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Databases
Published in Ian Foster, Rayid Ghani, Ron S. Jarmin, Frauke Kreuter, Julia Lane, Big Data and Social Science, 2020
Relational DBMSs were traditionally motivated by the need for transaction processing and analysis, which led them to put a premium on consistency and availability. This led the designers of these systems to provide a set of properties summarized by the acronym ACID (Gray, 1981; Silberschatz et al., 2010): Atomic: All work in a transaction completes (i.e., is committed to stable storage) or none of it completes;Consistent: A transaction transforms the database from one consistent state to another consistent state;Isolated: The results of any changes made during a transaction are not visible until the transaction has committed;Durable: The results of a committed transaction survive failures.
Databases for Planning and Manufacturing
Published in Ulrich Rembold, Robot Technology and Applications, 2020
Klaus R. Dittrich, Alfons Kemper, Peter C. Lockemann
Our database schema as it currently stands treats all entities as mutually independent. Hence the second rule is trivially satisfied. The first one, however, is not. It is a typical example of an entity depending on its existence on a second one. Referential integrity does not solve the problem because it deals only with the existence of relationships. Fortunately, there is way out by means of transactions (Section 9.2.1). A transaction is a kind of database procedure consisting of a sequence of database operations that, taken in their entirety, guarantee the consistency of the database. To observe the first rule we introduce a transaction that first checks whether the desired robot exists in the database, then inserts an axis tuple, and finally a tuple into robot_axes. Provided the database system would check consistency, it would do so only at transaction end (transaction commit).
Advanced Microprocessor Architectures
Published in David R. Martinez, Robert A. Bond, Vai M. Michael, High Performance Embedded Computing Handbook, 2018
Janice McMahon, Stephen Crago, Donald Yeung
Another paradigm emerging from the research community and showing great promise for speculative execution is transactional coherence and consistency (TCC). In TCC systems, transactions serve as the fundamental unit of parallel work, communication, and coherence. A transaction is a sequence of instructions that is guaranteed to execute and complete only as an atomic unit. Each transaction produces a block of writes, called the write state, that are committed to shared memory only as an atomic unit after the transaction completes execution. As each transaction completes, it atomically writes all of its newly produced state to shared memory (called a commit), while restarting other processors that have speculatively read stale data. Therefore, data synchronization is handled correctly, without programmer intervention. A sample TCC system is shown in Figure 26-9.
Cloud-based storage and computing for remote sensing big data: a technical review
Published in International Journal of Digital Earth, 2022
Chen Xu, Xiaoping Du, Xiangtao Fan, Gregory Giuliani, Zhongyang Hu, Wei Wang, Jie Liu, Teng Wang, Zhenzhen Yan, Junjie Zhu, Tianyang Jiang, Huadong Guo
Relational database management systems (RDBMS) are a widely used database model (Codd 1970). RDBMS is oriented toward transactional operations and focuses on the properties of atomicity, consistency, isolation, and durability (ACID). The reliability and stability of RDBMS have been greatly improved with the development of RSBD. Some RDBMS, such as PostgreSQL, can manage spatial data and have been widely used for remote sensing metadata management. However, there are apparent bottlenecks in the standalone RDBMS load capacity. A cloud-based distributed RDBMS, NewSQL, was proposed to enhance the scalability of traditional RDBMS for massive structured data (Pavlo and Aslett 2016). Google Spanner is an example of this technology (Corbett et al. 2013).