This paper presents an efficient recovery scheme suitable for real-time mainmemory database. In the recovery scheme, log records are stored in non-volatile RAM which is dividedinto four different partitions based on t...This paper presents an efficient recovery scheme suitable for real-time mainmemory database. In the recovery scheme, log records are stored in non-volatile RAM which is dividedinto four different partitions based on transaction types. Similarly, a main memory database isdivided into four partitions based data types. When the using ratio of log store area exceeds thethreshold value, checkpoint procedure is triggered. During executing checkpoint procedure, someuseless log records are deleted. During restart recovery after a crash, partition reloading policyis adopted to assure that critical data are reloaded and restored in advance, so that the databasesystem can be brought up before the entire database is reloaded into main memory. Therefore downtime is obvionsly reduced. Simulation experiments show our recovery scheme obviously improves thesystem performance, and does a favor to meet the dtadlints of real-time transactions.展开更多
Recent studies have addressed that the cache be havior is important in the design of main memory index structures. Cache-conscious indices such as the CSB^＋-tree are shown to outperform conventional main memory indic...Recent studies have addressed that the cache be havior is important in the design of main memory index structures. Cache-conscious indices such as the CSB^＋-tree are shown to outperform conventional main memory indices such as the AVL-tree and the T-tree. This paper proposes a cacheconscious version of the T-tree, CST-tree, defined according to the cache-conscious definition. To separate the keys within a node into two parts, the CST-tree can gain higher cache hit ratio.展开更多
With the full development of disk-resident databases(DRDB)in recent years,it is widely used in business and transactional applications.In long-term use,some problems of disk databases are gradually exposed.For applica...With the full development of disk-resident databases(DRDB)in recent years,it is widely used in business and transactional applications.In long-term use,some problems of disk databases are gradually exposed.For applications with high real-time requirements,the performance of using disk database is not satisfactory.In the context of the booming development of the Internet of things,domestic real-time databases have also gradually developed.Still,most of them only support the storage,processing,and analysis of data values with fewer data types,which can not fully meet the current industrial process control system data types,complex sources,fast update speed,and other needs.Facing the business needs of efficient data collection and storage of the Internet of things,this paper optimizes the transaction processing efficiency and data storage performance of the memory database,constructs a lightweight real-time memory database transaction processing and data storage model,realizes a lightweight real-time memory database transaction processing and data storage model,and improves the reliability and efficiency of the database.Through simulation,we proved that the cache hit rate of the cache replacement algorithm proposed in this paper is higher than the traditional LRU(Least Recently Used)algorithm.Using the cache replacement algorithm proposed in this paper can improve the performance of the system cache.展开更多
Storing the whole database in the main-memory is a common method to processreal-time transaction in real-time database systems. The recovery mechanism of Main-memory Real-timeDatabase Systems (MMRTDBS) should reflect ...Storing the whole database in the main-memory is a common method to processreal-time transaction in real-time database systems. The recovery mechanism of Main-memory Real-timeDatabase Systems (MMRTDBS) should reflect the characteristics of the main-memory database andreal-time database because their structures are quite different from other conventional databasesystems. In this paper, therefore, we propose a multi-level recovery mechanism for main-memoryreal-time database systems with Extendable Chained Bucket Hashing (ECBH). Owing to the occurrence ofreal-time data in real-time systems, we should also consider it in our recovery mechanism .According to our performance test, this mechanism can improve the transaction concurrency, reducingtransactions ' deadline missing rate.展开更多
As the speed gap between main memory and modern processors continues to widen, the cache behavior becomes more important for main memory database systems （MMDBs）. Indexing technique is a key component of MMDBs. Unfo...As the speed gap between main memory and modern processors continues to widen, the cache behavior becomes more important for main memory database systems （MMDBs）. Indexing technique is a key component of MMDBs. Unfortunately, the predominant indexes -B^＋-trees and T-trees -- have been shown to utilize cache poorly, which triggers the development of many cache-conscious indexes, such as CSB^＋-trees and pB^＋-trees. Most of these cache-conscious indexes are variants of conventional B^＋-trees, and have better cache performance than B^＋-trees. In this paper, we develop a novel J^＋-tree index, inspired by the Judy structure which is an associative array data structure, and propose a more cacheoptimized index -- Prefetching J^＋-tree （pJ^＋-tree）, which applies prefetching to J^＋-tree to accelerate range scan operations. The J^＋-tree stores all the keys in its leaf nodes and keeps the reference values of leaf nodes in a Judy structure, which makes J^＋-tree not only hold the advantages of Judy （such as fast single value search） but also outperform it in other aspects. For example, J^＋-trees can achieve better performance on range queries than Judy. The pJ^＋-tree index exploits prefetching techniques to further improve the cache behavior of J^＋-trees and yields a speedup of 2.0 on range scans. Compared with B^＋-trees, CSB^＋-trees, pB^＋-trees and T-trees, our extensive experimental Study shows that pJ^＋-trees can provide better performance on both time （search, scan, update） and space aspects.展开更多
文摘This paper presents an efficient recovery scheme suitable for real-time mainmemory database. In the recovery scheme, log records are stored in non-volatile RAM which is dividedinto four different partitions based on transaction types. Similarly, a main memory database isdivided into four partitions based data types. When the using ratio of log store area exceeds thethreshold value, checkpoint procedure is triggered. During executing checkpoint procedure, someuseless log records are deleted. During restart recovery after a crash, partition reloading policyis adopted to assure that critical data are reloaded and restored in advance, so that the databasesystem can be brought up before the entire database is reloaded into main memory. Therefore downtime is obvionsly reduced. Simulation experiments show our recovery scheme obviously improves thesystem performance, and does a favor to meet the dtadlints of real-time transactions.
