SQL Expressions

6 Key excerpts on "SQL Expressions"

• 

  eBook - ePub

  Computer Programming for Beginners

  A Step-By-Step Guide

  • Murali Chemuturi(Author)
  • 2018(Publication Date)
  • Chapman and Hall/CRC

    (Publisher)

  7 Arithmetic, Relational, and Logical Expressions Introduction to Expressions

  As we have noted in Chapter 6 , expressions are used in statements. Almost every statement contains at least one expression. Merriam Webster’s dictionary defines an expression generally as “an act of expressing” and “an act of making your thoughts, feelings etc. known by speech, writing or some other method,” and in the context of computer programming, thus, “a mathematical or logical symbol or a meaningful combination of symbols”. Wikipedia defines an expression thus: “an expression in computer programming is a combination of explicit values, constants, variables, operators and functions, that are interpreted according to the particular rules of precedence and of association for the specific programming language.”

  Let us enumerate the attributes of expressions in the context of computer programming to understand them better: 1.  An expression may consist of at least two variables, a constant, or a combination of variables and constants. 2.  The variables and constants in the expression are combined using mathematical, relational, or logical symbols, generally referred to as “operators.” 3.  The expression is amenable to evaluation using arithmetic, relational, or logical rules.

  4.  The evaluation of an expression in a statement yields only one value that can be used for assignment to a variable or in programmed decision making. That is, expressions can be used in assignment statements and control statements. Expressions are not used in a stand-alone mode.

  5.  Expressions, when used in assignment statements, must be on the right-hand side of the assignment symbol. An expression can never be on the left-hand side of an assignment symbol.

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  eBook - PDF

  SQL: 1999

  Understanding Relational Language Components

  • Jim Melton, Alan R. Simon(Authors)
  • 2001(Publication Date)
  • Morgan Kaufmann

    (Publisher)

  Advanced SQL Query Expressions Introduction To this point, we've discussed the basic SQL statements that you will use to write your applications, and we've talked about the kinds of values and basic relational operators that you can use in those statements. Now, it's time to delve a bit deeper and clarify the more complex query expression facilities of SQL. In this chapter, we dissect SQL's query expression and study each of its com- ponents; then we see how they build on one another. After that, we look more closely at the relational operators to understand their precise syntax and seman- tics. We also tackle the concept of grouped tables that causes so much confusion; during that discussion, we'll have to reexamine the set functions to see how their behavior is affected by grouping operations. Many of the statements we've dis- cussed in the preceding chapters are revisited, this time from a more formal ori- entation. We also introduce the table value concept and show where it can help you write your applications. We also take a very close look at subqueries and discuss their uses and restrictions, a subject we briefly introduced earlier. Initially, we diverge from our music and video examples to concentrate on more abstract examples that may be easier to follow as we explore statement internals. We have included some very advanced material at the end of this chapter, including SQL:1999's CUBE and ROLLUP analytical operations, as well as its new ability to perform recursive queries. 265 266 Chapter 9 Advanced SQL Query Expressions This chapter tells you the inside story about the most important elements of SQL: the query expression and the query specification. The two phrases sound awfully similar, don't they? Well, there's an easy way to remember the difference: use an analogy with value specifications and value expressions (we discussed them in Chapter 5, Values, Basic Functions, and Expressions).

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  eBook - PDF

  Wiley Pathways Introduction to Database Management

  • Mark L. Gillenson, Paulraj Ponniah, Alex Kriegel, Boris M. Trukhnov, Allen G. Taylor, Gavin Powell, Frank Miller(Authors)
  • 2012(Publication Date)
  • Wiley

    (Publisher)

  6.2.3 Retrieving Other Values When using Microsoft SQL Server, you can use SELECT to evaluate expres- sions. These can be, for example, mathematical expressions or expressions 6.2.3 RETRIEVING OTHER VALUES 195 containing SQL functions. The syntax for using SELECT to perform a calcu- lation is: SELECT expression You can’t get much simpler than that. The expression is any mathematical or log- ical expression that returns a result. Here’s an easy example: SELECT 5  7 When you execute the command, the database server returns a result of 12. The expression must resolve to a legal value or an error is returned. For example, the following will return a divide by 0 error: SELECT 5/0 The syntax is similar for resolving a function. In this case, the syntax is: SELECT function [(parameter_list)] The parameter_list is in square brackets because some functions do not include any parameters. Others can accept multiple parameters, depending on what the FOR EXAMPLE The SELECT Statement The SELECT statement is the basic workhorse of most database applications. To understand this, think about how a database might meet the needs of a business, such as an online sales business. A customer logs onto your Web site. When this happens, it’s likely that your application will attempt to retrieve information from the customer’s computer and compare it with information it has on file, using the information to recognize returning cus- tomers. How will it do this? By running a SELECT statement filtered by this identifying information. The customer wants to view information about products you have for sale. This information is often spread across multiple tables, requiring the use of one or more SELECT statements used to retrieve the information and organize the result. The checkout process relies on a series of SELECT statements, retriev- ing shipping options and formulas for calculating shipping costs, the cus- tomer’s preferred shipping address and possibly one or more alternate addresses.

