Introduction to SQL by keralaguest

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									Introduction to SQL



 Vijay Kanabar

 Boston University

 Ron McFadyen

 University of Winnipeg
                                                                                    Table of Contents 2



TABLE OF CONTENTS

      TABLE OF CONTENTS _____________________________________________________________________ 2
Chapter 1 _______________________________________________________________________________________ 1

  SQL Architecture ___________________________________ 1
    Introduction __________________________________________________________________________________ 1
       Client/Server Architecture_____________________________________________________________________ 1
    Databases ___________________________________________________________________________________ 3
       The Relational Model ________________________________________________________________________ 3
    Structured Query Language (SQL) ________________________________________________________________ 4
Chapter Two _____________________________________________________________________________________ 6

  Database Definition _________________________________ 6
    The Library Database __________________________________________________________________________ 6
      Patron ____________________________________________________________________________________ 9
    Creating Tables _______________________________________________________________________________ 9
    Altering a Table______________________________________________________________________________ 10
      Dropping Tables ___________________________________________________________________________ 11
      Copying Tables ____________________________________________________________________________ 11
    Data Types _________________________________________________________________________________ 12
    Predefined Types_____________________________________________________________________________ 13
      Numeric types _____________________________________________________________________________ 13
      String types _______________________________________________________________________________ 13
    SQL Data Types _____________________________________________________________________________ 14
      The null value _____________________________________________________________________________ 15
Chapter Three ___________________________________________________________________________________ 16

  Data Manipulation _________________________________ 16
    Selecting Columns ___________________________________________________________________________ 16
    Selecting Rows ______________________________________________________________________________ 18
    Arithmetic Operations _________________________________________________________________________ 19
    Boolean Operators____________________________________________________________________________ 20
       Special Operators for the WHERE clause ________________________________________________________ 21
       System Variables __________________________________________________________________________ 24
    Column Functions ____________________________________________________________________________ 24
       Use of COUNT ____________________________________________________________________________ 25
       Ordering the Result _________________________________________________________________________ 26
    Grouping Data_______________________________________________________________________________ 28
       Restricting groups using HAVING _____________________________________________________________ 29
       Interaction of clauses in the SELECT ___________________________________________________________ 30
    Joins ______________________________________________________________________________________ 30
       Outer Join_________________________________________________________________________________ 33
    Nested Queries ______________________________________________________________________________ 34
       Correlated Subqueries _______________________________________________________________________ 36
       Exists ___________________________________________________________________________________ 37
       Use of ALL, ANY _________________________________________________________________________ 38
    Set Operations _______________________________________________________________________________ 38
       Union ___________________________________________________________________________________ 38
       Difference ________________________________________________________________________________ 39
                                                                                        Table of Contents 3



Chapter Four ___________________________________________________________________________________ 41

  Updating The Database _____________________________ 41
    Modifying Rows _____________________________________________________________________________ 41
    Deleting Rows_______________________________________________________________________________ 43
    Inserting New Rows __________________________________________________________________________ 44
Chapter Five ____________________________________________________________________________________ 48

  V I E W S_________________________________________ 48
    Creating Views ______________________________________________________________________________ 48
      Dropping views ____________________________________________________________________________ 49
      Advantages of Views _______________________________________________________________________ 49
      Grouped Views ____________________________________________________________________________ 49
    Check Option _______________________________________________________________________________ 50
Chapter Six ______________________________________________________________Error! Bookmark not defined.51

  REFERENTIAL INTEGRITYError! Bookmark not defined.51
    Primary Key Integrity _______________________________________________ Error! Bookmark not defined.51
    Referential Integrity ________________________________________________ Error! Bookmark not defined.52
Chapter Seven ____________________________________________________________Error! Bookmark not defined.59

