Absrtact: This paper is a summary of temporal database, introduces the background of temporal database, research trends, then introduces the classification of temporal database and the existing typical models, and finally introduces the problems of temporal management and temporal database design.
L Background
Traditional database technology can reflect the real world data, but it can only reflect the current state of the real world data, only reflect the state of an object at a certain moment (snapshot), do not contact its past and future. This is what people often say about snapshot databases (Snapshot database). The modern information flow contains the temporal message of the event (temporal information), which has moment information (Instant information), time interval information (Interval information) and relative time information (before, after, overlapping) Wait a minute.
The increasingly extensive database application requires the management of the historical information of the processed events, and the temporal information of the meta events in the system. Two problems need to be urgently addressed: the first is to request the management of the historical information of the events, such as personnel, financial, financial and natural disasters and other historical data, from which the essential law of the development of things can be seen; the second is to manage the temporal information of meta events in the database system, such as increasing the check, time and interval This data can improve the reliability and efficiency of the database system, such as the prominent peculiarity of locking queue and resource competition coordination in multi-user system. Therefore, the temporal database is introduced.
L Research Trends
In the the early 1970s, many people began to explore the processing of time information in databases and information systems.
In the early 80 's, the research of temporal database began to flourish, and in 1982-1986 years, there were more than 80 papers on the temporal database. By the middle of the 80 's, the scheme of nearly hundred kinds of temporal database has been put forward, and after more than 10 years ' development and mutual learning, it is gradually merged into more than 10 kinds of accepted models.
Kahn Ketal studied the question of "temporal knowledge" in an article in the journal AI in 1977.
J. Ben Zvi A groundbreaking study of the temporal database in 1979-1982, and his doctoral thesis (UCLA, 1982) summed up a series of his work. Ben Zvi's contributions are highlighted in the following points:
(1), he proposed the temporal database model, introduced the time interval (Period), and later was renamed as the time interval by the academia.
(2) in the hot period of the study of the relationship canonical type of 1979-1982, Ben Zvi broke through the restricted area of thought, and proposed and studied the TDB of non-1NF.
(3) With the time area of the field value, refresh the people think that the database field value can only be a number or a series of ideas.
(4) introduced the concept of later called the double tense, that is, using the effective time to represent the managed objects in the library life cycle, using transaction time to represent the history of the database itself.
(5). The temporal indexing structure is introduced.
1982 J. Clifford completed his doctoral thesis at NYU "A logical frame work for the temporal semantics and Natural Language querying of historical Database "and a group of related articles, has made an important contribution to the groundbreaking of historical databases. It takes note of the lifecycle of the managed object (lifespan), studies the technical details of the information on the relationship, the tuple, the field value, introduces the historical relation model, the historical Relation algebra, and studies the special requirements and special rules of projection, selection and connection in the historical database. This paper studies the compatibility of the historical relation model with the traditional relational model, that is, when the interval is reduced to a point (now, the historical database is degraded to the traditional snapshot database, and the corresponding temporal algebra operation is degraded to the traditional snapshot relational operation (Now)).
S. American University of Southern California. Professor Ginsburg was formerly a pioneer in formal language, especially in context-free grammar studies. In 1983, he presented the object-history model (objects History).
Classification of L-Temporal database
According to Spipada and Snodgrass, the temporal database can be divided into three categories by function:
(1) Transaction database. The time that the database itself is censored is called the transaction time (Transaction times), and the transaction database supports transaction time, which he addresses by transaction time, preserving the state of the past in all state evolution. The relationship of a transaction is a three-dimensional structure consisting of a tuple, a property, and a transaction time.
(2) Historical database. The lifecycle of the managed object is called the active time (Valid times), and the historical database is similar to the transaction database in that it replaces the transaction time with the valid time instead of the static state sequence, but records a history state with each relationship. The historical relationship is also a three-dimensional structure, consisting of tuples, attributes and effective time.
(3) Temporal database can not only manage the history of the object but also manage the history of the database itself, also called the Double temporal database. He has the advantages of the first two, supporting the transaction time and the effective time. Temporal relation is a four-dimensional structure, which consists of tuple, attribute, transaction time and effective time.