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  eBook - ePub

  Learn SQL Database Programming

  Query and manipulate databases from popular relational database servers using SQL

  • Josephine Bush(Author)
  • 2020(Publication Date)
  • Packt Publishing

    (Publisher)

  Working with Expressions

  In this chapter, you will learn how to use expressions, including using literals, operators, columns, and built-in functions to create expressions. You will learn about the different types of built-in functions, including string, numeric, datetime, and advanced functions, which include casting and converting to other data types. You will learn how to use statistical functions, including how to get and use variance and standard deviation. Finally, you will learn how to create a generated column based on an expression.

  In this chapter, we will cover the following topics:

  • Using expressions
  • Working with dates and times
  • Using statistical functions
  • Using generated columns

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  Technical requirements

  You can refer to the code files of this chapter at the following GitHub link: https://github.com/PacktPublishing/learn-sql-database-programming/tree/master/chapter-9 .

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  Using expressions

  An expression is a combination of values that are interpreted by MySQL to produce another value. Expressions can be used in SELECT statement clauses, the WHERE clause, the ORDER BY clause, the HAVING clause (covered in Chapter 10 , Grouping and Summarizing Data ), or in a SET statement (covered in Chapter 12 , Programmable Objects ).

  Expressions include column values, operators, literal values, built-in functions, NULL values, user-defined functions, and stored procedures. User-defined functions and stored procedures are

  covered in Chapter 12 ,

  Programmable Objects.

  You can combine literals, operators, and built-in functions in countless ways to produce expressions. Your imagination may be the only limit on the ways you can combine these into expressions.

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  Literal values

  A literal value is a constant value such as a string, a number, or a NULL value. The following query shows an example of different literal values in a SELECT statement: SELECT 'string', 1, 1.23, NULL; The previous query has four literals: a string, a number, a floating-point or decimal number, and a NULL. The following screenshot shows the results:

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  eBook - PDF

  Introduction to Database and Knowledge-Base Systems

  • S Krishna(Author)
  • 1992(Publication Date)
  • WSPC

    (Publisher)

  SQL was the product of a major research and development project undertaken by IBM to implement a relational database system. The database management system to emerge out of this effort was known as System R. The commercial products which 4.1 SQL 69 followed are known as DB2 and SQL/DS. With its emergence as a stand-ard, SQL is available on practically all hardware and software platforms. Several DBMS packages (INGRES, dBASEIV etc.) whose principal inter-face is different, also provide an SQL interface. SQL incorporates all aspects of database creation, interaction and management. Our concern here will be mainly with the features for data retrieval or querying. The SQL term for a relation is a table. An attribute is a column (or a field) and a tuple is a row (or a record). A query as expressed in SQL can ask for values for one or more columns in one or more tables which satisfy a set of conditions. A query has basically a very simple syntax of the form SELECT .... FROM .... WHERE... The general form of the query with the optional clauses indicated by [...] is: SELECT [ALL/DISTINCT] columnname(s) FROM table(s) [WHERE predicate(s)][GROUP BY field(s)] [HAVING predicate] [ORDER BY column_name(s)] The following preliminary remarks concern the use of table names and column names in queries. 1. Range variables: A range variable may be associated with each table. Use of range variables is optional and may be dispensed with in most cases. When table names are long, use of range variables rather than full table names could shorten expression of search conditions. Range variables, however, are necessary when a table has to be present in more than one operand position. In Q8 below, for example, we need the join of a table with itself. This is the only example in which range variables are neces-sary, in the examples in this chapter. 2. Qualifying column names: Column names may be qualified with the name of the table (or range variable) to which they belong, together with a .

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  MCSA Guide to Microsoft SQL Server 2012 (Exam 70-462)

  • Faisal Akkawi, Kayed Akkawi, Schofield, , Faisal Akkawi, Kayed AkkawiSchofield(Authors)
  • 2013(Publication Date)
  • Cengage Learning EMEA

    (Publisher)

  SQL is widely supported by the majority of commercial database management systems, but several variants have emerged as DBMS vendors have extended the language to support functionality that was unavailable in the SQL standard. One such variant is Transact-SQL , which has been developed jointly by Microsoft and Sybase; you will use Transact-SQL throughout this book. Unless otherwise noted, references to SQL in this book refer to the Transact-SQL variant of the language. SQL is a declarative language , which means that it uses a set of logical statements to specify what it is trying to accomplish, rather than specifying how to accomplish the results. The SQL Server query optimizer is the component within the database engine that builds a physical execution plan from the logical steps defined in a SQL query. Separating the logical specification of a query from actual implementation yields several benefits. A complex query can be written in a very concise manner because the user can leave the implementation details to the query optimizer. Because the language is written using logical expressions, it can be kept simple and very intuitive, making it easy for nonprogrammers to use. The query optimizer that manages physical implementation is highly efficient and ensures consistency, both in terms of physical implementation and query performance. This chapter breaks down the practical aspects of programming the SQL language into three functionally based sections. In the first section, you’ll learn how to use Transact-SQL as a data manipulation language (DML). Data manipulation language (DML) provides the means to query and manipulate data, and it is the most widely used component of the SQL language. The second and third sections of the chapter introduce the components of the SQL language that enable you to manage and administer the database. These two components are data definition language and data control language.

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