  DATABASE ADMINISTRATION ____ Error! Bookmark not
  defined.59
    Indexes __________________________________________________________          Error! Bookmark not defined.59
      Creating Single Column Indexes_____________________________________       Error! Bookmark not defined.59
      Creating Concatenated Indexes ______________________________________      Error! Bookmark not defined.60
      Creating Unique Indexes ___________________________________________       Error! Bookmark not defined.60
    Data Control Language: Controlling Access to Data________________________   Error! Bookmark not defined.61
      Grant and Revoke ________________________________________________         Error! Bookmark not defined.62
    System Catalog ___________________________________________________          Error! Bookmark not defined.63
Chapter Eight ____________________________________________________________Error! Bookmark not defined.67

  EMBEDDED SQL _________ Error! Bookmark not defined.67
Part B __________________________________________________________________Error! Bookmark not defined.75

  Oracle ___________________ Error! Bookmark not defined.75
PART C________________________________________________________________Error! Bookmark not defined.104

  SQLSERVER ____________ Error! Bookmark not defined.104
    Using Stored Procedures and Triggers _________________________________    Error! Bookmark not defined.104
    Stored Procedures _________________________________________________       Error! Bookmark not defined.104
    Creating Stored Procedures __________________________________________     Error! Bookmark not defined.105
    Examples________________________________________________________          Error! Bookmark not defined.105
    Returning Information from Stored Procedures___________________________   Error! Bookmark not defined.109
    Return Status Values _______________________________________________      Error! Bookmark not defined.110
    Return Parameters _________________________________________________       Error! Bookmark not defined.111
                                                                                        Table of Contents 4



 Stored Procedures and Performance ___________________________________         Error! Bookmark not defined.113
 Stored Procedure Rules _____________________________________________          Error! Bookmark not defined.113
 Qualifying Names Inside Stored Procedures _____________________________       Error! Bookmark not defined.114
 Renaming Stored Procedures ________________________________________           Error! Bookmark not defined.115
 Displaying Information About Stored Procedures _________________________      Error! Bookmark not defined.115
 Dropping Stored Procedures _________________________________________          Error! Bookmark not defined.116
 Using Triggers to Define Business Processes ____________________________      Error! Bookmark not defined.117
 How Triggers Work _______________________________________________             Error! Bookmark not defined.117
 Nested Triggers ___________________________________________________           Error! Bookmark not defined.118
 Triggers and Performance ___________________________________________          Error! Bookmark not defined.118
 Creating Triggers _________________________________________________           Error! Bookmark not defined.119
 Multirow Considerations ____________________________________________          Error! Bookmark not defined.119
 Conditional Insert Trigger ___________________________________________        Error! Bookmark not defined.121
 Testing Data Modifications Against the Trigger Test Tables ________________   Error! Bookmark not defined.122
 Triggers and ROLLBACK TRANSACTION ___________________________                 Error! Bookmark not defined.123
 Triggers and ROLLBACK TRANSACTION ___________________________                 Error! Bookmark not defined.123
 Implicit and Explicit Null Values _____________________________________       Error! Bookmark not defined.124
 Renaming and Triggers _____________________________________________           Error! Bookmark not defined.125
 Displaying Information About Triggers ________________________________        Error! Bookmark not defined.125
 Dropping a Trigger ________________________________________________           Error! Bookmark not defined.127

Appendix B ______________ Error! Bookmark not defined.129
 SQL Syntax _____________________________________________________ Error! Bookmark not defined.129
                                                                                                  Chapter 1

                SQL Architecture
Client/Server and Web Technology Architecture
 Introduction

              There are two types of architectures used to develop SQL applications. The first category is
              the traditional mainframe application and the second is the client/server architecture.

          1) Mainframe Architecture: With this architecture we essentially use a powerful mainframe to
              host the Data Base Management System (DBMS). Several terminals, largely passive dumb
              terminals communicate with the mainframe and retrieve data from it.

          2) Client/Server Architecture: With client/server architecture, the DBMS system and user
              applications are partitioned into two or more logical segments or tiers. The first tier is the front-
              end or client, which is responsible for the Graphical User Interface (GUI) and some of the
              application business logic. The second tier (last tier) functions as the back-end database
              server. This is typically a powerful computer and hosts the DBMS. A key component of the
              client/server architecture is middleware. Middleware is software “glue” that ties a client and
              server together. The partition of the client and database server represents a functional division
              of work and also included a division of hardware and software components amongst the
              various tiers.

