Temporal Querying Constructs and the TSQL2 Language
26.2.4 Temporal Querying Constructs and the TSQL2 Language
So far, we have discussed how data models may be extended with temporal con- structs. Now we give a brief overview of how query operations need to be extended for temporal querying. We will briefly discuss the TSQL2 language, which extends SQL for querying valid time, transaction time, and bitemporal relational databases.
In nontemporal relational databases, the typical selection conditions involve attrib-
26.2 Temporal Database Concepts 955
current tuples. Following that, the attributes of interest to the query are specified by
a projection operation (see Chapter 6). For example, in the query to retrieve the names of all employees working in department 5 whose salary is greater than 30000, the selection condition would be as follows:
((Salary > 30000) AND (Dno = 5)) The projected attribute would be Name . In a temporal database, the conditions may
involve time in addition to attributes. A pure time condition involves only time— for example, to select all employee tuple versions that were valid on a certain time
point T or that were valid during a certain time period [ T 1 ,T 2 ] . In this case, the spec- ified time period is compared with the valid time period of each tuple version [ T .Vst , T .Vet] , and only those tuples that satisfy the condition are selected. In these opera-
tions, a period is considered to be equivalent to the set of time points from T 1 to T 2 inclusive, so the standard set comparison operations can be used. Additional opera- tions, such as whether one time period ends before another starts are also needed. 21
Some of the more common operations used in queries are as follows:
[T .Vst ,T .Vet ] INCLUDES [ T 1 ,T 2 ]
Equivalent to T 1 ≥ T. Vst AND T 2 ≤ T. Vet
[T .Vst ,T .Vet ] INCLUDED_IN [ T 1 ,T 2 ]
Equivalent to T 1 ≤T .Vst AND T 2 ≥ T. Vet
[T .Vst ,T .Vet ] OVERLAPS [ T 1 ,T 2 ]
Equivalent to (T 1 ≤ T. Vet AND T 2 ≥T .Vst ) 22
[T .Vst ,T .Vet ] BEFORE [ T 1 ,T 2 ]
Equivalent to T 1 ≥T .Vet
[T .Vst ,T .Vet ] AFTER [ T 1 ,T 2 ]
Equivalent to T 2 ≤T .Vst [T .Vst ,T .Vet ] MEETS_BEFORE [ T 1 ,T 2 ] Equivalent to T 1 =T .Vet +1 23
[T .Vst ,T .Vet ] MEETS_AFTER [ T 1 ,T 2 ]
Equivalent to T 2 +1=T .Vst
Additionally, operations are needed to manipulate time periods, such as computing the union or intersection of two time periods. The results of these operations may not themselves be periods, but rather temporal elements—a collection of one or more disjoint time periods such that no two time periods in a temporal element are
directly adjacent. That is, for any two time periods [ T 1 ,T 2 ] and [ T 3 ,T 4 ] in a tempo- ral element, the following three conditions must hold:
[T 1 ,T 2 ] intersection [T 3 ,T 4 ] is empty.
T 3 is not the time point following T 2 in the given granularity.
T 1 is not the time point following T 4 in the given granularity.
The latter conditions are necessary to ensure unique representations of temporal elements. If two time periods [ T 1 ,T 2 ] and [ T 3 ,T 4 ] are adjacent, they are combined
21 A complete set of operations, known as Allen’s algebra (Allen, 1983), has been defined for compar- ing time periods. 22 This operation returns true if the intersection of the two periods is not empty; it has also been called INTERSECTS_WITH.
956 Chapter 26 Enhanced Data Models for Advanced Applications
into a single time period [ T 1 ,T 4 ] . This is called coalescing of time periods. Coalescing also combines intersecting time periods.
