Adobe Dreamweaver CS3 Unleashed- P22

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Adobe Dreamweaver CS3 Unleashed- P22

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Adobe Dreamweaver CS3 Unleashed- P22: The good news is Dreamweaver provides numerous windows, panels, inspectors, and toolbars for streamlining the way you build websites. The bad news, unfortunately, is that Dreamweaver provides numerous windows, panels, inspectors, and toolbars for streamlining the way you build websites. Why so many windows, panels, and so on, Dreamweaver is unprecedented in the feature set it provides, allowing developers complete control when building websites and applications....

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  1. Summary This chapter has introduced you to some simple, yet important, concepts—mainly data storage. You learned about the skeleton of a database—which is composed of tables, columns, and rows—and about crucial concepts that can aid in performance, maintenance, and efficiency. More importantly, you looked at the various databases supported in this book. You learned about Access, SQL Server 2005 Express Edition, and MySQL as well as the DBMSs that work in conjunction with them. You saw how to obtain and install the necessary software, how to create tables, columns, and rows, and how to attach/restore the Vecta Corp database so that you can work with dynamic Vecta Corp data in your database of choice from Dreamweaver. As the chapter progressed, we also looked at the many tables contained within the Vecta Corp database. You looked at the Employees, Departments, CreditCards, EmployeeStore, and Orders tables as well as the other tables left open so that you can continue to work with the Vecta Corp web application on your own. The next chapter, "A SQL Primer," goes beyond data storage and introduces you to the language used in data access—SQL.
  2. Chapter 23. A SQL Primer IN THIS CHAPTER The Structured Query Language Basic SQL Expressions Operators Functions Joins Subqueries Generating Queries Visually At this point, you are familiar with just how easy it is to create a database using Access, SQL Server 2005 Express, or MySQL. In the coming chapters, you'll learn just how easy Dreamweaver makes it to extract from, insert into, update within, and delete information from your database. Although Dreamweaver provides a simple process for the extraction of data from your database, you may quickly find your application growing far beyond the scope of simple data extraction. The kind of applications you eventually build will have a direct impact on how complex your use of a data-access language will be. Dreamweaver provides a simple and easy-to-use process for commonly used data extraction and filtering tasks, but if you truly want to get the most out of your application, you should become familiar with the topics discussed in this chapter. The Structured Query Language This chapter focuses on the language of today's database. The Structured Query Language, or SQL (pronounced "sequel"), was established in the 1970s as a way of interacting with current database technologies and the tables that made them up. With dozens of clauses, keywords, and operators, SQL quickly became the language standard for simple and complex database operations. The keywords that you construct, also known as statements, range from a simple few to a complex string of subqueries and joins. Although this chapter cannot begin to cover all there is to know on the subject, it can provide you with an introduction to beginning and advanced SQL statements, clauses, joins, subqueries, and action queries. The concepts you learn in this chapter will help you, on a more advanced level, interact with data in your database using Dreamweaver.
  3. Chapter 23. A SQL Primer IN THIS CHAPTER The Structured Query Language Basic SQL Expressions Operators Functions Joins Subqueries Generating Queries Visually At this point, you are familiar with just how easy it is to create a database using Access, SQL Server 2005 Express, or MySQL. In the coming chapters, you'll learn just how easy Dreamweaver makes it to extract from, insert into, update within, and delete information from your database. Although Dreamweaver provides a simple process for the extraction of data from your database, you may quickly find your application growing far beyond the scope of simple data extraction. The kind of applications you eventually build will have a direct impact on how complex your use of a data-access language will be. Dreamweaver provides a simple and easy-to-use process for commonly used data extraction and filtering tasks, but if you truly want to get the most out of your application, you should become familiar with the topics discussed in this chapter. The Structured Query Language This chapter focuses on the language of today's database. The Structured Query Language, or SQL (pronounced "sequel"), was established in the 1970s as a way of interacting with current database technologies and the tables that made them up. With dozens of clauses, keywords, and operators, SQL quickly became the language standard for simple and complex database operations. The keywords that you construct, also known as statements, range from a simple few to a complex string of subqueries and joins. Although this chapter cannot begin to cover all there is to know on the subject, it can provide you with an introduction to beginning and advanced SQL statements, clauses, joins, subqueries, and action queries. The concepts you learn in this chapter will help you, on a more advanced level, interact with data in your database using Dreamweaver.
