Data access

About: Data access is a research topic. Over the lifetime, 13141 publications have been published within this topic receiving 172859 citations. The topic is also known as: Data access.

Broadcasting information and providing data access over the internet to investors and managers on demand

Abstract: A system and method for providing real time information access to investors is disclosed Embodiments of the present invention as disclosed collect live productivity data and streaming media information broadcast from remote sites of interest (such as oil and gas drilling locations, construction sites, etc) in real-time into a collection and distribution network that delivers this data and information to investors and managers via the Internet via a dynamic web page interface Such web pages according to the present invention allow the user to select and set the data and streaming media, including real-time video images, from an array of choices as well as access time-stamped past data and streaming media According to preferred embodiments of the invention, satellite transmissions are employed to send the data and information from the remote sites

An efficient replicated data access approach for large-scale distributed systems

Abstract: In data-intensive distributed systems, replication is the most widely used approach to offer high data availability, low bandwidth consumption, increased fault-tolerance and improved scalability of the overall system. Replication-based systems implement replica control protocols that enforce a specified semantics of accessing the data. Also, the performance depends on a host of factors chief of which is the protocol used to maintain consistency among object replica. In this paper, we propose a new low-cost and high data availability protocol for maintaining replicated data on networked distributed computing systems. We show that the proposed approach provides high data availability, low bandwidth consumption, increased fault-tolerance and improved scalability of the overall system as compared to standard replica control protocols.

Trekking through Siberia: managing cold data in a memory-optimized database

Abstract: Main memories are becoming sufficiently large that most OLTP databases can be stored entirely in main memory, but this may not be the best solution. OLTP workloads typically exhibit skewed access patterns where some records are hot (frequently accessed) but many records are cold (infrequently or never accessed). It is still more economical to store the coldest records on secondary storage such as flash. This paper introduces Siberia, a framework for managing cold data in the Microsoft Hekaton main-memory database engine. We discuss how to migrate cold data to secondary storage while providing an interface to the user to manipulate both hot and cold data that hides the actual data location. We describe how queries of different isolation levels can read and modify data stored in both hot and cold stores without restriction while minimizing number of accesses to cold storage. We also show how records can be migrated between hot and cold stores while the DBMS is online and active. Experiments reveal that for cold data access rates appropriate for main-memory optimized databases, we incur an acceptable 7-14% throughput loss.

On the Design and Scalability of Distributed Shared-Data Databases

Abstract: Database scale-out is commonly implemented by partitioning data across several database instances. This approach, however, has several restrictions. In particular, partitioned databases are inflexible in large-scale deployments and assume a partition-friendly workload in order to scale. In this paper, we analyze an alternative architecture design for distributed relational databases that overcomes the limitations of partitioned databases. The architecture is based on two fundamental principles: We decouple query processing and transaction management from data storage, and we share data across query processing nodes. The combination of these design choices provides scalability, elasticity, and operational flexibility without making any assumptions on the workload. As a drawback, sharing data among multiple database nodes causes synchronization overhead. To address this limitation, we introduce techniques for scalable transaction processing in shared-data environments. Specifically, we describe mechanisms for efficient data access, concurrency control, and data buffering. In combination with new hardware trends, the techniques enable performance characteristics that top state-of-the-art partitioned databases.

Conditional data access after database system failure

Abstract: A method of operation within a data processing system that includes a plurality of processing nodes each having access to a set of shared resources. Failure of one of the processing nodes is detected, followed by receipt of a request to access a first resource of the set of shared resources. Access to the first resource is granted if the failed node was not responsible for controlling access to the first resource and did not have exclusive access to the first resource when the failure was detected.