Course Topics. Microsoft SQL Server. Dr. Shohreh Ajoudanian. 01 Installing MSSQL Server Data types

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1 Dr. Shohreh Ajoudanian Course Topics Microsoft SQL Server 01 Installing MSSQL Server Creating a database 05 Querying Tables with SELECT 07 Using Set Operators 02 Data types 04 Creating a table, inserting data in table 06 Joining tables 08 Using Functions and Aggregating Data ١

2 01 Installing MS SQL Server ٢

3 Allow installation to proceed by clicking [Yes] button 5 6 ٣

4 Click [New installation or add featured to an existing installation] link to start the installation 7 8 ۴

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6 Accept the License Agreement Click [Next] button ۶

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8 Select the Database Engine Services and Management Tools - Basic options and click [Next] button 15 Select the Default Instance option Click [Next] button 16 ٨

9 Select the [Collation] tab 17 Select the SQL_Latin1_General_CP1_CI_AS option; this defines how your data will be searched and compared. Click [Next] button 18 ٩

10 Select the Windows Authentication Mode option to use your Windows account to connect to database; alternatively you may specify Mixed Mode, and supply User ID and Password and then select the Data Directories tab. Click [Next] button 19 Unless you understand ramifications, it is recommended that accept all defaults for the Discovering SQL purposes Click [Next] button 20 ١٠

11 Click [Next] button 21 The installation could take some time depending on your computer s hardware configuration 22 ١١

12 Click [Close] button 23 This screen shows the MS SQL Server 2008 R2 Express database service running on your Windows machine (the console is accessible from the Administrative Tools menu). 24 ١٢

13 MS SQL Server 2008 Express R2 Limitations 1GB of addressable RAM (computer memory), will only use single CPU only one database can be installed for the instance the size of the database is limited to 10GB 02 Data types ١٣

14 Data types A data type is an attribute that specifies the type of data that an object can hold as well as the number of bytes of information that can be stored in the object If you have similar data types to choose from but they only differ in byte size, use the data type that has a larger range of values and/or has increased precision Exact numeric data types (int, tinyint) are the most common SQL Server data types used to store numeric information. Approximate Numerics include precision (p) which is the total number of decimal digits that could be stored, both to the left and right of the decimal point. Data types Unicode data types provide storage of international characters, such as Japanese and Chinese, to allow worldwide businesses to use big vendor database products to store their data. Unicode data types takes more bytes to store the data in the database If you have similar data types to choose from but they only differ in byte size, use the data type that has a larger range of values and/or has increased precision Exact numeric data types (int, tinyint) are the most common SQL Server data types used to store numeric information. Approximate Numerics include precision (p) which is the total number of ١۴

15 Built-in data type categories SQL Server 2012 s built-in data types are organized into the following categories: Exact numerics (bigint, bit, decimal, int, money, numeric, smallint) Approximate numerics (float, real) Date and time (date, datetime2, datetime, datetimeoffset, time) Character strings (char, varchar, text) Unicode character strings (nchar, ntext, nvarchar) Binary strings (binary, varbinary, image) Other data types (cursor, timestamp, uniqueidentifier, table) Large valued data types (varchar(max), nvarchar(max)) Large object data types (text, ntext, image, xml) Data types Money - used where you ll store money or currency values Int - used to store whole numbers and when performing mathematical computations Float - commonly used in the scientific community and is considered an approximate-number data type Datetime - used to store date and time values in one of many different formats ١۵

16 Data types Char fixed length non-unicode string data type where n defines the string length Varchar variable length non-unicode string data type that indicates the actual storage size of the data Bit (Boolean) integer that can have a null, 0 (False), or 1 (True) value Datetimeoffset a date combined with time of day that has time zone awareness Data types storage size Data Type Use/Description Storage Size Money Monetary or currency values 922,337,203,685, to 922,337,203,685, Int Integer data from 2^31 ( 2,147,483,648) to 2^31 1 (2,147,483,647) Float Approximate number 1.79E+308 to 2.23E 308, 0 and 2.23E 308 to 1.79E+308 Datetime Char Varchar Date Range January 1, 1753, through December 31, 9999 Time Range 00:00:00 through 23:59: Fixed length, non Unicode string data. Can be a value from 1 through 8,000 Variable length non Unicode string. Can be a value from 1 through 8,000 8 bytes 4 bytes Depends on the value of n 8 bytes n bytes Actual length + 2 bytes Bit Integer with a value of 0 or 1. 1 byte for every 8 bit columns Datetimeoffse Date range January1,1 A.D. through December 10 Bytes ١۶

