In this paper we present a simple and efficient method, called ARIES ( Algorithm for Recouery and Isolation Exploiting Semantics), which supports partial rollbacks of transactions, finegranularity (e.g., record) locking and recovery using write-ahead logging (WAL). We introduce the paradigm of repeating history to redo all missing updates before performing the rollbacks of the loser transactions during restart after a system failure. ARIES uses a log sequence number in each page to correlate the state of a page with respect to logged updates of that page. All updates of a transaction are logged, including those performed during rollbacks. By appropriate chaining of the log records written during rollbacks to those written during forward progress, a bounded amount of logging is ensured during rollbacks even in the face of repeated failures during restart or of nested rollbacks We deal with a variety of features that are very Important in building and operating an industrial-strength transaction processing system ARIES supports fuzzy checkpoints, selective and deferred restart, fuzzy image copies, media recovery, and high concurrency lock modes (e. g., increment /decrement) which exploit the semantics of the operations and require the ability to perform operation logging. ARIES is flexible with respect to the kinds of buffer management policies that can be implemented. It supports objects of

An analysis of the failure statistics of a commercially available fault-tolerant system shows that administration and software are the major contributors to failure. Various approaches to software fault-tolerance are then discussed -- notably process-pairs, transactions and reliable storage. It is pointed out that faults in production software are often soft (transient) and that a transaction mechanism combined with persistent processpairs provides fault-tolerant execution -- the key to software fault-tolerance.

Data replication is an increasingly important topic as databases are more and more deployed over clusters of workstations. One of the challenges in database replication is to introduce replication without severely affecting performance. Because of this difficulty, current database products use lazy replication, which is very efficient but can compromise consistency. As an alternative, eager replication guarantees consistency but most existing protocols have a prohibitive cost. In order to clarify the current state of the art and open up new avenues for research, this paper analyses existing eager techniques using three key parameters. In our analysis, we distinguish eight classes of eager replication protocols and, for each category, discuss its requirements, capabilities, and cost. The contribution lies in showing when eager replication is feasible and in spelling out the different aspects a database replication protocol must account for.

Tandem builds single-fault-tolerant computer systems. At the hardware level, the system is designed as a loosely coupled multi-processor with fail-fast modules connected via dual paths. It is designed for online diagnosis and maintenance. A range of CPUs may be inter-connected via a hierarchical fault-tolerant local network. A variety of peripherals needed for online transaction processing are attached via dual ported controllers. A novel disc subsystem allows a choice between low cost-per-megabyte and low cost-per-access. System software provides processes and messages as the basic structuring mechanism. Processes provide software modularity and fault isolation. Process pairs tolerate hardware and transient software failures. Applications are structured as requesting processes making remote procedure calls to server processes. Process server classes utilize multi-processors. The resulting process abstractions provide a distributed system which can utilize thousands of processors. High-level networking protocols such as SNA, OSI, and a proprietary network are built atop this base. A relational database provides distributed data and distributed transactions. An application generator allows users to develop fault-tolerant applications as though the system were a conventional computer. The resulting system has price/performance competitive with conventional systems.

In this paper, I describe first the background behind the development of the original ARIES recovery method, and its significant impact on the commercial world and the research community. Next, I provide a brief introduction to the various concurrency control and recovery methods in the ARIES family of algorithms. Subsequently, I discuss some of the recent developments affecting the transaction management area and what these mean for the future. In ARIES, the concept of repeating history turned out to be an important paradigm. As I examine where transaction management is headed in the world of the internet, I observe history repeating itself in the sense of requirements that used to be considered significant in the mainframe world (e.g., performance, availability and reliability) now becoming important requirements of the broader information technology community as well. 1. Introduction Transaction management is one of the most important functionalities provided by a...

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Testing the reliability of high performance transaction processing systems poses many difficult challenges that are not adequately answered by conventional testing techniques. We discuss a new test paradigm, which is dynamic and exploratory in nature, and discuss its ability to meet these challenges. We describe an implementation of this paradigm in products that aid in efficiently testing reliable, high performance transaction processing systems at Tandem Computers Inc. 1 Introduction Mission critical database applications, e.g., a stock market system, insist on guaranteed data integrity in all situations. They also demand extremely high performance and high system availability (the cost of even short outages, of the order of minutes, is prohibitively high). Such applications employ high performance transaction processing systems that also have high availability characteristics ([TDG87], [SKPO88], [MHLPS92]). Tandem's NonStop SQL ([TDG87], [TPG88], [BP88]) is one such syst...

In this paper, I describe first the background behind the development of the original ARIES recovery method, and its significant impact on the commercial world and the research community.

An analysis of the failure statistics of a commercially available fault-tolerant system shows that administration and software are the major contributors to failure. Various approachs to software faulttolerance are then discussed notably process-pairs, transactions and reliable storage. It is pointed out that faults in production software are often soft (transient) and that a transaction mechanism combined with persistent process-pairs provides fault-tolerant execution-- the key to software fault-tolerance. DISCLAIMER This paper is not an "official " Tandem statement on fault-tolerance.