Four methods of temporal information processing for DBMS
Events are often accompanied by temporal information, the traditional database only through user-defined time to record temporal information, DBMS does not have the mechanism to manage the temporal information of events. The following table lists four ways in which the DBMS handles temporal information.
The problem of L-temporal management
For a long time, in the era of no use of temporal database, the management of historical data by enterprises and institutions is to put together multiple snapshots (that is, the backup of the database saved at different times) to form a history.
(1). How much time interval do you take to save snapshots? If the interval is too large, it is not enough to ensure accurate and detailed data, if the interval is too small, the data redundancy, accounting for large storage space.
(2). In traditional relational database, multiple snapshots of a table cannot be loaded into memory at the same time, and can not be operated and queried simply by traditional selection, projection and connection operations. Because the values under the same attribute of the same tuple may be different in different snapshots, you must make more complex, generic programming.
(3). In traditional databases, the maintenance of the history of the database itself is insufficient, generally only for the recovery of the transaction log (Transaction log), the lack of the corresponding transaction query command (for example, quickly find out who made more than 10 changes to a field).
L Existing Temporal Database model
In the middle of the 80, the scheme of nearly hundred kinds of temporal database has been proposed, after more than 10 years of development and mutual learning, and gradually merged into more than 10 kinds of accepted models, of which 13 were paid the first monograph on temporal Database in the world, temporal database-theory, design and Implementation ".
(1). Time relational model, which was presented by Ben Zvi in his doctoral dissertation in 1979--1982, is a pioneering research work in the field of TDB. It pioneered the study of temporal database and temporal query language.
(2). HRDM (historical relational Data Model), J. Clifford, 1982.
(3). Tempsql, Sharshi. K. Gadia & Sunil, S. Nair, 1985.
(4). IXRM (interval-extended relational Model), Nikos A. lorentzos,1987.
(5). TRM and TSQL (temporal Extensions to the relational Model) K. B. navathe,1987.
(6). Hsql (historical Query Language), N. L. Sarda 1987.
(7). Tquel,r. Snodgrass, 1985.
(8). TRC (Temporal relational calculus), Abdullah Tansel, 1992
(9). Teer, (temporal Query Language for enhanced Entity Model), R. Relationship, 1985.
(a). TDM (Temporal Data Model Based on Time sequeuce), Arie Segev & Arie Shosham, 1988.
(one). Oodaplex (Object oriented Aplex), U. dayal,1989.
(a). Object History, S. Ginsburg, Tanaka, Tang Changjie, 1983.
From different needs and viewpoints, the above 13 TDB models have independently established a set of terms, concepts and mathematical models, and formed a set of independent theoretical systems.
The difficulties of L-temporal database in the concrete realization process
(1) Large amount of data. Temporal database is designed to manage historical data, with the passage of time, new data flow into the database, in order to ensure the TDB in the large amount of data space-time efficiency, must have efficient data storage organization and temporal indexing mechanism.
(2) In the practical application of the temporal query, selection, projection and connection operations accounted for the main resources. The optimization of temporal selection, temporal projection and temporal connection is the technical focus of TDB query optimization.
(3) on the index, due to the addition of the temporal effect, the traditional hash and B-tree, plus + trees need to be extended in order to meet the TDBMS requirements.
L Temporal data management and artificial intelligence
In the field of artificial intelligence, the mechanism of temporal inference is mainly studied. There are two types of this:
(1) Interpretation of the main data and its links this system can be used to support the natural language understanding which contains the time problem. J.f.allen's "Time zone calculus" is representative.
(2) Plans for the establishment of future activities this system can be used in the factory scheduling resources, known as "intelligent scheduling", the problem is: within a certain time limit, to develop the correct use of resources to solve a given scheduling problem.
L Reference Documents
"Special database Technology" he upstart, Tang Changjie Science Press 2000
"Temporal database Technology" Huangnan, Liu Eichen Microcomputer Development 2002 1th
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