  4. Basic SQL Just as your savings account would be useless without a valid ID or bank card to get to that money, information contained within a database is useless data unless you have the means of extracting it. SQL is the language that does just that; it allows for quick and complex access to the data contained in your database through the use of queries. Queries pose the questions and return the results to your application, usually in the form of a recordset. Caution Don't think of SQL as simply a way of extracting information. The SQL language can be complex, allowing not only queries from a database, but can add, modify, and delete information from a database as well. Consider trying to extract information from the EmployeeStore table of the Vecta Corp database. Recall that the EmployeeStore table resembles the table that follows (although this table does not show the ItemDescription and Headshot columns): Field Name Date Type ItemID AutoNumber ItemName Text Quantity Currency Cost Number You can then list products in rows that would look like the following: ItemID ItemName Cost Quantity 1 Vecta Corp Shirt $12.99 100 2 Vecta Corp Hooded $29.99 100 3 Vecta Corp Longsleeve $19.99 100 4 Vecta Corp Polo $23.99 100 5 Vecta Corp Sticker $1.99 100 6 Vecta Corp Mousepad $4.99 100 7 Vecta Corp Coffee Mug $6.99 100 8 Vecta Corp Water Bottle $9.99 100 Consider some important aspects about the previous table and the columns and data contained in the eight rows. The EmployeeStore table contains four columns: an ItemID with an AutoNumber that increments a value whenever an item is added, an ItemName that contains a Text data type allowing for a simple title of the product to be added, a column for Cost with a Currency data type that allows us to store price information for each specific item, and a Quantity column with a Number data type that allows us to store a numeric value indicating how many of a specific item we have left in our inventory. The last thing to
  5. consider is the data contained in the table. We are storing a list of Vecta Corp employee store items that are to be sold from the Web Store application. Now what? You have the table created, columns and data types have been outlined, and you have rows of data in the table. Our next step is to get to our data somehow. The next few sections outline how to use SQL to extract data from your tables. The SELECT Statement The foundation to all SQL queries is the SELECT statement. Made up of two keywords, the SELECT statement provides a means for retrieving the data from the database. In its simplest form, the SELECT statement is written using the following elements: SELECT—The SELECT keyword is used to identify the statement or action you are attempting to perform on the database. Other keywords include INSERT, DELETE, and UPDATE. More on these later. * or field names—The asterisk or names of the fields tell the statement which columns you want to extract data from. In this case, the asterisk means "all fields." FROM—The FROM keyword identifies which table to extract the data from. The FROM keyword is required with all SELECT statements. Table name(s)—The table name from which you want to extract the data. The following example extracts all records from your EmployeeStore table: SELECT * FROM EmployeeStore The preceding statement uses two keywords—the SELECT keyword and the FROM keyword—to extract all records from the EmployeeStore table. The previous statement would produce the following results (some fields have been excluded in order to fit on the page): ItemID ItemName Cost Quantity 1 Vecta Corp Shirt $12.99 100 2 Vecta Corp Hooded $29.99 100 3 Vecta Corp Longsleeve $19.99 100 4 Vecta Corp Polo $23.99 100 5 Vecta Corp Sticker $1.99 100 6 Vecta Corp Mousepad $1.99 100 7 Vecta Corp Coffee Mug $1.99 100 8 Vecta Corp Water Bottle $9.99 100 Selecting Certain Fields If you did not want to select all the fields in the database table, you could modify the field names to include only the fields that you wanted. SELECT ItemID, ItemName, Cost
