15215532
Estimating Answer Sizes for XML Queries
Estimating the sizes of query results, and intermediate results, is crucial to many aspects of query processing. In particular, it is necessary for effective query optimization. Even at the user level, predictions of the total result size can be valuable in "next-step" decisions, such as query refinement. This paper proposes a technique to obtain query result size estimates effectively in an XML database.Queries in XML frequently specify structural patterns, requiring specific relationships between selected elements. Whereas traditional techniques can estimate the number of nodes (XML elements) that will satisfy a node-specific predicate in the query pattern, such estimates cannot easily be combined to provide estimates for the entire query pattern, since element occurrences are expected to have high correlation.We propose a solution based on a novel histogram encoding of element occurrence position. With such position histograms, we are able to obtain estimates of sizes for complex pattern queries, as well as for simpler intermediate patterns that may be evaluated in alternative query plans, by means of a position histogram join (pH-join) algorithm that we introduce. We extend our technique to exploit schema information regarding allowable structure (the no-overlap property) through the use of a coverage histogram.We present an extensive experimental evaluation using several XML data sets, both real and synthetic, with a variety of queries. Our results demonstrate that accurate and robust estimates can be achieved, with limited space, and at a miniscule computational cost. These techniques have been implemented in the context of the TIMBER native XML database [22] at the University of Michigan.
1362728
Structural join order selection for XML query optimization
Structural join operations are central to evaluating queries against XML data, and are typically responsible for consuming a lion's share of the query processing time. Thus, structural join order selection is at the heart of query optimization in an XML database, just as (value-based) join order selection is central to relational query optimization. We introduce five algorithms for structural join order optimization for XML tree pattern matching and present an extensive experimental evaluation. Our experiments demonstrate that many relational rules of thumb are no longer appropriate: for instance, using dynamic programming style optimization is not efficient; limiting consideration to left-deep plans usually misses the best solution. Our experiments also show that a dynamic programming optimization with pruning (DPP) algorithm can find the optimal solution, with low cost relative to the traditional dynamic programming (DP) algorithm; and an optimization technique that only considers fully pipelined (FP) plans can very quickly choose a plan that in most cases is close to optimal. Our recommendation is that DPP should be used in XML query optimizers where query execution time is expected to be significant, and that FP should be used where it is important to find a good (but not necessarily the best) plan quickly.
1408601
Grouping in XML
XML permits repeated and missing sub-elements, and missing attributes. We discuss the consequent implications on grouping, both with respect to specification and with respect to implementation. The techniques described here have been implemented in the TIMBER native XML database system being developed at the University of Michigan.
7798629
Structural joins: a primitive for efficient XML query pattern matching
XML queries typically specify patterns of selection predicates on multiple elements that have some specified tree structured relationships. The primitive tree structured relationships are parent-child and ancestor-descendant, and finding all occurrences of these relationships in an XML database is a core operation for XML query processing. We develop two families of structural join algorithms for this task: tree-merge and stack-tree. The tree-merge algorithms are a natural extension of traditional merge joins and the multi-predicate merge joins, while the stack-tree algorithms have no counterpart in traditional relational join processing. We present experimental results on a range of data and queries using the TIMBER native XML query engine built on top of SHORE. We show that while, in some cases, tree-merge algorithms can have performance comparable to stack-tree algorithms, in many cases they are considerably worse. This behavior is explained by analytical results that demonstrate that, on sorted inputs, the stack-tree algorithms have worst-case I/O and CPU complexities linear in the sum of the sizes of inputs and output, while the tree-merge algorithms do not have the same guarantee.