17 Operators Arithmetic Assignment Comparison Logical String Unary Bitwise 03 Creating a database ١٧

18 SQL Database Objects A SQL Server database has lot of objects like Tables Views Stored Procedures Functions Rules Defaults Cursors Triggers System Databases By default SQL server has 4 databases Master : System defined stored procedures, login details, configuration settings etc Model : Template for creating a database Tempdb : Stores temporary tables. This db is created when the server starts and dropped when the server shuts down Msdb : Has tables that have details with respect to alerts, jobs. Deals with SQL Server Agent Service ١٨

19 Creating a database We need to use Master database for creating a database By default the size of a database is 1 MB A database consists of Master Data File (.mdf) Primary Log File (.ldf) Database operations Changing a database Use <dbname> Creating a database Create database <dbname> Dropping a database Drop database <dbname> ١٩

20 Creating a database CREATE DATABASE Sales ON ( NAME = Sales_dat, FILENAME = F:\DATA\saledat.mdf', SIZE = 10, MAXSIZE = 50, FILEGROWTH = 5 ) LOG ON ( NAME = Sales_log, FILENAME = F:\DATA\salelog.ldf', SIZE = 5MB, MAXSIZE = 25MB, FILEGROWTH = 5MB ) ; GO Deleting a database DROP DATABASE Sales, NewSales ; GO ٢٠

21 04 Creating a table, inserting data in table Tables A table is a collection of rows and columns that is used to organize information about a single topic. Each row within a table corresponds to a single record and contains several attributes that describe the row. EmployeeID LastName FirstName Department 100 Smith Bob IT 101 Jones Susan Marketing 102 Adams John Finance ٢١

22 Creating a Table CREATE TABLE table_name ( { <column_definition> }) Insert statements Inserting data to all columns Insert into tablename(col1,col2) values(v1,v2) Insert into tablename values(v1,v2) Inserting data to selected columns Insert into tablename(col1) values (v1) Insert into tablename(col2) values (v2) ٢٢

23 Update statement Update table tablename Set colname=value - This updates all rows with colname set to value Update table tablename Set colname=value Where <<condition>> - This updates selected rows with colname as value only if the row satisfies the condition Delete statements Delete from table1; Deletes all rows in table1 Delete from table1 where <<condition>> Deletes few rows from table1 if they satisfy the condition ٢٣

24 05 Querying Tables with SELECT The SELECT Statement Element Expression Role SELECT <select list> Defines which columns to return FROM <table source> Defines table(s) to query WHERE <search condition> Filters rows using a predicate GROUP BY <group by list> Arranges rows by groups HAVING <search Filters groups using a SELECT condition> OrderDate, predicate COUNT(OrderID) ORDER BY <order by list> Sorts the output FROM Sales.SalesOrder WHERE Status = 'Shipped' GROUP BY OrderDate HAVING COUNT(OrderID) > 1 ORDER BY OrderDate DESC; ٢۴

25 Basic SELECT Query Examples All columns SELECT * FROM Production.Product; Specific columns SELECT Name, ListPrice FROM Production.Product; Expressions and Aliases SELECT Name AS Product, ListPrice * 0.9 AS SalePrice FROM Production.Product; Removing Duplicates SELECT ALL Default behavior includes duplicates SELECT Color FROM Production.Product; SELECT DISTINCT Removes duplicates SELECT DISTINCT Color FROM Production.Product; Color Blue Red Yellow Blue Yellow Black Color Blue Red Yellow Black ٢۵