Client/Server Architecture

              The client/server architecture is a computational architecture that separates an application into
              two processes:

          1. One process plays the role of the client, the other plays the role of the server

          2. The client process requests services from server process

                       Middleware glues the two components together.

          The first generation client/server systems were two tiered architectures. Such architectures tend to
          lose their efficiency when scaled up to support large-scale computing environments that service
          hundreds of clients. Scalability is poor because the business logic (application program
          components) resides in the front-end. This creates heavy network traffic between the client and
          database server. Three tiered client/server architectures overcome this limitation.




                                                      1
                                                                                  INTRODUCTION 2




With three tiered architectures an application is typically divided into three logical components. The
client front-end is only responsible for the GUI and does no application programming. The
intermediate layer can also support a variety of services. For example the application server is
typically on the intermediate layer. Such a server typically shares application logic with other
servers or clients.

    Since this book deals with the SQL-environment of typical client/server architectures we
    introduce its key components next. An SQL-environment comprises:

    One SQL-agent.

    One SQL-implementation.

    Zero or more SQL-client modules, containing externally-invoked procedures available to the
    SQL-agent.

    Zero or more authorization identifiers.

    Zero or more catalogs, each of which contains one or more SQL-schemas.

    The sites, principally tables that constitute „„the database‟‟.

SQL Client/Server Terms
The client/server architecture translates into parallel SQL architecture concepts. ISO introduces the
following terms in their standard.

    SQL-Agent: An SQL-agent is that which causes the execution of SQL-statements. In the case
    of the direct invocation of SQL it is implementation-defined. Alternatively, it may consist of one
    or more compilation units that, when executed, invoke externally invoked procedures in an
    SQL-client module.

    SQL-Implementation: An SQL-implementation is a processor that executes SQL-statements,
    as required by the SQL-agent. An SQL-implementation, as perceived by the SQL-agent,
    includes one SQL-client, to which that SQL-agent is bound, and one or more SQL-servers.

    SQL-Client: An SQL-client is a processor, perceived by the SQL-agent as part of the SQL-
    implementation that establishes SQL-connections between itself and SQL-servers and
    maintains a diagnostics area and other state data relating to interactions between itself, the
    SQL-agent, and the SQL-servers.

    SQL-Server: Each SQL-server is a processor, perceived by the SQL-agent as part of the
    SQL-implementation that manages SQL-data. Each SQL-server:
                                                                                            INTRODUCTION 3



             Manages the SQL-session taking place over the SQL-connection between itself and the SQL-
             client.

             Executes SQL-statements received from the SQL-client, receiving and sending data as
             required.

             Maintains the state of the SQL-session, including the authorization identifier and certain
             session defaults.

         Other Key Concepts

             SQL-connection: An association between an SQL-client and an SQL-server.

         o   SQL-environment: The context in which SQL-data exists and SQL-statements are
             executed.
             SQL-session: The context within which a single user, from a single SQL-agent, executes a
             sequence of consecutive SQL-statements over a single SQL-connection.

             SQL-statement: A string of characters that conforms, or purports to conform, to the Format


 Databases

         Most organizations today store their data resource in a database. So then, what is a database? A
         database is a central reservoir for all data. A computerized database system facilitates sharing of
         data (and information). Consider a library users database. Any branch of the same library should
         be capable of checking your book in or out. They should also be in a position to answer questions
         such as “How much do I owe in fines?” or “Is this book available?” In order to respond to such
         questions the library database should be available to all the employees at all the branches.

         Databases are queried and updated frequently - new data inserted, old removed, and existing data
         changed; we use a Data Base Management System (DBMS) to facilitate these tasks. It enables us
         to store, retrieve and manipulate the database.

The Relational Model

         The relational model is almost the exclusive choice for implementation and use on a
         microcomputer. The model is simple, flexible and easy to use. We consider a database to be a
         collection of tables. Each table is a two dimensional construct of rows and columns. The
         mathematical concept comparable to the term table is relation--hence, the name relational
         database.

