene expression result depending on distinct structure-activity relationships.     

Heuristics for join processing using nonclustered indexes

The author examines join processing when the access paths available are nonclustered indexes on the joining attribute(s) for both relations involved in the join. He uses a bipartite graph model to represent the pages from the two relations that contain tuples to be joined. The minimization of the number of page accesses needed to compute a join in the author's database environment is explored from two perspectives. The first is to reduce the maximum buffer size so that no page is accessed more than once, and the second is to reduce the number of page accesses for a fixed buffer size. The author has developed heuristics for these problems. He gives performance comparisons of these heuristics and another method that recently appeared in the literature. Results show that one particular heuristic performs very well for addressing the problem from either perspective     

Performance analysis of a concurrent file reorganization algorithmfor record clustering

Presents a simulation-based performance analysis of a concurrent file reorganization algorithm. We examine the effect on throughput of (a) buffer size, (b) degree of reorganization, (c) write probability of transactions, (d) multiprogramming level, and (e) degree of clustered transactions. The problem of file reorganization that we consider involves altering the placement of records on pages of a secondary storage device. In addition, we want this reorganization to be done in place, i.e. using the file's original storage space for the newly reorganized file. Our approach is appropriate for a non-in-place reorganization as well. The motivation for such a physical change, i.e. record clustering, is to improve the database system's performance, i.e. minimizing the number of page accesses made in answering a set of queries. There are numerous record clustering algorithms, but they usually do not solve the entire problem, i.e., they do not specify how to efficiently reorganize the file to reflect the clustering assignment that they determine. In previous work, we have presented an algorithm that is a companion to general record clustering algorithms, i.e. it actually transforms the file. In this work we show through simulation that our algorithm, when run concurrently with user transactions, provides an acceptable level of overall database system performance     

A parallel algorithm for relational database normalization

The problem of database normalization in a parallel environment is examined. Generating relation schemes in third normal form is straightforward when given a set of functional dependencies that is a reduced cover. It is shown that a reduced cover for a set of functional dependencies can be produced in parallel. The correctness of the algorithm is based on two important theorems. it is demonstrated that the companion third normal form algorithm can be easily translated into a parallel version. The performance of the two algorithms is compared to the performance of their serial counterparts. The standard serial algorithms for computing minimal covers and synthesizing third normal form relations are presented. The parallel algorithms and their rationale are discussed     

Efficient disk-based K-means clustering for relational databases

K-means is one of the most popular clustering algorithms. We introduce an efficient disk-based implementation of K-means. The proposed algorithm is designed to work inside a relational database management system. It can cluster large data sets having very high dimensionality. In general, it only requires three scans over the data set. It is optimized to perform heavy disk I/O and its memory requirements are low. Its parameters are easy to set. An extensive experimental section evaluates quality of results and performance. The proposed algorithm is compared against the Standard K-means algorithm as well as the Scalable K-means algorithm.     

Hash-based and index-based join algorithms for cube and ringconnected multicomputers

The authors compare the performance of two join algorithms on both cube and ring interconnections for message-based multicomputers, and investigate the effects that the number of processors and the type of interconnection scheme have on the performance. First, the parallel hybrid-hash join algorithm and the parallel join-index join algorithm for both the cube and ring connected multicomputers are presented. The performance of these algorithms is then compared through analytical cost modeling. The result shows that the join-index join algorithm gives good performance only when the join selectivity is very small, and the hybrid-hash join algorithm performs consistently well under most situations. It is shown that the cube topology yields better execution time than the same algorithm on the ring topology. Furthermore, increasing the number of processors has a more significant improvement on the execution time of the cube than for the ring configuration. The applicability of join indexes on the parallel database algorithms is also discussed     

Physiological and pathophysiological regulation of cytochrome P450

This article is a report on a symposium sponsored by the American Society for Pharmacology and Experimental Therapeutics and held at the April 1998 Experimental Biology '98 meeting in San Francisco. The presentations focused on the mechanisms of regulation of cytochrome P450 gene expression by developmental factors and by hormones and cytokines, as well as on the interplay between physiological and chemical regulation. Approaches and systems used to address these questions included conditional gene knockouts in mice, primary hepatocyte cultures, immunofluorescence imaging of cells, and cell lines stably expressing reporter gene constructs.     

The partitioned exponential file for database storage management

The rate of increase in hard disk storage capacity continues to outpace the rate of decrease in hard disk seek time. This trend implies that the value of a seek is increasing exponentially relative to the value of storage. With this trend in mind, we introduce the partitioned exponential file (PE file) which is a generic storage manager that can be customized for many different types of data (e.g., numerical, spatial, or temporal). The PE file is intended for use in environments with intense update loads and concurrent, analytic queries. Such an environment may be found, for example, in long-running scientific applications which can produce petabytes of data. For example, the proposed Large Synoptic Survey Telescope [36] will produce 50–100 petabytes of observational, scientific data over its multi-year lifetime. This database will never be taken off-line, so bursty update loads of tens of terabytes per day must be handled concurrently with data analysis. In the PE file, data are organized as a series of on-disk sorts with a careful, global organization. Because the PE file relies heavily on sequential I/O, only a fraction of a disk seek is required for a typical record insertion or retrieval. In addition to describing the PE file, we also detail a set of benchmarking experiments for T1SM, which is a PE file customized for use with multi-attribute data records ordered on a single numerical attribute. In our benchmarking, we implement and test many competing data organizations that can be used to index and store such data, such as the B+-Tree, the LSM-Tree, the Buffer Tree, the Stepped Merge Method, and the Y-Tree. As expected, no organization is the best over all benchmarks, but our experiments show that T1SM is the best choice in many situations, suggesting that it is the best overall. Specifically, T1SM performs exceptionally well in the case of a heavy query workload that must be handled concurrently with an intense insertion stream. Our experiments show that T1SM (and its close cousin, the T2SM storage manager for spatial data) can handle very heavy mixed workloads of this type, and still maintain acceptably small query latencies.