  6. FROM EmployeeStore Notice that the preceding statement retrieves the data only from the ItemID, ItemName, and Cost fields. The preceding query produces the following results: ItemID ItemName Cost 1 Vecta Corp Shirt $12.99 2 Vecta Corp Hooded $29.99 3 Vecta Corp Longsleeve $19.99 4 Vecta Corp Polo $23.99 5 Vecta Corp Sticker $1.99 6 Vecta Corp Mousepad $1.99 7 Vecta Corp Coffee Mug $1.99 8 Vecta Corp Water Bottle $9.99 Notice that in this case, the ItemDescription and Quantity columns are left off. You could also modify the statement in an effort to retrieve the same information in a different order. For example, we could switch the field names by placing ItemName in front of ItemID, like this: SELECT ItemName, ItemID, Cost FROM EmployeeStore This code would give the following result: ItemName ItemID Cost Vecta Corp Shirt 1 $12.99 Vecta Corp Hooded 2 $29.99 Vecta Corp Longsleeve 3 $19.99 Vecta Corp Polo 4 $23.99 Vecta Corp Sticker 5 $1.99 Vecta Corp Mousepad 6 $1.99 Vecta Corp Coffee Mug 7 $1.99 Vecta Corp Water Bottle 8 $9.99 Selecting Unique Data The information in the EmployeeStore table contains duplicate values. As you can see, we have three items in our table that are priced at $1.99. If someone wanted to know about the unique variety of prices in our database, we would have to modify the statement to produce distinct results. The DISTINCT keyword can be used before the Cost field in this case to extract from the table only unique instances of data contained in that field. SELECT DISTINCT Cost FROM EmployeeStore The preceding statement would produce the following result:
  7. Cost $12.99 $29.99 $19.99 $23.99 $1.99 $9.99 As you can see, in this case, all cost information is displayed, but the results are limited to unique price instances. $1.99 is listed only once rather than three times. Clauses Clauses are portions of SQL that allow for further refinement of the query or additional work that must be accomplished by the SQL statement. The following clauses are covered in this section: The WHERE clause The ORDER BY clause The GROUP BY clause The WHERE Clause The WHERE clause is used in conjunction with the SELECT statement to deliver a more refined search based on individual field criteria. This example could be used to extract a specific employee based on a name: SELECT * FROM Employees WHERE Name = 'Ada' Notice that the selection is made only when a certain criteria is true. If a record with the name of Ada did not exist, it wouldn't return anything. But what if we had more than one Ada in the database? You could refine your search even further by using the AND operator: SELECT * FROM Employees WHERE Name = 'Ada' AND Phone = '5555551111' In this case, even if two Adas were listed in our database, we can assume that they don't have the same phone number. In this situation, the query returns one result (assuming, of course, that the two Adas aren't roommates). The ORDER BY Clause The ORDER BY clause provides you with a quick way of sorting the results of your query in either ascending or descending order. Consider the following table of information:
  8. EmployeeID Name Email 1 Cammy cammy@vectacorp.com 2 Ferris ferris@vectacorp.com 3 Ada ada@vectacorp.com 4 Dave dave@vectacorp.com 5 Agnes agnes@vectacorp.com If you selected all the records by using a SELECT all statement (SELECT *), it would return all the results, ordering them based on the value in the EmployeeID field: 1 through 5. Using the SELECT statement with an ORDER BY clause allows you to sort based on a different field name: SELECT * FROM Employees ORDER BY Name The preceding statement would return results in the following order: EmployeeID Name Email 3 Ada ada@vectacorp.com 5 Agnes agnes@vectacorp.com 1 Cammy cammy@vectacorp.com 4 Dave dave@vectacorp.com 2 Ferris ferris@vectacorp.com You can also order by multiple columns by adding a comma after the field name and entering a second field name: SELECT * FROM Employees ORDER BY Name, Phone In this case, all records with identical Name fields are sorted by phone. Tip You might decide to sort the results of your query in either ascending or descending order. When this is the case, you can use the ASC and DESC keywords preceding the field names as follows: SELECT * FROM Employees ORDER BY Name, Phone DESC The GROUP BY Clause
  9. When a query statement includes a GROUP BY clause, the SELECT statement for that query can list functions while operating on groups of data values in other columns. For example, data within the Orders table could look similar to the following table: OrderID EmployeeID ItemID Quantity 1 1 2 2 2 1 4 4 3 3 8 4 4 4 7 2 5 5 2 2 6 5 7 1 If you wanted to retrieve the total number of orders that were received, you could run the following query: SELECT Count(Quantity) AS NumberOfOrders FROM Orders The result would return the following: NumberOfOrders 6 In this case, we're exploring two unique concepts. First, we're selecting a count, using the built in Count function to return a total number of orders for the Quantity column. Second, we're using the AS keyword to create a virtual field called "NumberOfOrders." This gives us a total count of orders and stores that number (6) temporarily within a virtual field called NumberOfOrders. You could use the GROUP BY clause in this instance to group the orders by EmployeeID as follows: SELECT EmployeeID, Count(Quantity) AS NumberOfOrders FROM Orders GROUP BY EmployeeID The result would be as follows: EmployeeID NumberOfOrders 1 2 3 1 4 1 5 2 The result is based on the fact that employees 1 and 5 made two orders each while employees 3 and 4 made one order each. The INSERT Statement Collecting information from your users is not uncommon and, in most cases, it is a necessity. When you