         Consider the sample table shown below - the first book has a call number 100, title Physics
         Handbook and subject category Physics. The information for each book is stored in rows; rows are
         sometimes referred to as records, and more formally in database terminology, rows are called
         tuples. The columns define fields: Title field, Subject field, etc. A field is also called an attribute.
                                                                                     INTRODUCTION 4



               CALLNO       TITLE                      SUBJECT

               100          Physics Handbook            Physics

               200          Database Systems           Computing

               300          HTML                       Computing

               400          XML                        Computing

               500          Software Testing           Computing

               600          E-Commerce                 Business


         In the relational model each row should have a unique identifier - a primary key, for example,
         callno, is a unique identifier in the table above. When one gives a specific value for the
         primary key, it identifies a single row. Generally speaking, one does not put information into a
         database unless it is possible to recall it later. Each book, and each patron, of the library is
         uniquely identified.

         To define and access information in the database (to retrieve and update the data) we need a
         language for expressing our requests. In this book we discuss the Structured Query
         Language (SQL) for accessing data in a relational database.




Structured Query Language (SQL)


                 Every DBMS has a data sub-language embedded in its architecture. This data sub-
                 language is used to communicate with the database. On the basis of the types of
                 operations performed, the data sub language can be classified into a data definition
                 language DDL), a data manipulation language (DML), and a data control language
                 (DCL).

                 The DDL commands facilitate the creation and description of a database, the DML
                 commands deal with manipulation of the data, and the DCL commands are used to
                 specify security constraints.

                 SQL is based on a data language initially designed for the IBM prototype relational
                 database system called System R. SQL is often pronounced sequel. SQL has been
                 standardized by ISO and will continue to be enhanced; when appropriate we make
                 references to the standard as ISO SQL. It has been adopted as an industry standard
                 for relational database systems and such systems appear on microcomputers,
                 minicomputers, and mainframes. In some cases the same product is available on all
                 these types. The number of SQL database systems is enormous and growing; we
                 cannot list all of them here, but the list includes IBM‟s SQL/DS, and DB2, Relational
                                                                               INTRODUCTION 5



           Technologies‟ INGRES, Oracle Corporation‟s Oracle, Cincom‟s SUPRA, Ashton-
           Tate‟s dBASE IV.


The SQL language is comprised of:

   1.DDL: data definition language. DDL is used to define the tables that make up the database.
   Example: Create Table syntax.

   2.DML: data manipulation language. DML is concerned with the retrieval and update of the
   database. Example: Select * from syntax.

   3.DCL: data control language. DCL is used to specify who can access data in the database
   and what operations they can perform. Example: Grant Table syntax.

   We have introduced the relational model. A relational database consists of tables; tables, of
   course, are a very simple data structure which everyone is capable of understanding. Every
   database system requires a language for accessing data; the language discussed in this text is
   SQL. We discussed the term primary key. Every table should have a primary key if we are to
   access the information in our database. A discussion of primary keys would lead to another
   topic, structural integrity, which is part of the relational model. This is discussed in a later
   chapter. Implementations of primary key integrity and referential integrity are beginning to
   appear in commercial systems, but such aspects of the relational model are not currently part
   of ISO SQL.
                                                                                        Chapter Two


        Database Definition
       The database consists of tables; each table is a two dimensional structure of rows and columns. A
       row is sometimes referred to as a record and a column is sometimes referred to as a field (these
       terms are carried over from data processing). The DDL is used to define (create) tables, views,
       and indexes.

       We create tables in accordance with our data management needs; as our needs grow it may be
       necessary to add new fields to existing tables.

       A view is a virtual table. It is a table defined in terms of other tables; it does not occupy any real
       space in the database. The view mechanism is very powerful and useful, providing us a way to
       simplify a user‟s perception of the database or for providing some types of security.

       Indexes provide the database system with efficient access paths to rows of tables. We create
       indexes in order to improve the efficiency of our requests for data.