基金Supported bythe National High Technology of 863Project (2002AA1Z2308 ,2002AA118030)
文摘Recent studies have addressed that the cache be havior is important in the design of main memory index structures. Cache-conscious indices such as the CSB^＋-tree are shown to outperform conventional main memory indices such as the AVL-tree and the T-tree. This paper proposes a cacheconscious version of the T-tree, CST-tree, defined according to the cache-conscious definition. To separate the keys within a node into two parts, the CST-tree can gain higher cache hit ratio.
基金supported by the National Key R&D Program of China“Key technologies for coordination and interoperation of power distribution service resource”[2021YFB1302400]“Research on Digitization and Intelligent Application of Low-Voltage Power Distribution Equipment”[SGSDDK00PDJS2000375].
文摘With the full development of disk-resident databases(DRDB)in recent years,it is widely used in business and transactional applications.In long-term use,some problems of disk databases are gradually exposed.For applications with high real-time requirements,the performance of using disk database is not satisfactory.In the context of the booming development of the Internet of things,domestic real-time databases have also gradually developed.Still,most of them only support the storage,processing,and analysis of data values with fewer data types,which can not fully meet the current industrial process control system data types,complex sources,fast update speed,and other needs.Facing the business needs of efficient data collection and storage of the Internet of things,this paper optimizes the transaction processing efficiency and data storage performance of the memory database,constructs a lightweight real-time memory database transaction processing and data storage model,realizes a lightweight real-time memory database transaction processing and data storage model,and improves the reliability and efficiency of the database.Through simulation,we proved that the cache hit rate of the cache replacement algorithm proposed in this paper is higher than the traditional LRU(Least Recently Used)algorithm.Using the cache replacement algorithm proposed in this paper can improve the performance of the system cache.
文摘Storing the whole database in the main-memory is a common method to processreal-time transaction in real-time database systems. The recovery mechanism of Main-memory Real-timeDatabase Systems (MMRTDBS) should reflect the characteristics of the main-memory database andreal-time database because their structures are quite different from other conventional databasesystems. In this paper, therefore, we propose a multi-level recovery mechanism for main-memoryreal-time database systems with Extendable Chained Bucket Hashing (ECBH). Owing to the occurrence ofreal-time data in real-time systems, we should also consider it in our recovery mechanism .According to our performance test, this mechanism can improve the transaction concurrency, reducingtransactions ' deadline missing rate.
基金supported by a grant from HP Lab China,and the National Natural Science Foundation of China under Grant Nos.60496325 and 60573092
文摘As the speed gap between main memory and modern processors continues to widen, the cache behavior becomes more important for main memory database systems （MMDBs）. Indexing technique is a key component of MMDBs. Unfortunately, the predominant indexes -B^＋-trees and T-trees -- have been shown to utilize cache poorly, which triggers the development of many cache-conscious indexes, such as CSB^＋-trees and pB^＋-trees. Most of these cache-conscious indexes are variants of conventional B^＋-trees, and have better cache performance than B^＋-trees. In this paper, we develop a novel J^＋-tree index, inspired by the Judy structure which is an associative array data structure, and propose a more cacheoptimized index -- Prefetching J^＋-tree （pJ^＋-tree）, which applies prefetching to J^＋-tree to accelerate range scan operations. The J^＋-tree stores all the keys in its leaf nodes and keeps the reference values of leaf nodes in a Judy structure, which makes J^＋-tree not only hold the advantages of Judy （such as fast single value search） but also outperform it in other aspects. For example, J^＋-trees can achieve better performance on range queries than Judy. The pJ^＋-tree index exploits prefetching techniques to further improve the cache behavior of J^＋-trees and yields a speedup of 2.0 on range scans. Compared with B^＋-trees, CSB^＋-trees, pB^＋-trees and T-trees, our extensive experimental Study shows that pJ^＋-trees can provide better performance on both time （search, scan, update） and space aspects.