  10. collect information such as registration information, you're not querying data, but rather you're inserting data into the database. In our Vecta Corp example, for instance, we'll create an Admin page that allows administrators to insert new employees into the database. To illustrate this point, consider the Employees table and some of the fields that make it up: Field Name Date Type EmployeeID AutoNumber DepartmentID Number Name Text Username Text Password Text Email Text Phone Text Headshot Text BillingShippingAddress Text BillingShippingCity Text BillingShippingState Text BillingShippingZip Text You could easily insert a new record into the Employees table using the following INSERT statement: INSERT INTO Employees (DepartmentID, Name, Username, Password, Email, Phone, Headshot, BillingShippingAddress, BillingShippingCity, BillingShippingState, BillingShippingZip) VALUES (1, 'Zak', 'zak', 'zak', 'zak@modulemedia.com', '5555555555', 'Images\head_zak.gif', '555 Sample St.', 'San Diego', 'Ca', '92115') The preceding statement inserts all the values you specified into the proper columns within the Employees table. The INSERT keyword generally uses the following elements: INSERT—The INSERT keyword is used to identify the statement or action you are attempting to perform on the database. INTO—The INTO keyword specifies that you are inserting something into a specific table. Table name—The name of the table into which you want to insert the values. VALUES—The actual values to be inserted. You could also use the SELECT statement within the INSERT statement to literally copy information from one table to the other: INSERT INTO Transactions (EmployeeID, Name, Email) SELECT EmployeeID, Name, Email
  11. FROM Employees WHERE EmployeeID = 1 The preceding statement assumes that we have a Transactions table. At any rate, this statement effectively copies from the Employees table the EmployeeID, Name, and Email whose EmployeeID is equal to 1 and copies this data into the Transactions table. The UPDATE Statement The UPDATE statement is used to define changes within your database tables. As you're probably aware, database information is not static, rather, it is constantly changing depending on user feedback or input. As an example, assume that an administrator wanted to change specific data (maybe a username and password) for a particular employee within the Employees table. To make these changes to an existing record in the table, an UPDATE statement would have to be used. The UPDATE statement requires certain keywords, operators, and usually a WHERE clause to modify the specific record, for instance: UPDATE Employees SET Name = "Cammi" WHERE EmployeeID = 3 This statement effectively changes Cammy's name to "'Cammi" because she matches the EmployeeID of 3. Note Operators enable you to connect certain portions of your statement, whereas clauses allow for more refined queries and searches. Both are discussed later in the chapter. You don't have to use the EmployeeID field with the WHERE clause. Instead, you could use Cammy's name as follows: UPDATE Employees SET Name = "Cammi" WHERE Name = "Cammy" In this case, all instances of "Cammy" are replaced with "Cammi" in the database. The DELETE Statement The DELETE statement can be used to remove unneeded records from the database. For instance, if you wanted to remove all employees from the Employees table, we might write a DELETE statement as follows: DELETE FROM Employees The preceding statement effectively removes all the employees from the Employees table. Of course, this doesn't make much sense! You wouldn't want to just go and remove all employees from your database. Instead, you might want to delete a specific employee—for instance, if an employee quits or is fired. If this were the case, you could append a WHERE clause to your statement to remove one record: DELETE
  12. FROM Employees WHERE EmployeeID = 2 This statement removes only the record where the EmployeeID is equal to 2. As was the case with the UPDATE example, you could also delete a user by name: DELETE FROM Employees WHERE Name = 'Agnes' This statement removes all records from the Employees table whose Name field matches "Agnes."
