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Evita Raced: Metacompilation for Declarative Networks ABSTRACT
"... Declarative languages have recently been proposed for many new applications outside of traditional data management. Since these are relatively early research efforts, it is important that the architectures of these declarative systems be extensible, in order to accommodate unforeseen needs in these ..."
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Cited by 28 (6 self)
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Declarative languages have recently been proposed for many new applications outside of traditional data management. Since these are relatively early research efforts, it is important that the architectures of these declarative systems be extensible, in order to accommodate unforeseen needs in these new domains. In this paper, we apply the lessons of declarative systems to the internals of a declarative engine. Specifically, we describe our design and implementation of Evita Raced, an extensible compiler for the OverLog language used in our declarative networking system, P2. Evita Raced is a metacompiler: an OverLog compiler written in OverLog. We describe the minimalist architecture of Evita Raced, including its extensibility interfaces and its reuse of P2’s data model and runtime engine. We demonstrate that a declarative language like OverLog is well-suited to expressing traditional and novel query optimizations as well as other query manipulations, in a compact and natural fashion. Finally, we present initial results of Evita Raced extended with various optimization programs, running on both Internet overlay networks and wireless sensor networks. 1.
Architecture of a Database System
"... Database Management Systems (DBMSs) are a ubiquitous and critical component of modern computing, and the result of decades of research and development in both academia and industry. Historically, DBMSs were among the earliest multi-user server systems to be developed, and thus pioneered many systems ..."
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Cited by 25 (0 self)
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Database Management Systems (DBMSs) are a ubiquitous and critical component of modern computing, and the result of decades of research and development in both academia and industry. Historically, DBMSs were among the earliest multi-user server systems to be developed, and thus pioneered many systems design techniques for scalability and reliability now in use in many other contexts. While many of the algorithms and abstractions used by a DBMS are textbook material, there has been relatively sparse coverage in the literature of the systems design issues that make a DBMS work. This paper presents an architectural discussion of DBMS design principles, including process models, parallel architecture, storage system design, transaction system implementation, query processor and optimizer architectures, and typical shared components and utilities. Successful commercial and open-source systems are used as points of reference, particularly when multiple alternative designs have been adopted by different groups. 1
Counter Strike: Generic Top-Down Join Enumeration for
"... Finding the optimal execution order of join operations is a crucial task of today’s cost-based query optimizers. There are two approaches to identify the best plan: bottom-up and top-down join enumeration. But only the top-down approach allows for branchand-bound pruning, which can improve compile t ..."
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Finding the optimal execution order of join operations is a crucial task of today’s cost-based query optimizers. There are two approaches to identify the best plan: bottom-up and top-down join enumeration. But only the top-down approach allows for branchand-bound pruning, which can improve compile time by several orders of magnitude while still preserving optimality. For both optimization strategies, efficient enumeration algorithms have been published. However, there are two severe limitations for the topdown approach: The published algorithms can handle only (1) simple (binary) join predicates and (2) inner joins. Since real queries may contain complex join predicates involving more than two relations, and outer joins as well as other non-inner joins, efficient topdown join enumeration cannot be used in practice yet. We develop a novel top-down join enumeration algorithm that overcomes these two limitations. Furthermore, we show that our new algorithm is competitive when compared to the state of the art in bottom-up processing even without playing out its advantage by making use of its branch-and-bound pruning capabilities. 1.
Optimal Top-Down Join Enumeration (extended version)
, 2007
"... Most contemporary database systems perform cost-based join enumeration using some variant of System-R’s bottomup dynamic programming method. The notable exceptions are systems based on the top-down transformational search of Volcano/Cascades. As recent work has demonstrated, bottom-up dynamic progra ..."
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Most contemporary database systems perform cost-based join enumeration using some variant of System-R’s bottomup dynamic programming method. The notable exceptions are systems based on the top-down transformational search of Volcano/Cascades. As recent work has demonstrated, bottom-up dynamic programming can attain optimality with respect to the shape of the join graph; no comparable results have been published for transformational search. However, transformational systems leverage benefits of top-down search not available to bottom-up methods. In this paper we describe a top-down join enumeration algorithm that is optimal with respect to the join graph. We present performance results demonstrating that a combination of optimal enumeration with search strategies such as branch-and-bound yields an algorithm significantly faster than those previously described in the literature. Although our algorithm enumerates the search space top-down, it does not rely on transformations and thus retains much of the architecture of traditional dynamic programming. As such, this work provides a migration path for existing bottom-up optimizers to exploit top-down search without drastically changing to the transformational paradigm.
Distributed Queries without Distributed State
- In WebDB
, 2002
"... Traditionally, distributed queries have been optimized centrally and executed synchronously. We outline a framework that relaxes both of these constraints using mutant query plans: XML representations of query plans that can also include verbatim XML data, references to resource locations (URLs), ..."
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Traditionally, distributed queries have been optimized centrally and executed synchronously. We outline a framework that relaxes both of these constraints using mutant query plans: XML representations of query plans that can also include verbatim XML data, references to resource locations (URLs), or abstract resource names (URNs). Servers work using local, possibly incomplete knowledge, partially evaluate as much of the query plan as they can, incorporate the partial results into a new, mutated query plan and transfer it to some other server that can continue processing.
