Lecture 2: Chapter Objectives. Relational Data Structure. Relational Data Model. Introduction to Relational Model & Structured Query Language (SQL)

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1 Lecture 2: Database Resources Management Fall Chapter Objectives Basics of Relational Model SQL Basics of SELECT statement Introduction to Relational Model & Structured Query Language (SQL) MIS511-FALL Relational Data Model First introduced by E.F Codd. Based on mathematical set theory. Relational data model has 3 main components: Relational Data Structure Where to store data? data organization Relational Data Integrity How to maintain integrity? facilities (constraints) are included to specifybusiness rules to maintain integrity of data as they are being manipulated Data Manipulation How to manipulate data? operations (using SQLlanguage) used to manipulate stored data 3 Relational Data Structure Main data structure used is a relation. Relation is a two-dimensional grid (table)that holds data about the entity(thing we focus on). SKU_DATA SKU_DATA (SKU, SKU_Description, Department, Buyer) Relational Database is a collection of relations with distinct relation names. 4 1

2 Relational Model Terminology Alternative Terminology Relation is a tablewithcolumnsandrows. Attributeis a named columnof a relation. Domain is the set of allowable values for one or more attributes. Tupleisarowofarelation. Degreeisthenumberofattributesinarelation. Metadata Cardinalityisthenumberoftuplesinarelation. Userdata 5 6 Properties of Relation Relation name is distinct from all other relation names in the database. Each attribute has a distinct name. Values of an attribute are all from the same domain Each cell of relation contains exactly one atomic (single) value. Each tuple is distinct; there are no duplicate tuples. Order of attributes has no significance. Order of tuples has no significance, theoretically. 7 Schema is a textual representation of the database relations defined by its namefollowed by a set of attributeand domain name pairs in paranthesis. A domain is the set of values that can be assigned to an attribute SKU_DATA (SKU: numeric, SKU_Description: String, Department:String, Buyer:String) Relational database schema set of relation schemas, each with a distinct name SKU_DATA (SKU, SKU_Description, Department, Buyer ORDER_ITEM (OrderNumber, SKU, Quantity, Price, ExtendedPrice) RETAIL_ORDER (OrderNumber, StoreNumber, StoreZip, OrderMonth, OrderYear, OrderTotal) 8 2

3 Data Integrity Three types of data integrity constraints Domain Constraints Entity Constraints Referential Constraints Domain Constraints The domain constraint states that the values of an attribute must be from the same domain. A domain is the set of values that can beassigned to an attribute. Description values are limited to String of length 20 Department values are limited to Water Sports, Cycling, Climbing, Camping... STU_NAME values are limited to String STU_DOB values are limited to Date STU_GPA values are limited to Numeric the range 0 4, inclusive, the domain is [0,4], 9 10 Relational Keys A key consists of one or more attributes that determine other attributes We need to specify one or more attributes (relational keys) that uniquely identify each tuple in a relation. Primary Key: It is a set of one or more attributes that has been selected to identify unique tuples Minimum set Composite Key : A key that has more than one attribute Relational Keys Foreign Key An attribute or a set of attributes for a relation thatserves as a link to theprimary key of some other (sometimes the same) relation whose values match the primary keyvalues in the other relation

4 Entity/Referencial Integrity Constraints Entity Integrity ensurethat every relationof a relational data model has a primary key the data values for the attributes ofthe primary key cannot be NULL. A null is no value at all. It does not mean a zero or a space. Referential Integrity ensurethat the foreign keys values of arelation must match the primary key value ofsome relation; otherwise,the value of a foreign key must be NULL. Many DBMSs enforce integrity constraints automatically. Entity/Referencial Integrity PRODUCT VENDOR EMPLOYEE 13 MIS511-Fall Data Manipulation A way to access and manipulate thedata in the relations. Example of a manipulation language : Structured Query Language (SQL) UPDATE SKU_DATA SET Department = Sport WHERE SKU= ; Data Manipulation : SQL Main language for relational DBMSs. data sublanguage creating and processing database data and metadata not a full featured programming language non-procedural specify whatinformation you require,ratherthan how to get it can be used by range of users relatively easy to learn essentially free-format, vocabulary less than 100 words consists of standard English words: SELECT, INSERT, UPDATE... An ISO standard now exists for SQL, the formal and defacto standard languagefor relational db. several different dialects (Oracle, Microsoft SQL Server, MySQL, IBM s DB2, Microsoft Access)

5 History In 1974, D. Chamberlin (IBM San Jose Laboratory) defined language called Structured English Query Language (SEQUEL). A revised version, SEQUEL/2, was defined in 1976 but name was subsequently changed to SQL for legal reasons In late 70s, ORACLE appeared and was probably first commercial RDBMS based on SQL. In 1987, ANSI and ISO published an initial standard for SQL. In 1989, ISO published an addendum that defined an Integrity Enhancement Feature. In 1992, first major revision to ISO standard occurred, referred to as SQL2 or SQL/92. In 1999, SQL:1999 was released with support for object-oriented data management. In late 2003, SQL:2003 was released. Most recent version is SQL:2008 SQL : DDL DCL and DML SQL statements can be divided into three categories: Data definition language (DDL) statements Used for creating tables, relationships, and other structures. Data Control Language (DCL) statements Statements to specify transaction control, semantic integrity (triggers and assertions), authorization and management of privileges Statements for specifying the physical storage parameters such as file structures and access paths (indexes) Both Covered later. Data manipulation language (DML) statements. Used for queries and data modification Covered NOW Cape Codd Outdoor Sports Cape Retail CoddSales Outdoor Tables Sports Cape CoddOutdoor Sports is a fictitious company based on an actual outdoor retail equipment vendor. Three tables are used: RETAIL_ORDER, ORDER_ITEM, & SKU_DATA, (SKU = Stock Keeping Unit) PPH

