This paper introduces a new approach to database disk buffering, called the LRU--K method. The basic idea of LRU--K is to keep track of the times of the last K references to popular database pages, using this information to statistically estimate the interarrival time of such references on a page by page basis. Although the LRU--K approach performs optimal statistical inference under relatively standard assumptions, it is fairly simple and incurs little bookkeeping overhead. As we demonstrate with simulation experiments, the LRU--K algorithm surpasses conventional buffering algorithms in discriminating between frequently and infrequently referenced pages. In fact, LRU--K can approach the behavior of buffering algorithms in which page sets with known access frequencies are manually assigned to different buffer pools of specifically tuned sizes. Unlike such customized buffering algorithms however, the LRU--K method is self--tuning, in the sense that it does not rely on external hints abo...

In a path-breaking paper last year Pat and Betty O'Neil and Gerhard Weikum proposed a self-tuning improvement to the Least Recently Used (LRU) buffer management algorithm[15]. Their improvement is called LRU/k and advocates giving priority to buffer pages based on the kth most recent access. (The standard LRU algorithm is denoted LRU/1 according to this terminology.) If P1's kth most recent access is more more recent than P2's, then P1 will be replaced after P2. Intuitively, LRU/k for k ? 1 is a good strategy, because it gives low priority to pages that have been scanned or to pages that belong to a big randomly accessed file (e.g., the account file in TPC/A). They found that LRU/2 achieves most of the advantage of their method. The one problem of LRU/2 is the processor Supported by U.S. Office of Naval Research #N00014-91-J1472 and #N00014-92-J-1719, U.S. National Science Foundation grants #CCR-9103953 and IRI-9224601, and USRA #5555-19. Part of this work was performed while Theodo...

Abstract. We show that production rules and persis-tent queues together provide a convenient mechanism for maintaining consistency in semantically heterogeneous multi-database environments. We describe a specification language and methods for automatically deriving production rules that maintain (1) existence dependencies, in which the presence of data in one database implies the presence of related data in another, and (2) value dependencies, in which the value of data in one database is baaed on the value of related data in another. The production rules derived from dependency specifications use persistent queues to monitor and maintain the dependencies automatically, asynchronously, incremen-tally, and correctly. 1

Database researchers have recognized that integrating a production rules facility into a database system provides a uniform mechanism for a number of advanced database features including integrity constraint enforcement, derived data maintenance, triggers, protection, version control, and others. In addition, a database system with rule processing capabilities provides a useful platform for large and efficient knowledge-base and expert systems. Database systems with production rules are referred to as active database systems, and the field of active database systems has indeed been active. This paper summarizes current work in active database systems and suggests future research directions. Topics covered include database rule languages, rule processing semantics, and implementation issues. 1 Introduction Database systems provide persistent storage for massive amounts of data and powerful interfaces for querying and modifying this data. Even so, most database systems are passive, si...

This paper describes our development of the Starburst Rule System, an active database rules facility integrated into the Starburst extensible relational database system at the IBM Almaden Research Center. The Starburst rule language is based on arbitrary database state transitions rather than tuple- or statement-level changes, yielding a clear and flexible execution semantics. The rule system has been implemented completely. Its rapid implementation was facilitated by the extensibility features of Starburst, and rule management and rule processing is integrated into all aspects of database processing. Index terms: active database systems, database production rules, extensible database systems, expert database systems 1 Introduction Active database systems allow users to create rules---rules specify data manipulation operations to be executed automatically whenever certain events occur or conditions are met. Active database rules provide a general and powerful mechanism for traditiona...

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As more and more query processing work can be done in main memory, memory access is becoming a significant cost component of database operations. Recent database research has shown that most of the memory stalls are due to second-level cache data misses and first-level instruction cache misses. While a lot of research has focused on reducing the data cache misses, relatively little research has been done on improving the instruction cache performance of database systems. We first answer the question “Why does a database system incur so many instruction cache misses? ” We demonstrate that current demand-pull pipelined query execution engines suffer from significant instruction cache thrashing between different operators. We propose techniques to buffer database operations during query execution to avoid instruction cache thrashing. We implement a new light-weight “buffer ” operator and study various factors which may affect the cache performance. We also introduce a plan refinement algorithm that considers the query plan and decides whether it is beneficial to add additional “buffer ” operators and where to put them. The benefit is mainly from better instruction locality and better hardware branch prediction. Our techniques can be easily integrated into current database systems without significant changes. Our experiments in a memory-resident PostgreSQL database system show that buffering techniques can reduce the number of instruction cache misses by up to 80 % and improve query performance by up to 15%. 1.

This paper reports on results and experiences from the COMFORT automatic tuning project. The objective of the project has been to investigate architectural principles of self-tuning database and transaction processing systems, and to develop self-tuning methods for specific performance tuning problems. A particular concern of the project has been to cope with workload dynamics and workload heterogeneity in multi-user systems. As a general guideline, an adaptive feedback control approach has been adopted, where observations of the current load characteristics are used to predict performance trends and to drive the dynamic adjustment of tuning parameters. As examples of these general principles, the paper discusses adaptive approaches to two specific tuning problems and the developed solutions. First, we present a self-tuning load control method that copes with overload caused by excessive lock conflicts that may occur during load surges. This conflict-driven load control method adapts t...

Managing data in large rule systems is a critical issue, and DBMS systems are being extended for the support of rule-based, data-intensive decision making such as in expert system applications. We suggest to selectively materialize the rule-generated data in relations so that rule-based decisions can be made incrementally and automatically when the collected data are updated, An algorithm is developed to select derived relations for materialization so that the overall cost of processing the inference rules is minimized while satisfying requirements on query response time. 1.

This paper investigates the performance of a multi-disk storage system equipped with a segmented disk cache processing a workload of multiple relational scans. Prefetching is a popular method of improving the performance of scans. Many modern disks have a multisegment cache which can be used for prefetching. We observe that, exploiting declustering as a data placement method, prefetching in a segmented cache causes a load imbalance among several disks. A single disk becomes a bottleneck, degrading performance of the entire system. A variation in disk queue length is a primary factor of the imbalance. Using a precise simulation model, we investigate several approaches to achieving better balancing. Our metrics are a scan response time for the closed-end system and an ability to sustain a workload without saturating for the open-end system. We arrive at two main conclusions: (1) Prefetching in main memory is inexpensive and effective for balancing and can supplement or substitute prefetc...