SQL Table

5 Key excerpts on "SQL Table"

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  eBook - PDF

  Python Programming for Biology

  Bioinformatics and Beyond

  • Tim J. Stevens, Wayne Boucher(Authors)
  • 2015(Publication Date)
  • Cambridge University Press

    (Publisher)

  20 Databases Contents A brief introduction to relational databases Tables Schemas Basic SQL Creating a table Running SQL Manipulating records Designing a molecular structure database SQL creation of the database Python interaction with the database Adding a structure to the database Getting a structure from the database Querying the database A brief introduction to relational databases Any collection of data can be considered to be a database, however it is stored or utilised. However, the common use of the word ‘database’ usually refers to a relational database. Relational databases were introduced in the 1970s and model their data in terms of tables with rows and columns. There is an associated language, SQL (Structured Query Language), that can be used to send messages to the database to allow the database to be queried and modified: inserting, changing and deleting data elements. SQL also provides the ability to make connections between the data in different tables. In terms of mathematics, relational databases can be thought of as ‘first-order predicate logic’, and this mathematical underpin- ning of the principles of relational databases is one reason they are conceptually attractive. Tables A table in a relational database has a name and also has some named columns and each row in the table represents one record of data. The type of the data in each column can be specified and the data in any column can be stated to be mandatory, or not. One or more columns in each table define the key . Each record in the table must have a unique key; the key identifies the individual record. Sometimes a table has a ‘natural’ key but sometimes there is no obvious key and so instead a counter (a ‘serial’ or ‘ID’ number) is used, which is set (in many database implementations automatically) to 1 for the first record, 2 for the second, etc. At a simplistic level, spreadsheets (e.g. as used in Excel) can be thought of as tables in a weak substitute for a relational database.

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  Agro-Informatics

  • Vanitha, G M.Kalpana(Authors)
  • 2020(Publication Date)
  • NEW INDIA PUBLISHING AGENCY (NIPA)

    (Publisher)

   a logical schema (data model) describes the semantics, as represented by a particular data manipulation technology. This consists of descriptions of tables and columns.  a physical schema (data model) describes the physical means by which data are stored. This is concerned with partitions, CPUs, tablespaces, and the like. Relational Database Model A relational database is a database that conforms to the relational model, and refers to a database’s data and schema. Common usage of the term “Relational database management system” technically refers to the software used to create a relational database, but sometimes mistakenly refers to a relational database. A relational database is a database that conforms to the relational model, and could also be defined as a set of relations or a database built in an RDBMS. A relational database management system (RDBMS) is a system that manages data using the relational model. Frequently, the term “RDBMS” is inaccurately used as a generic label for the relational database concept. Ironically, most RDBMS software packages are not technically considered “relational” because they do not fully conform to the relational model. Table A table is a set of data elements (values) that is organized using a model of horizontal rows and vertical columns. The columns are 133 Database Management System (DBMS) identified by name, and the rows are identified by the values appearing in a particular column subset which has been identified as a candidate key. Table is another term for relations; although there is the difference in that a table is usually a multi-set (bag) of rows whereas a relation is a set and does not allow duplicates. A table has a specified number of columns but can have any number of rows. View A view is a virtual or logical table composed of the result set of a query.

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  Understanding Databases

  Concepts and Practice

  • Suzanne W. Dietrich(Author)
  • 2021(Publication Date)
  • Wiley

    (Publisher)

