We propose a semantic model for client-side caching and replacement in a client-server database system and compare this approach to page caching and tuple caching strategies. Our caching model is based on, and derives its advantages from, three key ideas. First, the client maintains a semantic description of the data in its cache,which allows for a compact specification, as a remainder query, of the tuples needed to answer a query that are not available in the cache. Second, usage information for replacement policies is maintained in an adaptive fashion for semantic regions, which are associated with collections of tuples. This avoids the high overheads of tuple caching and, unlike page caching, is insensitive to bad clustering. Third, maintaining a semantic description of cached data enables the use of sophisticated value functions that incorporate semantic notions of locality, not just LRU or MRU, for cache replacement. We validate these ideas with a detailed performance study that i...

object encapsulation and enable local reasoning about program correctness in object-oriented languages. However, a type system that enforces strict object encapsulation is too constraining: it does not allow e#cient implementation of important constructs like iterators. This paper argues that the right way to solve the problem is to allow objects of classes defined in the same module to have privileged access to each other's representations; we show how to do this for inner classes. This approach allows programmers to express constructs like iterators and yet supports local reasoning about the correctness of the classes, because a class and its inner classes together can be reasoned about as a module. The paper also sketches how we use our variant of ownership types to enable e#cient software upgrades in persistent object stores.

The construction of high-performance database systems that combine the best aspects of the relational and object-oriented approaches requires the design of client-server architectures that can fully exploit client and server resources in a flexible manner. The two predominant paradigms for client-server query execution are datashipping and query-shipping. We first define these policies in terms of the restrictions they place on operator site selection during query optimization. We then investigate the performance tradeoffs between them for bulk query processing. While each strategy has advantages, neither one on its own is efficient across a wide range of circumstances. We describe andevaluate a more flexible policy called hybrid-shipping, which can execute queries at clients, servers, or any combination of the two. Hybrid-shipping is shown to at least match the best of the two "pure" policies, and in some situations, to perform better than both. The implementation of hybrid-shipping rais...

No single encoding scheme or fault model is optimal for all data. A versatile storage system allows them to be matched to access patterns, reliability requirements, and cost goals on a per-data item basis. Ursa Minor is a cluster-based storage system that allows data-specific selection of, and on-line changes to, encoding schemes and fault models. Thus, different data types can share a scalable storage infrastructure and still enjoy specialized choices, rather than suffering from "one size fits all." Experiments with Ursa Minor show performance benefits of 2--3 when using specialized choices as opposed to a single, more general, configuration. Experiments also show that a single cluster supporting multiple workloads simultaneously is much more efficient when the choices are specialized for each distribution rather than forced to use a "one size fits all" configuration. When using the specialized distributions, aggregate cluster throughput nearly doubled.

A decade ago, the connection between objects and databases was new and was being explored in a number of di erent ways within our community. Driven by the perception that managing traditional business data was largely a solved problem, projects data types to relational databases and building extensible database systems, objectoriented database systems, and toolkits for constructing special-purpose database systems. In addition, work was underway elsewhere in the computer science research community on extending programming languages with database-inspired features such aspersistence and transactions. In this paper, we take a look at where our eld was a decade ago and where it is now in terms of database support for objects (and vice versa). We look both at research projects and at commercial database products. We share our vision and our biases about the future of objects and databases, and we identify anumber of research challenges that remain to be addressed in order to ultimately achieve our vision.

THOR is a persistent object store that provides a powerful programming model. THOR ensures that persistent objects are accessed only by calling their methods and it supports atomic transactions. The result is a system that allows applications to share objects safely across both space and time. The paper

Relational DBMS typically execute concurrent queries independently by invoking a set of operator instances for each query. To exploit common data retrievals and computation in concurrent queries, researchers have proposed a wealth of techniques, ranging from buffering disk pages to constructing materialized views and optimizing multiple queries. The ideas proposed, however, are inherently limited by the query-centric philosophy of modern engine designs. Ideally, the query engine should proactively coordinate same-operator execution among concurrent queries, thereby exploiting common accesses to memory and disks as well as common intermediate result computation.

Essentially all distributed systems, applications, and services at some level boil down to the problem of managing distributed shared state. Unfortunately, while the problem of managing distributed shared state is shared by many applications, there is no common means of managing the data -- every application devises its own solution. We have developed Khazana, a distributed service exporting the abstraction of a distributed persistent globally shared store that applications can use to store their shared state. Khazana is responsible for performing many of the common operations needed by distributed applications, including replication, consistency management, fault recovery, access control, and location management. Using Khazana as a form of middleware, distributed applications can be quickly developed from corresponding uniprocessor applications through the insertion of Khazana data access and synchronization operations.

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Many client-server object-oriented database systems (OODBs) run applications at clients and perform all accesses on cached copies of database objects. Moving both data and computation to the clients can improve response time, throughput, and scalability. For applications with good locality of reference, retaining cached state across transaction boundaries can result in further performance and scaling benefits. This thesis examines the question of what concurrency control scheme is best able to realize these potential benefits. It describes a new optimistic concurrency control scheme called AOCC (Adaptive Optimistic Concurrency Control) and compares its performance with that of ACBL (Adaptive-Granularity Callback Locking), the scheme shown to have the best performance in previous studies. Like all optimistic schemes, AOCC synchronizes transactions at the commit point, aborting transactions when synchronization fails; ACBL, like other locking schemes, synchronizes transactions while they execute. Earlier