26 Sorting Results Use ORDER BY to sort results by one or more columns Aliases created in SELECT clause are visible to ORDER BY You can order by columns in the source that are not included in the SELECT clause You can specify ASC or DESC (ASC is the default) SELECT ProductCategory AS Category, ProductName FROM Production.Product ORDER BY Category, Price DESC; Limiting Sorted Results TOP allows you to limit the number or percentage of rows returned by a query Works with ORDER BY clause to limit rows by sort order Added to SELECT clause: SELECT TOP (N) TOP (N) Percent With percent, number of rows rounded up SELECT TOP (N) WITH TIES Retrieve duplicates where applicable (nondeterministic) SELECT TOP 10 ProductName, ListPrice FROM Production.Product ORDER BY ListPrice DESC; ٢۶

27 Paging Through Results OFFSET-FETCH is an extension to the ORDER BY clause: Allows filtering a requested range of rows Dependent on ORDER BY clause Provides a mechanism for paging through results Specify number of rows to skip, number of rows to ORDER BY <order_by_list> retrieve: OFFSET <offset_value> ROW(S) FETCH FIRST NEXT <fetch_value> ROW(S) ONLY Filtering and Using Predicates Specify predicates in the WHERE clause Predicates and Description Operators = < > Compares values for equality / non equality. IN Determines whether a specified value matches any value in a subquery or a list. BETWEEN Specifies an inclusive range to test. LIKE Determines whether a specific character string matches a specified pattern, which can include wildcards. AND Combines two Boolean expressions and returns TRUE only when both are TRUE. OR Combines two Boolean expressions and returns TRUE if either is TRUE. ٢٧

28 06 Joining Tables Module Overview Join Concepts Join Syntax Inner Joins Outer Joins Cross Joins Self Joins ٢٨

29 Join Concepts Combine rows from multiple tables by specifying matching criteria Usually based on primary key foreign key relationships For example, return rows that combine data from the Employee and SalesOrder tables by matching the Employee.EmployeeID primary key to the SalesOrder.EmployeeID foreign key It helps to think of the tables Sales as sets in a Venn diagram Employee SalesOrder orders that were taken by employees Join Syntax Tables joined by commas in FROM Clause Not recommended: Accidental Cartesian products! SELECT... FROM Table1, Table2 WHERE <where_predicate>; ٢٩

30 Inner Joins Return only rows where a match is found in both input tables Match rows based on attributes supplied in predicate SELECT If join emp.firstname, predicate operator is =, also known as ord.amount equi-join FROM HR.Employee AS emp [INNER] JOIN Sales.SalesOrder AS ord ON emp.employeeid = ord.employeeid Employee SalesOrder Set returned by inner join Outer Joins Return all rows from one table and any matching rows from second table One table s rows are preserved Designated with LEFT, RIGHT, FULL keyword All rows from preserved table output to result set SELECT emp.firstname, ord.amount FROM HR.Employee AS emp LEFT [OUTER] JOIN Sales.SalesOrder AS ord ON emp.employeeid = ord.employeeid; Matches from other table retrieved Additional rows added to results for non-matched rows NULLs added in places where attributes do not match Example: Return all employees Employee SalesOrder Set returned by left outer join ٣٠

31 Cross Joins Combine each row from first table with each row from second table All possible combinations output Logical foundation for inner and outer joins Inner join starts with Cartesian product, adds filter Outer join takes Cartesian output, filtered, adds back non-matching rows (with NULL placeholders) Due to Cartesian product output, not typically a desired form of Employe eid Employee FirstNa me 1 Dan 2 Aisha Result FirstNam Name e Dan Widget Dan Gizmo Aisha Widget Aisha Gizmo Product Product Name ID 1 Widget 2 Gizmo SELECT emp.firstname, prd.name FROM HR.Employee AS emp CROSS JOIN Production.Product AS prd; Self Joins Compare rows in same table to each other Create two instances of same table in FROM clause At least one alias required Example: Return all employees and the name of the employee s manager Employee ID Employee FirstNa me Manage rid 1 Dan NULL 2 Aisha 1 3 Rosie 1 4 Naomi 3 SELECT emp.firstname AS Employee, man.firstname AS Manager FROM HR.Employee AS emp LEFT JOIN HR.Employee AS man ON emp.managerid = man.employeeid; Employee Dan Aisha Rosie Naomi Result Manager NULL Dan Dan Aisha ٣١