  13. Expressions If you are the least bit familiar with programming languages, you know that expressions are anything that, when calculated, result in a value. For instance, 1 + 1 = 2 is an example of an expression. Expressions in SQL work similarly. Consider the following data that could appear in the Employees table: EmployeeID FirstName LastName 1 Ada Spada 2 Agnes Senga 3 Cammy Franklin 4 Dave Terry 5 Ferris Wheel You could use a simple SELECT statement to display the information exactly as it appears in the preceding table, or you could write an expression that appends the FirstName and LastName fields together. The query would look like this: SELECT EmployeeID, FirstName & LastName AS Name FROM Employees Notice the & operator. The & operator is used to concatenate, or join, two fields into one virtual field using the AS keyword. The results would display as follows: EmployeeID Name 1 AdaSpada 2 AgnesSenga 3 CammyFranklin 4 DaveTerry 5 FerrisWheel Notice that there is no space between the first and last names. To add a space, you need to add a literal string value as follows: SELECT EmployeeID, FirstName & ' ' & LastName AS Name FROM Employees Note You might have noticed that we've been using single quotes in every SQL statement. The reason for this is simple: When you construct your SQL statements in Dreamweaver, the server-side language encloses the entire statement in double quotes. For the statement to be valid, strings within a SQL statement must be enclosed within single quotes.
  14. Adding the space results in a gap between the first and last names as follows: EmployeeID Name 1 Ada Spada 2 Agnes Senga 3 Cammy Franklin 4 Dave Terry 5 Ferris Wheel
  15. Operators In the previous section, you were introduced to the use of the & operator. Operators are used in programming languages to aid in the evaluation of expressions. The following table lists operators with which you should become familiar: Operator Description * The multiplication operator is used when multiplying fields or values. / The divide operator is used when dividing fields or values. – The minus operator is used when subtracting fields or values. > The greater-than operator is used in WHERE clauses to determine whether a first value is greater than the second, such as: SELECT * FROM Employees WHERE EmployeeID > 10 The result returns all the EmployeeIDs after 10. < The less-than operator is used in WHERE clauses to determine whether a first value is less than the second, such as: SELECT * FROM Employees WHERE EmployeeID < 10 The result returns EmployeeIDs 1–9. >= The greater than or equal to operator is used in WHERE clauses to determine whether a first value is greater than or equal to the second, such as: SELECT * FROM Employees WHERE EmployeeID >= 10 The result returns EmployeeIDs of 10 and greater.
  16. Operator Description SELECT * FROM Employees WHERE EmployeeID = 1 AND EmployeeID = 2 OR Typically used with the WHERE clause in the SELECT statement. The OR operator can be used when a certain condition needs to be met or when you can settle for a second, such as: SELECT * FROM Employees WHERE EmployeeID = 1 OR EmployeeID = 2 LIKE The LIKE operator is generally used with WHERE clauses when a wildcard needs to be performed, such as: SELECT * FROM Employees WHERE Name LIKE 'A%' This result returns all employees whose names start with A. Our result returns Ada and Agnes because both their names begin with the letter A. NOT Typically used in conjunction with the LIKE operator, the NOT operator is used when a value is not going to be LIKE the value of a second, such as: SELECT * FROM Employees WHERE Name NOT LIKE 'A%' In this case, all names other than Ada and Agnes are returned. _ The underscore operator is used with WHERE clauses and is performed when you do not know the second value, such as: SELECT * FROM Employees WHERE BillingShippingState LIKE 'A_' The result, in this case, returns all states that begin with the letter A, such as AK, AL, AR, and AZ. % The multiple-character operator is similar to the underscore operator except that it allows for multiple characters, whereas the underscore operator allows for only two. This operator is used in more situations than the underscore operator.
