By C. J. Date
It doesn't matter what DBMS you're using—Oracle, DB2, SQL Server, MySQL, PostgreSQL—misunderstandings can continually come up over the proper meanings of phrases, misunderstandings which can have a major influence at the luck of your database tasks. for instance, listed here are a few universal database phrases: characteristic, BCNF, consistency, denormalization, predicate, repeating staff, subscribe to dependency. have you learnt what all of them suggest? Are you sure?
The New Relational Database Dictionary defines all of those phrases and plenty of, many extra. conscientiously reviewed for readability, accuracy, and completeness, this publication is an authoritative and entire source for database execs, with over 1700 entries (many with examples) facing matters and ideas bobbing up from the relational version of knowledge. DBAs, database designers, DBMS implementers, program builders, and database professors and scholars can locate the data they want each day, info that isn't available wherever else.
Read Online or Download The New Relational Database Dictionary: Terms, Concepts, and Examples PDF
Best databases books
This e-book brings the entire components of database layout jointly in one quantity, saving the reader the time and cost of creating a number of purchases. It consolidates either introductory and complex issues, thereby masking the gamut of database layout method ? from ER and UML concepts, to conceptual facts modeling and desk transformation, to storing XML and querying relocating gadgets databases.
Oracle Call Interface. Programmer's Guide
The Oracle name Interface (OCI) is an program programming interface (API) that permits functions written in С or C++ to have interaction with a number of Oracle database servers. OCI provides your courses the potential to accomplish the complete variety of database operations which are attainable with an Oracle database server, together with SQL assertion processing and item manipulation.
Oracle Warehouse Builder 11g: Getting Started
This easy-to-understand instructional covers Oracle Warehouse Builder from the floor up, and faucets into the author's vast event as a software program and database engineer. Written in a peaceful sort with step by step motives, plenty of screenshots are supplied during the e-book. there are lots of tips and valuable tricks all through that aren't present in the unique documentation.
Additional resources for The New Relational Database Dictionary: Terms, Concepts, and Examples
Example text
1. 1 An Implicit Representation of Quasi-Periodic Granularities As a working example, let us consider the following user-defined granularity. Let us suppose that, in the year 2012, starting from Monday January 9th and ending on Sunday December 23rd, the ‘working shift’ for one employee in company is from 08:00 to 12:00, and from 14:00 to 18:00 each day from Monday to Friday, and from 08:00 to 12:00 on Saturday, let us call such a granularity ‘WS’. In addition, let us suppose that person also works on Saturday evening from 14:00 to 18:00 in two specific days, say on January 14th and 21st , let us call ‘WS+’ the granularity WS with such an addition.
In other words, besides time periods which repeats periodically in time, we also optionally add a set of periods that do not follow such periodic pattern. We propose the following implicit representation of a quasi-periodic granularity G. A quasi-periodic granularity G is represented by a quadruple: G = P, IP , IA , FT where P is an integer representing the duration of the periodic pattern; IP is the set of the convex periods in the first ‘periodic pattern’ of the bottom granularity; IA is the set of the convex periods constituting the aperiodic part; FT is a period constituting the frame time.
With TOUCH we want to combine the best of both, space- as well as dataoriented partitioning, while avoiding the pitfalls. We use data-oriented partitioning to avoid the replication problem of space-oriented partitioning and build an index based on data-oriented partitioning (similar to an R-Tree) on the first dataset A (all elements of A are in the leaf nodes). To avoid the issue of overlap, we do not probe the data-oriented index for every element of the second dataset B. Instead, we assign each element b of B to the lowest (closest to the leafs) internal node of the index that fully contains b.