this paper, we study two alternatives to index modification, namely OAT (One-At-a-Time page movement) and BULK (bulk page movement). OAT and BULK are two extremes on the spectrum of the granularity of data movement. OAT and BULK differ in two respects: first, OAT uses very little additional disk space (at most one extra page), whereas BULK uses a large amount of disk space. Second, BULK uses sequential prefetch I/O to optimize on the number of I/Os during index modification, while OAT does not. Using an experimental testbed, we show that BULK is an order of magnitude faster than OAT. In terms of the impact on transaction performance during reorganization, BULK and OAT perform differently: when the number of indexes to be modified is either one or two, OAT has a lesser impact on the transaction performance degradation. However, when the number of indexes is greater than 2, both techniques have the same impact on transaction performance.

In this paper, we present an efficient method to do online reorganization of sparsely-populated B + -trees. It reorganizes the leaves first, compacting in short operations groups of leaves with the same parent. After compacting, optionally, the new leaves may swap locations or be moved into empty pages so that they are in key order on the disk. After the leaves are reorganized, the method shrinks the tree by making a copy of the upper part of the tree while leaving the leaves in place. A new concurrency method is introduced so that only a minimum number of pages are locked during reorganization. During leaf reorganization, Forward Recovery is used to save all work already done while maintaining consistency after system crashes. A heuristic algorithm is developed to reduce the number of swaps needed during leaf reorganization, so that better concurrency and easier recovery can be achieved. A detailed description of switching from the old B + -tree to the new B + -tree is describe...

With today’s demands for continuous avail-ability of mission-critical databases, on-line reorganization is a necessity. In this paper we present a new on-Iine reorganization algo-rithm which defers secondary index updates and piggybacks them with user transactions. In addition to the significant reduction of the total I/O cost, the algorithm also assures that almost all the database is available all of the time and that the reorganization is interrupt-ible and restartable. We believe that the tech-nique presented in this paper could be used for improving normal database update perfor-mance as well. 1

In recent years, as more applications start using massive databases as their main source of information, more emphasis is placed on the performance of the database system. These require not only that the database system have good performance, but also that it be continually available. The research in this thesis makes strides in meeting these requirements: dynamically clustering data improves the database performance, and efficient on-line reorganization methods enable the database systems to be continually available. An new algorithm, Enc, for dynamically clustering hierarchical data is presented in this thesis. It uses a primary B + -tree as the main storage structure, all relations in the hierarchy are stored in the B + -tree. The hierarchical relationship is encoded into the keys of the B + -tree. The Enc algorithm maintains good clustering in the presence of insertions and deletions. Experimental results show that using the Enc algorithm, hierarchical queries can be process...

Reorganization of objects in an object databases is an important component of several operations like compaction, clustering, and schema evolution. The high availability requirements #24 # 7 operation# of certain application domains requires reorganization to be performed on-line with minimal intereference to concurrently executing transactions. In this paper, we address the problem of on-line reorganization in object databases, where a set of objects have to be migrated from one location to another. Speci#cally,we consider the case where objects in the database may contain physical references to other objects. Relocating an object in this case involves #nding the set of objects #parents# that refer to it, and modifying the references in each parent. We propose an algorithm called the Incremental Reorganization Algorithm #IRA# that achieves the above task with minimal interference to concurrently executing transactions. The IRA algorithm holds locks on at most two distinct objects at ...

this paper, we propose online heat balancing strategies for Btree index over parallel shared nothing machines based on the principle of distributing the given heat as evenly as possible across the system PEs. Furthermore, the proposed strategies have the capability to reduce the instantaneous migration cost during the heat balancing process, which in turn avoid the harmful migrations that may degrade the system performance. We evaluate the performance of the proposed strategies in comparison with the well-known strategies. The conducted simulation shows their efficiency in correcting the system performance degradation.

We present a model for data reorganization in parallel disk systems that is geared towards load t)ahmcing m an environment with periodic access patterns. Data reorganization is performed by disk cooling, i e., migrating files or extents from the hottest disks to tim coldest <mes. \Ve develop an approximate queueing model for determining the effective arrival rates of cooling requests and discuss its use in assessing the costs versus benefits of cooling actions. Index Terms: database reorganization, load balancing, temporal access patterns, parallel disk systems, approximate queue-ing model. I/O service stealing 1

Introduction On-line reorganization is and will be a major problem for transaction systems of the 1990s and the 2000s. Mainframes are rapidly being replaced by workstation farms. Most large software systems must eventually be ported to these new cheaper hardware architectures. The new hardware architectures lend themselves to a client-server software architecture. Presentation services are off-loaded to client workstations. Even servers are no longer on mainframes, but instead on collections of workstations, each perhaps responsible for only a part of the database. Application software will have to be rewritten to conform to the new hardware and software architectures. In addition, some companies may want to take advantage of newer object-oriented software and object-relational systems and new indexing and presentation options. They must then reorganize their data to make the best use of these new software systems. But at the same time, large companies such as airlines and ba

In shared nothing machines, data are typically declustered and indexed across the system processing elements (PEs) to achieve efficient query and transaction execution. Since the access pattern is inherently dynamic, therefore, there is no one placement of relations that is optimal for the lifetime of the database system. Whenever data is moved across PEs, the indexes need to be modified too. Consequently reorganization based on the access history (heat) of the data or its corresponding index is essential and should be online, in addition, it should satisfactorily deal with the index modification, as data is moving across the PEs. In this paper, we study the heat balancing strategies that have the capability of minimizing the index modification. Meanwhile, it has been observed that the system performance during reorganization is greatly affect by the cost of the balancing decisions (migration cost) and the location of the hot spot in the system. In this paper, we propo...

In shared-nothing environments, data is typically declustered and indexed across the system processing elements (PEs) to achieve efficient processing. However access patterns are inherently dynamic and skewed, thus, data reorganization based on the data access history (heat) is essential and should be done online. While the data is being reorganized, indexes need to be modified too, therefore, reorganization should additionally deal with the index modification. Based on minimization of index modification, we propose a data reorganization technique over a shared-nothing parallel system. By finding the exact work that should be done, the technique can smoothly balance a given heat across the PEs as fast as possible, if it is required. By tuning its parameters, it can cover a wide range of balancing requirements. We evaluate its performance through simulation studies. Its effectiveness is clarified quantitatively. 1