To illustrate how pure time conditions can be used, suppose a user wants to select all employee versions that were valid at any point during 2002. The appropriate selec- tion condition applied to the relation in Figure 26.8 would be
[T .Vst ,T .Vet ] OVERLAPS [2002-01-01, 2002-12-31] Typically, most temporal selections are applied to the valid time dimension. For a
bitemporal database, one usually applies the conditions to the currently correct tuples with uc as their transaction end times. However, if the query needs to be applied to a previous database state, an AS_OF T clause is appended to the query, which means that the query is applied to the valid time tuples that were correct in the database at time T.
In addition to pure time conditions, other selections involve attribute and time conditions . For example, suppose we wish to retrieve all EMP_VT tuple versions T for employees who worked in department 5 at any time during 2002. In this case, the condition is
[T .Vst ,T .Vet ] OVERLAPS [2002-01-01, 2002-12-31] AND (T. Dno = 5) Finally, we give a brief overview of the TSQL2 query language, which extends SQL
with constructs for temporal databases. The main idea behind TSQL2 is to allow users to specify whether a relation is nontemporal (that is, a standard SQL relation) or temporal. The CREATE TABLE statement is extended with an optional AS clause to allow users to declare different temporal options. The following options are avail- able:
< AS VALID STATE <GRANULARITY> (valid time relation with valid time period) < AS VALID EVENT <GRANULARITY> (valid time relation with valid time point) < AS TRANSACTION (transaction time relation with transaction time period) < AS VALID STATE <GRANULARITY> AND TRANSACTION (bitemporal rela- tion, valid time period) < AS VALID EVENT <GRANULARITY> AND TRANSACTION (bitemporal rela- tion, valid time point)
The keywords STATE and EVENT are used to specify whether a time period or time point is associated with the valid time dimension. In TSQL2, rather than have the user actually see how the temporal tables are implemented (as we discussed in the previous sections), the TSQL2 language adds query language constructs to specify various types of temporal selections, temporal projections, temporal aggregations, transformation among granularities, and many other concepts. The book by Snodgrass et al. (1995) describes the language.
26.3 Spatial Database Concepts 957
Parts
» Fundamentals_of_Database_Systems,_6th_Edition
» Characteristics of the Database Approach
» Advantages of Using the DBMS Approach
» A Brief History of Database Applications
» Schemas, Instances, and Database State
» The Three-Schema Architecture
» The Database System Environment
» Centralized and Client/Server Architectures for DBMSs
» Classification of Database Management Systems
» Domains, Attributes, Tuples, and Relations
» Key Constraints and Constraints on NULL Values
» Relational Databases and Relational Database Schemas
» Integrity, Referential Integrity, and Foreign Keys
» Update Operations, Transactions, and Dealing with Constraint Violations
» SQL Data Definition and Data Types
» Specifying Constraints in SQL
» The SELECT-FROM-WHERE Structure of Basic SQL Queries
» Ambiguous Attribute Names, Aliasing, Renaming, and Tuple Variables
» Substring Pattern Matching and Arithmetic Operators
» INSERT, DELETE, and UPDATE Statements in SQL
» Comparisons Involving NULL and Three-Valued Logic
» Nested Queries, Tuples, and Set/Multiset Comparisons
» The EXISTS and UNIQUE Functions in SQL
» Joined Tables in SQL and Outer Joins
» Grouping: The GROUP BY and HAVING Clauses
» Discussion and Summary of SQL Queries
» Specifying General Constraints as Assertions in SQL
» Introduction to Triggers in SQL
» Specification of Views in SQL
» View Implementation, View Update, and Inline Views
» Schema Change Statements in SQL
» Sequences of Operations and the RENAME Operation
» The UNION, INTERSECTION, and MINUS Operations