5146790
Modeling skew in data streams
Data stream applications have made use of statistical summaries to reason about the data using nonparametric tools such as histograms, heavy hitters, and join sizes. However, relatively little attention has been paid to modeling stream data parametrically, despite the potential this approach has for mining the data. The challenges to do model fitting at streaming speeds are both technical -- how to continually find fast and reliable parameter estimates on high speed streams of skewed data using small space -- and conceptual -- how to validate the goodness-of-fit and stability of the model online.In this paper, we show how to fit hierarchical (binomial multifractal) and non-hierarchical (Pareto) power-law models on a data stream. We address the technical challenges using an approach that maintains a sketch of the data stream and fits least-squares straight lines; it yields algorithms that are fast, space-efficient, and provide approximations of parameter value estimates with a priori quality guarantees relative to those obtained offline. We address the conceptual challenge by designing fast methods for online goodness-of-fit measurements on a data stream; we adapt the statistical testing technique of examining the quantile-quantile (q-q) plot, to perform online model validation at streaming speeds.As a concrete application of our techniques, we focus on network traffic data which has been shown to exhibit skewed distributions. We complement our analytic and algorithmic results with experiments on IP traffic streams in AT&T's Gigascope®® data stream management system, to demonstrate practicality of our methods at line speeds. We measured the stability and robustness of these models over weeks of operational packet data in an IP network. In addition, we study an intrusion detection application, and demonstrate the potential of online parametric modeling.
8794770
A Novel Representation of Sequence Data Based on Structural Information for Effective Music Retrieval
In this paper, we propose a novel representation of sequences based on the structural information of the sequences. A sequence is represented by a set of rules, which are derived from its subsequences. There are two types of subsequences of interest. One is called frequent pattern, which is a subsequence appearing often enough in the sequence. The other is called correlative pattern, which is a subsequence composed of highly correlated elements. The rules derived from the frequent patterns are called frequent rules, while the ones derived from the correlative patterns are called correlative rules. By considering music objects as sequences, we represent each of them as a set of rules and design a similarity function for effective music retrieval. The experimental results show that our approaches outperform the approaches based on the Markov-model on the average precision.
8380855
High Performance Computations for Large Scale Simulations of Subsurface Multiphase Fluid and Heat Flow
TOUGH2 is a widely used reservoir simulator for solving subsurface flow related problems such as nuclear waste geologic isolation, environmental remediation of soil and groundwater contamination, and geothermal reservoir engineering. It solves a set of coupled mass and energy balance equations using a finite volume method. This contribution presents the design and analysis of a parallel version of TOUGH2. The parallel implementation first partitions the unstructured computational domain. For each time step, a set of coupled non-linear equations is solved with Newton iteration. In each Newton step, a Jacobian matrix is calculated and an ill-conditioned non-symmetric linear system is solved using a preconditioned iterative solver. Communication is required for convergence tests and data exchange across partitioning borders. Parallel performance results on Cray T3E-900 are presented for two real application problems arising in the Yucca Mountain nuclear waste site study. The execution time is reduced from 7504 seconds on two processors to 126 seconds on 128 processors for a 2D problem involving 52,752 equations. For a larger 3D problem with 293,928 equations the time decreases from 10,055 seconds on 16 processors to 329 seconds on 512 processors.
6169370
Indexing emails and email threads for retrieval
Electronic mail poses a number of unusual challenges for the design of information retrieval systems and test collections, including informal expression, conversational structure, variable document granularity (e.g., messages, threads, or longer-term interactions), a naturally occuring integration between free text and structural metadata, and incompletely characterized user needs. This paper reports on initial experiments with a large collection of public mailing lists from the World Wide Web consortium that will be used for the TREC 2005 Enterprise Search Track. Automatic subject-line threading and removal of duplicated text were found to have little effect in a small pilot study. Those observations motivated development of a question typology and more detailed analysis of collection characteristics; preliminary results for both are reported.
62726183
Further improve circuit partitioning using GBAW logic perturbation techniques
Efficient circuit partitioning is gaining more importance with the increasing size of modern circuits. Conventionally, circuit partitioning is solved by modeling a circuit as a hypergraph for the ease of applying graph algorithms. However there exists room for further improvement on even optimum hypergraph partitioning results, if logic information can be applied for perturbation. In this paper we present a multi-way partitioning framework which can couple any excellent hypergraph partitioner and a noval logic perturbation based technique (GBAW) for further improvement over very excellent partitioning results. Our approach can integrate with any graph partitioner. We performed experiments on 2-, 3-, 4-, and 5-way partitionings for various circuits of different sizes from MCNC benchmarks. We have chosen the state-of-the-art hMetis-Kway to obtain high quality initial solutions for the experiments. Our experiments showed that this partitioning approach can achieve a further 15% reduction in cut size for 2-way partitioning with an area penalty of only 0.33%. The good results demonstrated the effectiveness of this new partitioning technique.