6 MS Access and its SQL The SQL SELECT Statement Used to list contents of table Syntax: SELECT columnlist FROM relationlist columnlistrepresents one or more attributes, separated by commas Asterisk can be used as wildcard character to list all attributes All SQL statements end with a semi-colon(;) MIS511-Fall PPH 22 Specific Columns on one Relation List the departments and buyers Specifying Column Order List the buyers and departments

7 The DISTINCT Keyword List the buyers and departments (elimiate duplicates) Selecting All Columns: Asterisk (*) Keyword List all stock s data (SKU, SKU_Desc., Dept., buyer) Sorting the Results: ORDER BY Multi-level Sorting : ORDER BY List orders sorted by order number SELECT columnlist FROM relationlist [ORDER BY columnlist [ASC DESC] ] List orders sorted by order number & (then) price NOTE: the actual relation contents are unaffected by the ORDER BY

8 Sort Order: Ascending& Descending List orders sorted by price descending & order number Specific Rowsfrom OneTable: WHERE List stock data in Water Sports Dept. SELECT columnlist FROM relationlist [WHERE conditionlist] [ORDER BY columnlist[asc DESC] ] NOTE: The default sort order is ASC does not have to be specified 29 NOTE: SQL wants a plain ASCII single quote: ' NOT! most SQL implementations yield case-sensitive match 30 Specific Columns and Rows from one Table Criteria / Condition List only the desc. and buyers in the Climbing Dept. Expression using one of the operators, a column name on one side and a value on theother Department = 'Water Sports' column names on both sides: Price <= ExtendedPrice Relational operators : =, <>, >, >=, <, <= Logical operators : AND, OR, NOT chain expressions together with logical operators. AND : row must meet all of the conditions OR : a rowneeds to meet only one of the conditions NOT : inverts the result of expression

9 WHERE Clause Options: AND List stock data in WS depart. for Nancy WHERE Clause Options: OR List stock data in either Camping or Climbing depts PPH(student_version) 34 WHERE Clause Options: IN WHERE Clause Options: NOT IN List stock data for Nancy, Cindy and Jerry List stock data for someone other than NM, CL, JM Used to check whether an attribute value matches any value within a value list

10 WHERE Clause Options: Range with BETWEEN WHERE Clause Options: Range with Math Symbols List order data for ExtendedPrice btw 100 and 200 Used to check whether an attribute value is within a range WHERE Clause Options:IS NULL WHERE Clause Options: LIKE and Wildcards List items with no Department info Used to check whether an attribute value is null Used to check whether an attribute value matches a given string pattern in conjunction with wildcards to find patterns within string attributes SQL 92 Standard (SQL Server, Oracle, etc.): _ = Exactly one character % = Any set of one or more characters MS Access (based on MS DOS)? = Exactly one character * = Any set of one or more characters

11 WHERE Clause Options:LIKE and Wildcards (Cont d) WHERE Clause Options:LIKE and Wildcards (Cont d) List stock data for any buyer starting with Pete List stock data that contains Tent in its description WHERE Clause Options:LIKE and Wildcards (Cont d) List stock data that contains 2 in 3rd position SQL Built-in Functions There are five SQL Built-in Functions: COUNT returns number of values in specified column. SUM returns sum of values in specified column. AVG returns average of values in specified column. MIN returns smallest value in specified column. MAX returns largest value in specified column. Eachoperatesonasinglecolumnofatableandreturnsasinglevalue. COUNT, MIN, and MAX apply to numeric and non-numeric fields, but SUM and AVG maybeusedonnumericfieldsonly. Apart from COUNT(*), each function eliminates nulls first and operates only on remaining non-null values

12 SQL Built-in Functions(Cont d) Find the sum of total orders for order 3000 SQL Built-in Functions(Cont d) SELECT OrderNumber,SUM(ExtendedPrice) FROM ORDER_ITEM An alias is an alternative name given to acolumnor relationin any SQL SELECT OrderNumber FROM ORDER_ITEM WHERE Price > AVG(Price); SQL Built-in Functions (Cont d) SQL Built-in Functions (Cont d) SELECT SUM (ExtendedPrice) AS OrderItemSum, AVG (ExtendedPrice) AS OrderItemAvg, MIN (ExtendedPrice) AS OrderItemMin, MAX (ExtendedPrice) AS OrderItemMax FROM ORDER_ITEM; Find the number of orders

13 SQL Built-in Functions (Cont d) String Functions in SELECT Find the number of departments (distinct) List the Buyer and departments into a single colum named Sponsor String Functions in SELECT (Cont d) Arithmetic Operations in SELECT List the Buyers and Departments into a single column named Sponsor Compute and compare the Extended Price

14 Arithmetic in SELECT Compute and compare sum of the Extended Price 53 14