» The CARTESIAN PRODUCT (CROSS PRODUCT) Operation
» Variations of JOIN: The EQUIJOIN and NATURAL JOIN
» Additional Relational Operations
» Examples of Queries in Relational Algebra
» The Tuple Relational Calculus
» The Domain Relational Calculus
» Using High-Level Conceptual Data Models
» Entity Types, Entity Sets, Keys, and Value Sets
» Relationship Types, Relationship Sets, Roles, and Structural Constraints
» ER Diagrams, Naming Conventions, and Design Issues
» Example of Other Notation: UML Class Diagrams
» Relationship Types of Degree Higher than Two
» Subclasses, Superclasses, and Inheritance
» Constraints on Specialization and Generalization
» Specialization and Generalization Hierarchies
» Modeling of UNION Types Using Categories
» A Sample UNIVERSITY EER Schema, Design Choices, and Formal Definitions
» Data Abstraction, Knowledge Representation, and Ontology Concepts
» ER-to-Relational Mapping Algorithm
» Discussion and Summary of Mapping for ER Model Constructs
» Mapping EER Model Constructs
» The Role of Information Systems
» The Database Design and Implementation Process
» Use of UML Diagrams as an Aid to Database Design Specification 6
» Rational Rose: A UML-Based Design Tool
» Automated Database Design Tools
» Introduction to Object-Oriented Concepts and Features
» Object Identity, and Objects versus Literals
» Complex Type Structures for Objects and Literals
» Encapsulation of Operations and Persistence of Objects
» Type Hierarchies and Inheritance
» Other Object-Oriented Concepts
» Object-Relational Features: Object Database Extensions to SQL
» Overview of the Object Model of ODMG
» Built-in Interfaces and Classes in the Object Model
» Atomic (User-Defined) Objects
» Extents, Keys, and Factory Objects
» The Object Definition Language ODL
» Differences between Conceptual Design of ODB and RDB
» Mapping an EER Schema to an ODB Schema
» Query Results and Path Expressions
» Overview of the C++ Language Binding in the ODMG Standard
» Structured, Semistructured, and Unstructured Data
» XML Hierarchical (Tree) Data Model
» Well-Formed and Valid XML Documents and XML DTD
» XPath: Specifying Path Expressions in XML
» XQuery: Specifying Queries in XML
» Extracting XML Documents from
» Database Programming: Techniques
» Retrieving Single Tuples with Embedded SQL
» Retrieving Multiple Tuples with Embedded SQL Using Cursors
» Specifying Queries at Runtime Using Dynamic SQL
» SQLJ: Embedding SQL Commands in Java
» Retrieving Multiple Tuples in SQLJ Using Iterators
» Database Programming with SQL/CLI Using C
» JDBC: SQL Function Calls for Java Programming
» Database Stored Procedures and SQL/PSM
» PHP Variables, Data Types, and Programming Constructs
» Overview of PHP Database Programming
» Imparting Clear Semantics to Attributes in Relations
» Redundant Information in Tuples and Update Anomalies
» Normal Forms Based on Primary Keys
» General Definitions of Second and Third Normal Forms
» Multivalued Dependency and Fourth Normal Form
» Join Dependencies and Fifth Normal Form
» Inference Rules for Functional Dependencies
» Minimal Sets of Functional Dependencies
» Properties of Relational Decompositions
» Dependency-Preserving Decomposition
» Dependency-Preserving and Nonadditive (Lossless) Join Decomposition into 3NF Schemas
» Problems with NULL Values and Dangling Tuples
» Discussion of Normalization Algorithms and Alternative Relational Designs
» Further Discussion of Multivalued Dependencies and 4NF
» Other Dependencies and Normal Forms
» Memory Hierarchies and Storage Devices
» Hardware Description of Disk Devices
» Magnetic Tape Storage Devices
» Placing File Records on Disk
» Files of Unordered Records (Heap Files)
» Files of Ordered Records (Sorted Files)
» External Hashing for Disk Files
» Hashing Techniques That Allow Dynamic File Expansion
» Other Primary File Organizations
» Parallelizing Disk Access Using RAID Technology
» Types of Single-Level Ordered Indexes
» Some General Issues Concerning Indexing
