TL;DR: A novel index analysis utility that can be leveraged by a variety of front-end tools and sketch important aspects of the user interfaces enabled by the utility.
Abstract: As databases get widely deployed, it becomes increasingly important to reduce the overhead of database administration. An important aspect of data administration that critically influences performance is the ability to select indexes for a database. In order to decide the right indexes for a database, it is crucial for the database administrator (DBA) to be able to perform a quantitative analysis of the existing indexes. Furthermore, the DBA should have the ability to propose hypothetical (“what-if”) indexes and quantitatively analyze their impact on performance of the system. Such impact analysis may consist of analyzing workloads over the database, estimating changes in the cost of a workload, and studying index usage while taking into account projected changes in the sizes of the database tables. In this paper we describe a novel index analysis utility that we have prototyped for Microsoft SQL Server 7.0. We describe the interfaces exposed by this utility that can be leveraged by a variety of front-end tools and sketch important aspects of the user interfaces enabled by the utility. We also discuss the implementation techniques for efficiently supporting “what-if” indexes. Our framework can be extended to incorporate analysis of other aspects of physical database design.
TL;DR: This paper proposes a new index structure, the T Tree, and it is compared to existing index structures in a main memory database environment, and results indicate that the T tree provides good overall performance in main memory.
TL;DR: In this paper, the authors proposed a dual-stage index architecture that achieves both space efficiency and high performance by periodically migrating entries from the first stage to the second, which uses a more compact, read-optimized data structure.
Abstract: Using indexes for query execution is crucial for achieving high performance in modern on-line transaction processing databases. For a main-memory database, however, these indexes consume a large fraction of the total memory available and are thus a major source of storage overhead of in-memory databases. To reduce this overhead, we propose using a two-stage index: The first stage ingests all incoming entries and is kept small for fast read and write operations. The index periodically migrates entries from the first stage to the second, which uses a more compact, read-optimized data structure. Our first contribution is hybrid index, a dual-stage index architecture that achieves both space efficiency and high performance. Our second contribution is Dual-Stage Transformation (DST), a set of guidelines for converting any order-preserving index structure into a hybrid index. Our third contribution is applying DST to four popular order-preserving index structures and evaluating them in both standalone microbenchmarks and a full in-memory DBMS using several transaction processing workloads. Our results show that hybrid indexes provide comparable throughput to the original ones while reducing the memory overhead by up to 70%.
TL;DR: In this article, an efficient method of generating a bit-reverse index array in real-time without performing any bit manipulation for a wireless communication system is presented, which can be used for wireless communication systems.
Abstract: An efficient method of generating a bit-reverse index array in real time without performing any bit manipulation for a wireless communication system.
TL;DR: An index selection tool helps reduce costs in time and memory in selecting an index configuration or set of indexes for use by a database server in accessing a database in accordance with a workload of queries.
Abstract: An index selection tool helps reduce costs in time and memory in selecting an index configuration or set of indexes for use by a database server in accessing a database in accordance with a workload of queries. The index selection tool attempts to reduce the number of indexes to be considered, the number of index configurations to be enumerated, and the number of invocations of a query optimizer in selecting an index configuration for the workload.