7365552
Tail recursion elimination in deductive databases
We consider an optimization technique for deductive and relational databases. The optimization technique is an extension of the magic templates rewriting, and it can improve the performance of query evaluation by not materializing the extension of intermediate views. Standard relational techniques, such as unfolding embedded view definitions, do not apply to recursively defined views, and so alternative techniques are necessary. We demonstrate the correctness of our rewriting. We define a class of “nonrepeating” view definitions, and show that for certain queries our rewriting performs at least as well as magic templates on nonrepeating views, and often much better. A syntactically recognizable property, called “weak right-linearity”, is proposed. Weak right-linearity is a sufficient condition for nonrepetition and is more general than right-linearity. Our technique gives the same benefits as right-linear evaluation of right-linear views, while applying to a significantly more general class of views.
9401708
Complex Aggregation at Multiple Granularities
Datacube queries compute simple aggregates at multiple granularities. In this paper we examine the more general and useful problem of computing a complex subquery involving multiple dependent aggregates at multiple granularities. We call such queries multi-feature cubes. An example is Broken down by all combinations of month and customer, find the fraction of the total sales in 1996 of a particular item due to suppliers supplying within 10% of the minimum price (within the group), showing all subtotals across each dimension. We classify multi-feature cubes based on the extent to which fine granularity results can be used to compute coarse granularity results; this classification includes distributive, algebraic and holistic multi-feature cubes. We provide syntactic sufficient conditions to determine when a multi-feature cube is either distributive or algebraic. This distinction is important because, as we show, existing datacube evaluation algorithms can be used to compute multi-feature cubes that are distributive or algebraic, without any increase in I/O complexity. We evaluate the CPU performance of computing multi-feature cubes using the datacube evaluation algorithm of Ross and Srivastava. Using a variety of synthetic, benchmark and real-world data sets, we demonstrate that the CPU cost of evaluating distributive multi-feature cubes is comparable to that of evaluating simple datacubes. We also show that a variety of holistic multi-feature cubes can be evaluated with a manageable overhead compared to the distributive case.
16656102
Groupwise Processing of Relational Queries
In this paper, we define and examine a particular class of queries called group queries. Group queries are natural queries in many decisionsupport applications. The main characteristic of a group query is that it can be executed in a groupby-group fashion. In other words, the underlying relation(s) can be partitioned (based on some set of attributes) into disjoint groups, and each group can be processed separately. We give a syntactic criterion to identify these queries and prove its sufficiency. We also prove the strong result that every group query has an equivalent formulation that satisfies our syntactic criterion. We describe a general evaluation technique for group queries, and demonstrate how an optimizer can determine this plan. We then consider more complex queries whose components are group queries with potentially different partitioning attributes. We give two methods to identify group query components within such a query. We also give some performance results for group queries expressed in standard SQL, comparing a commercial database system with our optimized plan on top of the same commercial system. These results indicate that there are significant potential performance improvements.
7567374
Foundations of Aggregation Constraints
We introduce a new constraint domain, aggregation constraints, which is useful in database query languages, and in constraint logic programming languages that incorporate aggregate functions. We study the fundamental problem of checking if a conjunction of aggregation constraints is solvable, and present undecidability results for many different classes of aggregation constraints. We describe a complete and minimal axiomatization of the class of aggregation constraints over finite multisets of reals, which permits a natural reduction from the class of aggregation constraints to the class of mixed integer/real, non-linear arithmetic constraints. We then present a polynomial-time algorithm that directly checks for solvability of a useful class of aggregation constraints, where the reduction-based approach does not lead to efficient checks for solvability.
31185043
Inferring negative information from disjunctive databases
We propose criteria that any rule for inferring negative information from disjunctive databases should satisfy, and examine existing rules from this viewpoint. We then present a new inference rule, the ‘disjunctive database rule’ (DDR), and compare it to the existing rules with respect to the criteria. In particular, the DDR is equivalent to the CWA for definite databases, it infers no more negative information than the GCWA, and it interprets disjunction inclusively rather than exclusively. We generalize the DDR to a class of layered databases, describe an implementation of the DDR, ‘negation as positive failure’, and study its soundness and completeness properties.