  17. Functions Aside from using operators to manually construct expressions, SQL provides built-in functions (small blocks of code that can perform operations and return a value) you can use. Functions are available simply by making a call to them and passing the value and/or values on which you want the function to operate. Note The functions outlined in the next sections represent a generic list of SQL functions. It's important to realize that not all databases support the same functions. Although some databases support similar functions, the way the function is written can differ syntactically from database to database. In the next sections, I'll provide you with a broad list of these functions. It's up to you however, to consult your database documentation for the appropriate syntax variation for the function. Date and Time Functions Date and Time functions allow for manipulations using dates and times that are stored within your database. For instance, if you wanted to return all items from the Orders table that were purchased on October 30, 2007, you might write the following code: SELECT * FROM Orders WHERE DatePurchased LIKE '10/30/2007' This code would produce the following results: OrderID EmployeeID ItemID Quantity DatePurchased 24 3 2 1 10/30/07 If you wanted to find all the orders from the previous month, you could use the DateAdd() function: SELECT * FROM Orders WHERE DatePurchased > DateAdd(m, -1, Date()) Assuming that the current date was 6/30/05, the results would be as follows: OrderID EmployeeID ItemID Quantity DatePurchased 24 3 2 1 6/15/05 2 2 2 1 6/11/05 11 6 3 1 6/14/05
  18. Tip In the preceding example, we included three values within parenthesis of the DateAdd function. These values are known as parameters. Parameters are values that you pass into the function so that it knows what to do or how to return the value. Also notice that the DateAdd() function accepts parameters. These parameters include the following: This parameter specifies which part of the date/time object you want to work with. Typically, you would want to use one of a few values: m for month, w for week, d for day, h for hour, n for minute, s for second, and so forth. How much time to add or subtract—In the preceding example, I subtracted one month. The date you want to use—In the preceding example, I called another function, the system date, as the date I wanted to use. When you use the Date() function, you are effectively reading the date and time from the computer and passing it in as a value. There are many other Date and Time functions. Too many, in fact, to cover in this small section. Date and Time functions are among the widely used functions in SQL and are worth the research. The Count() Function One of the most obvious functions available is the Count() function. The Count() function is used when you want to perform a count of records. Consider the following data from the Orders table: OrderID EmployeeID ItemID Quantity DatePurchased 24 3 2 1 6/30/05 2 2 2 2 6/30/05 11 6 3 2 6/30/05 You could use the following code to count the number of orders you have taken in a day from the Orders table: SELECT Count(Quantity) AS NumberOfOrders FROM Orders The statement would result in the following: NumberOfOrders 3 Notice that you pass in the field name as a parameter in the Count() function. The parameter is evaluated, and a value is returned into a virtual field named NumberOfOrders. The Sum() Function
  19. Unlike the Count() function that returns a value from a calculation on the number of fields, the Sum() function performs a calculation on data within those fields. If, for instance, you needed to know the total number of items you sold, you could modify the preceding statement to read: SELECT Sum(Quantity) AS Total FROM Orders The statement would produce the following results: Total 5 Rather than simply doing a count on the records, the sum is calculated based on the values within the specified field. Because a total of five items were ordered, this value is shown. The Avg() Function The Avg() function returns the average of values in specific fields. Consider the following orders in the Orders table: OrderID EmployeeID ItemID Quantity DatePurchased 24 3 2 1 6/30/05 2 2 2 3 6/30/05 11 6 3 5 6/30/05 To get the total average of items being ordered, we might write a statement that resembled the following: SELECT Avg(Quantity) AS Average FROM Orders The statement would produce the following result: Average 3 Of course, this is because the average of the numbers 1, 3, and 5 is 3. The Min() and Max() Functions The Min() and Max() functions enable you to find the smallest and largest values of a specific record. To get the minimum quantity ordered, you could write a statement such as this one: SELECT Min(Quantity) AS Minimum FROM Orders Based on the Orders table data from the previous section, the preceding statement produces this result (because the minimum value in the Quantity field is 1):
  20. Minimum 1 To receive the maximum value of a record in the database, try this statement: SELECT MAX(Quantity) AS Maximum FROM Orders Based on the Orders table data from the previous section, the preceding statement produces this result (because the maximum value in the Quantity field is 5): Maximum 5 Arithmetic Functions Aside from using Sum(), Min(), Max(), and Avg(), a few other arithmetic functions can help you when calculating fields in your database. They are as follows: Function Description Abs() Returns the absolute value. Ceil() Returns the largest integer value not greater than the value. Floor() Returns the smallest integer value not greater than the value. Cos() Returns the cosine of the value where the value is provided in radians. Cosh() Returns the hyperbolic cosine of the value where the value is provided in radians. Sin() Returns the sine of the value where the value is provided in radians. Sinh() Returns the hyperbolic sine of the value where the value is provided in radians. Tan() Returns the tangent of the value where the value is provided in radians. Tanh() Returns the hyperbolic tangent of the value where the value is provided in radians. Exp() Returns the mathematical constant e raised to the provided exponential value. Mod() Returns the remainder of a value divided by a second value. Sign() Returns the sign of the argument as –1, 0, or 1, depending on whether the value is negative, zero, or positive. Sqrt() Returns the non-negative square root of a value. Power() Returns the result of a value raised to the power of a second value.
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