32 07 Using Set Operators Module Overview What are UNION Queries? What are INTERSECT Queries? What are EXCEPT Queries? ٣٢

33 What are UNION Queries? UNION returns a result set of distinct rows combined from all statements UNION removes duplicates during query processing (affects performance) UNION ALL retains duplicates during query processing -- only distinct rows from both queries are returned SELECT countryregion, city FROM HR.Employees UNION SELECT countryregion, city FROM Sales.Customers; UNION Guidelines Column aliases Must be expressed in first query Number of columns Must be the same Data types Must be compatible for implicit conversion (or converted explicitly) ٣٣

34 What are INTERSECT Queries? INTERSECT returns only distinct rows that appear in both result sets -- only rows that exist in both queries will be returned SELECT countryregion, city FROM HR.Employees INTERSECT SELECT countryregion, city FROM Sales.Customers; What are EXCEPT Queries? EXCEPT returns only distinct rows that appear in the first set but not the second Order in which sets are specified matters -- only rows from Employees will be returned SELECT countryregion, city FROM HR.Employees EXCEPT SELECT countryregion, city FROM Sales.Customers; ٣۴

35 08 Using Functions and Aggregating Data Introduction to Built-In Functions Function Category Scalar Logical Aggregate Window Rowset Description Operate on a single row, return a single value Scalar functions that compare multiple values to determine a single output Take one or more input values, return a single summarizing value Operate on a window (set) of rows Return a virtual table that can be used subsequently in a Transact SQL statement ٣۵

36 Scalar Functions Operate on elements from a single row as inputs, return a single value as output Return a single (scalar) value Can be used like an expression in queries May be deterministic or nondeterministic Scalar Function Categories Configuration Conversion Cursor Date and Time Mathematical Metadata Security String System System Statistical Text and Image Logical Functions Output is determined by comparative logic ISNUMERIC IIF CHOOSE SELECT ISNUMERIC('101.99') AS Is_a_Number; SELECT productid, listprice, IIF(listprice > 50, 'high','low') AS PricePoint FROM Production.Product; SELECT ProductName, Color, Size, CHOOSE (ProductCategoryID, 'Bikes','Components','Clothing','Accessories') AS Category FROM Production.Product; ٣۶

37 Window Functions Functions applied to a window, or set of rows Include ranking, offset, aggregate and distribution SELECT TOP(3) functions ProductID, Name, ListPrice, RANK() OVER(ORDER BY ListPrice DESC) AS RankByPrice FROM Production.Product ORDER BY RankByPrice; ProductID ProductName UnitPrice RankByPrice 8 Gizmo Widget Thingybob Aggregate Functions Functions that operate on sets, or rows of data Summarize input rows Without GROUP BY clause, all rows are arranged as one group SELECT COUNT(*) AS OrderLines, SUM(OrderQty*UnitPrice) AS TotalSales FROM Sales.OrderDetail; OrderLines TotalSales ٣٧

38 Grouping with GROUP BY GROUP BY creates groups for output rows, according to a unique combination of values specified in the GROUP BY clause GROUP BY calculates a summary value for aggregate functions in subsequent phases Detail rows are lost after GROUP BY clause is SELECT CustomerID, COUNT(*) AS Orders processed FROM Sales.SalesOrderHeader GROUP BY CustomerID; Filtering with HAVING HAVING clause provides a search condition that each group must satisfy WHERE clause is processed before GROUP BY, HAVING clause is processed after GROUP BY SELECT CustomerID, COUNT(*) AS Orders FROM Sales.SalesOrderHeader GROUP BY CustomerID HAVING COUNT(*) > 10; ٣٨