38852147
On Negation in HiLog
Abstract The logic HiLog of Chen, Kifer, and Warren has a second order syntax, while its semantics is first order. HiLog programs with negative literals in the body are considered. A stable-model semantics and a well-founded semantics for this class of program are defined, and it is shown that these semantics generalize the stable-model semantics and the well-founded semantics, respectively, for range-restricted normal programs. A second order property called preservation under extensions is proposed and investigated. Preservation under extensions ensures that the semantics of a program is not changed when rules having no symbols in common with the program are appended to the program. It is shown that for normal programs, domain independence and preservation under extensions are equivalent, while for HiLog programs, preservation under extensions is strictly stronger. Range restrictedness is generalized to HiLog programs in two ways, and it is shown that range restricted HiLog programs are preserved under extensions with respect to the well-founded semantics. Conditions under which the well-founded semantics is two-valued are investigated, and the class of modularly stratified programs is generalized to HiLog. An extension of magic-set techniques to modularly stratified HiLog programs is described.
27419087
Implementation of Monte Carlo Integration for the Analysis of Product-Form Queueing Networks
Abstract MonteQueue is a new public-domain software package which rapidly solves large and small multiclass product-form queueing networks with multiple- and single-server stations over a wide range of traffic conditions. MonteQueue obtains estimates of performance measures by applying importance sampling to sum and integral representations of the network's normalization constants. This paper discusses the implementation issues and surveys of the theoretical properties of the four importance sampling techniques included in MonteQueue. It also presents new numerical data which compare the performance of the four techniques.
1230494
Optimizing File Availability in Peer-to-Peer Content Distribution
A fundamental paradigm in peer-to-peer (P2P) content distribution is that of a large community of intermittently-connected nodes that cooperate to share files. Because nodes are intermittently connected, the P2P community must replicate and replace files as a function of their popularity to achieve satisfactory performance. In this paper, we develop an analytical optimization theory for benchmarking the performance of replication/replacement algorithms, including algorithms that employ erasure codes. We also consider a content management algorithm, the Top-K Most Frequently Requested algorithm, and show that in most cases this algorithm converges to an optimal replica profile. Finally, we present two approaches for achieving an evenly balanced load over all the peers in the community.
369703
Object replication strategies in content distribution networks
Recently, the Internet has witnessed the emergence of content distribution networks (CDNs). In this paper, we study the problem of optimally replicating objects in CDN servers. In our model, each Internet autonomous system (AS) is a node with finite storage capacity for replicating objects. The optimization problem is to replicate objects so that when clients fetch objects from the nearest CDN server with the requested object, the average number of ASs traversed is minimized. We formulate this problem as a combinatorial optimization problem. We show that this optimization problem is NP complete. We develop four natural heuristics and compare them numerically using real Internet topology data. We find that the best results are obtained with heuristics that have all the CDN servers cooperating in making the replication decisions. We also develop a model for studying the benefits of cooperation between nodes, which provides insight into peer-to-peer content distribution.
45021908
Video-on-Demand Over ATM: Constant-Rate Transmission and Transport
We introduce a specific transport and transmission scheme for video-on-demand (VoD) called constant-rate transmission and transport (CRTT). CRTT establishes a constant bit-rate (CBR) virtual channel between the video provider and the viewer's set-top box (STB) and then transmits cells from the provider into this channel at a constant rate. Since we assume that the number of cells in a frame is variable, CRTT requires that some number of cells be built up in an STB buffer before the commencement of playback. The build up, cell transmission rate, and the set-top memory size must be chosen so that there is no starvation or overflow at the STB. We develop fundamental relationships between these parameters for viable CRTT. We then apply the theory to an MPEG encoding of Star Wars and find that the minimal STB memory far CRTT is 23 Mbytes. We also consider varying the constant rate over a small number of intervals. We find, for example, that for Star Wars approximately 2 Mbytes of set-top memory suffices with 32 constant-rate intervals.
14659770
Guaranteeing statistical QoS to regulated traffic: the single node case
Multimedia traffic can typically tolerate some loss but has rigid delay constraints. A natural QoS requirement for a multimedia connection is a prescribed bound on the the fraction of traffic that exceeds an end-to-end delay limit. We propose and analyze a traffic management scheme which guarantees QoS to multimedia traffic while simultaneously allowing for a large connection-carrying capacity. We study our traffic management scheme in the context of a single node. In order for the node to guarantee QoS, each connection's traffic is regulated. In order to support many connections, the link statistically multiplexes the connections' traffic. The scheme consists of (i) cascaded leaky-buckets for traffic regulation, (ii) smoothers at the ingresses, and (iii) bufferless statistical multiplexing within the node. For this scheme we show that loss probabilities are minimized with simple one-buffer smoothers which operate at specific minimum rates. We also show that the worst-case input traffic is extremal on-off traffic for all connections. These two results lead to a straightforward scheme for guaranteeing QoS to regulated traffic. Using MPEG video traces, we present numerical results which demonstrate the methodology. Finally, we compare the bufferless scheme with buffered statistical multiplexing.