» Algorithms for External Sorting
» Implementing the SELECT Operation
» Implementing the JOIN Operation
» Algorithms for PROJECT and Set
» Notation for Query Trees and Query Graphs
» Heuristic Optimization of Query Trees
» Catalog Information Used in Cost Functions
» Examples of Cost Functions for SELECT
» Examples of Cost Functions for JOIN
» Example to Illustrate Cost-Based Query Optimization
» Factors That Influence Physical Database Design
» Physical Database Design Decisions
» An Overview of Database Tuning in Relational Systems
» Transactions, Database Items, Read and Write Operations, and DBMS Buffers
» Why Concurrency Control Is Needed
» Transaction and System Concepts
» Desirable Properties of Transactions
» Serial, Nonserial, and Conflict-Serializable Schedules
» Testing for Conflict Serializability of a Schedule
» How Serializability Is Used for Concurrency Control
» View Equivalence and View Serializability
» Types of Locks and System Lock Tables
» Guaranteeing Serializability by Two-Phase Locking
» Dealing with Deadlock and Starvation
» Concurrency Control Based on Timestamp Ordering
» Multiversion Concurrency Control Techniques
» Validation (Optimistic) Concurrency
» Granularity of Data Items and Multiple Granularity Locking
» Using Locks for Concurrency Control in Indexes
» Other Concurrency Control Issues
» Recovery Outline and Categorization of Recovery Algorithms
» Caching (Buffering) of Disk Blocks
» Write-Ahead Logging, Steal/No-Steal, and Force/No-Force
» Transaction Rollback and Cascading Rollback
» NO-UNDO/REDO Recovery Based on Deferred Update
» Recovery Techniques Based on Immediate Update
» The ARIES Recovery Algorithm
» Recovery in Multidatabase Systems
» Introduction to Database Security Issues 1
» Discretionary Access Control Based on Granting and Revoking Privileges
» Mandatory Access Control and Role-Based Access Control for Multilevel Security
» Introduction to Statistical Database Security
» Introduction to Flow Control
» Encryption and Public Key Infrastructures
» Challenges of Database Security
» Distributed Database Concepts 1
» Types of Distributed Database Systems
» Distributed Database Architectures
» Data Replication and Allocation
» Example of Fragmentation, Allocation, and Replication
» Query Processing and Optimization in Distributed Databases
» Overview of Transaction Management in Distributed Databases
» Overview of Concurrency Control and Recovery in Distributed Databases
» Current Trends in Distributed Databases
» Distributed Databases in Oracle 13
» Generalized Model for Active Databases and Oracle Triggers
» Design and Implementation Issues for Active Databases
» Examples of Statement-Level Active Rules
» Time Representation, Calendars, and Time Dimensions
» Incorporating Time in Relational Databases Using Tuple Versioning
» Incorporating Time in Object-Oriented Databases Using Attribute Versioning
» Temporal Querying Constructs and the TSQL2 Language
» Spatial Database Concepts 24
» Multimedia Database Concepts
» Clausal Form and Horn Clauses
» Datalog Programs and Their Safety
» Evaluation of Nonrecursive Datalog Queries
» Introduction to Information Retrieval
» Types of Queries in IR Systems
» Evaluation Measures of Search Relevance
» Web Analysis and Its Relationship to Information Retrieval
» Analyzing the Link Structure of Web Pages
» Approaches to Web Content Analysis
» Trends in Information Retrieval
» Data Mining as a Part of the Knowledge
» Goals of Data Mining and Knowledge Discovery
» Types of Knowledge Discovered during Data Mining
» Market-Basket Model, Support, and Confidence
» Frequent-Pattern (FP) Tree and FP-Growth Algorithm
» Other Types of Association Rules
» Approaches to Other Data Mining Problems
» Commercial Data Mining Tools
» Data Modeling for Data Warehouses
» Difficulties of Implementing Data Warehouses
» Grouping, Aggregation, and Database Modification in QBE
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