  6 SQL: Beyond the Query Language LEARNING OBJECTIVES • To define a relational database schema in SQL satisfying the constraints of the design • To learn how to manipulate data using insert, update, and delete • To understand fundamental data security using privileges Although SQL is short for Structured Query Language, the SQL standard has evolved to include much more than just the query language. There is a data definition language for defining tables and associated constraints on the table and its attributes, including referential integrity. There is also a data manipulation language for inserting, updating, and deleting tuples from tables. In addi- tion, there are language components for defining data access privileges. This chapter highlights these features of a relational database. It is important to note that every database product is an approximation to the SQL standard. When you use a particular database product, it is important to look up the specific syntax it supports. 6.1 Data Definition Chapter 1 introduced the relational data model as a collection of relations. A relation’s schema refers to its description, indicating the attributes in the relation. A visual schema of the database includes the tables with their attributes along with yellow gold keys to indicate primary keys and orange keys to denote foreign keys linked to their associated primary keys, illustrating the referential integrity relationship between the tables. Textually, a summary syntax for a relational schema provides the table name with a list of its attributes enclosed in parentheses, underlining the attributes that form the primary key of the table. The SQL DDL specifies the syntax to create, drop, and alter tables. The SQL standard provides a sublanguage for defining a database, called a data definition lan- guage (DDL). There is a create table statement to define the table attributes with the associated types and constraints, along with any constraints that apply at the table level.

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  Design of Industrial Information Systems

  • Thomas Boucher, Ali Yalcin(Authors)
  • 2010(Publication Date)
  • Academic Press

    (Publisher)

  The unique characteristics, or attributes, of the entities have the attribute names: VENDOR_ID, V_NAME, V_STREET, V_CITY, V_STATE, and V_ZIP. The meaning of these attributes is obvious. No two attributes have the same name. The same interpretation can be given for the tables PURCHASE_ORDER and PO_DETAIL. A table is a relation because it contains a set of attributes about a group of related entities, the entity set. As we build our knowledge of database models, you will see that a database contains many such tables and that these tables are related to one another. For example, the table VENDOR is related to the table PURCHASE_ORDER by the attribute that is common to both tables (i.e., the VENDOR_ID). However, the term relational in relational database does not refer to the rela-tionships among tables, but to the fact that the entities in the entity set of a table are related by a common set of attributes. The attribute columns of the entity sets PURCHASE_ORDER and PO_DETAIL are a tabular representation of the data that appear on the physical document called a purchase order. The reader will note that PURCHASE_ORDER tabulates data in the header and PO_DETAIL is the body of the purchase order. Tables are constructed of rows and columns, and we usually use these terms in referring to a table structure. A row represents a single entity, or instance of the entity set. A row is sometimes referred to as a record , which is a term carried over from a period when computer information was maintained in a file structure. A column represents the attributes of the entity set. Sometimes columns are referred to as fields . The VENDOR table contains four rows (entities or records) and six columns (attributes or fields). Relational database management systems support a variety of data types. Typical data types are numeric , character or text , date , and currency . Numeric data types are classified as integer, floating point, or decimal.

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  Computing Skills for Biologists

  A Toolbox

  • Stefano Allesina, Madlen Wilmes(Authors)
  • 2019(Publication Date)
  • Princeton University Press

    (Publisher)

  C H A P T E R 10 • • • • • • • • • • • • • • Relational Databases 10.1 What Is a Relational Database? A database is a structured collection of data, making the data easy to access, manage, and update. Databases are particularly useful for handling large data sets, and are one of the main items in the toolbox of biologists working with sequence data, spatial data (GIS, 1 combining maps and databases), and “big data” in general. This chapter introduces relational databases, in which data are arranged in tables, and different tables are connected through related columns. Rela-tional databases consist of three components: first, the data, organized in tables; second, a language to query the data (Structured Query Language, SQL); and third, a program to manage the data (relational database manage-ment system, RDBMS). The tables of a relational database can be thought of as a series of spread-sheets that are linked with each other. Each table is composed of rows (called records ) and columns (called fields ). Each field contains a certain type of data (e.g., text, numeric, date). The relationships between the tables are encoded in a schema . To interact with a relational database, you write SQL queries , com-mands that retrieve, update, or modify the data. In most cases, running a query returns a particular representation of a (processed) subset of the data. Relational database management systems store the data and related objects in specific binary formats that can be read by specialized software (as opposed to text files, which can be read by almost any software). 1. Geographic information system. 338 ● Chapter 10 10.2 Why Use a Relational Database? Throughout the book, we have always sided with the use of plain text, given that text files provide a simple, efficient way to store your data, code, and manuscripts. When you have much data, however, using relational databases can greatly improve performance.

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