       In this chapter we concentrate on the CREATE TABLE command for creating tables, and leave the
       discussion of views and indexes to subsequent chapters.




The Library Database


       To illustrate features of SQL we employ a sample database consisting of three tables used in a
       library environment.

       BOOK

       CALLNO                            TITLE                              SUBJECT
       100                               Physics Handbook                   Physics
       200                               Database Systems                   Computing
       300                               HTML                               Computing
       400                               XML                                Computing
       500                               Software Testing                   Computing
       600                               E-Commerce                         Business




                                                  6
                                                                                 DATA DEFINITION 7




PATRON

USERID                      NAME                   AGE
   10                       Wong                   22
   15                       Colin                  31
   20                       King                   21
   25                       Das                    67
   30                       Niall                  17
   35                       Smith                  72
   40                       Jones                  41



LOAN


LOANID        CALLNO             USERID      DATEDUE       DATERET           FINE        PAID
1             100                10          10-FEB-00     09-FEB-00         0
2             200                10          30-MAY-00     30-MAY-00         0
3             300                20          05-AUG-88                       50          No
4             500                30          26-APR-90                       50          Yes
5             600                40          22-DEC-00                       10          No


Figure 2.1: Relational Tables for a Library



Book

    Information on each book in the library is recorded in the BOOK table:

    BOOK:      callno    title   subject

For each book we have:
           a call number (callno) which uniquely identifies the book

           the title of the book

           the subject matter of the book
                                                                                    DATA DEFINITION 8



Loan

    Each time a book is borrowed information is recorded in the LOAN table:

    LOAN:     loanid     callno   userid    datedue      dateret    fine   paid

For each loan of a book to a person we record:

    the loan id (loanid) key that uniquely identifies the loan row.

    the call number (callno) of the book borrowed

    the identifier (userid) of the person borrowing the book

    the date the book is due (datedue)

            the date the book was returned (dateret); no value is assigned until the book is
             returned

            the fine is calculated for all books returned late, at the rate of 10 cents per day (no
             value is assigned until the book is actually returned)

            the attribute paid; if it‟s value is yes it indicates that the fine has been paid.


                 The LOAN table is illustrated in Figure 2.1. You will note three separate cases:

Example 1: A book has not been returned. Fine accrues and has not been paid.

    LOANID         CALLNO           USERID          DATEDUE           DATERET           FINE      PAID
    3              300              20              05-AUG-88                           50        No



Example 2: Case where the book was returned before the due date. No Fines.

    LOANID         CALLNO          USERID          DATEDUE         DATERET          FINE          PAID
    1              100             10              10-FEB-00       09-FEB-00        0
                                                                                      DATA DEFINITION 9



         Example 3: The book was returned late. A fine was assessed, and paid.

            LOANID        CALLNO          USERID         DATEDUE        DATERET         FINE          PAID
            4             500             30             26-APR-90                      50            Yes




Patron

            We refer to users of the library as patrons; for each patron of the library we record information
            in the PATRON table:

            PATRON:      userid    name     age

            For each patron we have:

            an identification number which uniquely identifies them (userid)

            their name

            their age


                    This database represents a subset of the information requirements of any library. The
                    contents of our library database is illustrated below:




Creating Tables


         To create a table one uses CREATE TABLE command. The general syntax of CREATE TABLE
         is:

            CREATE TABLE table-name
                  (column-specifications) ;

            The table is named (table-name) and each column is defined (column-specification). A
            column-specification is the definition of a column giving its data type and other properties. The
            execution of this command causes the system to save the definition of the table; initially the
            table is empty. We now illustrate the use of the command and then we discuss data types and
            other options. To create the BOOK table we could use:

                    CREATE TABLE BOOK (
                    CALLNO          NUMBER(3) NOT NULL,
                    TITLE     VARCHAR2(20),
                                                                               DATA DEFINITION 10



                   SUBJECT        VARCHAR2(13),
                   CONSTRAINT BOOK_PRIMARY_KEY PRIMARY KEY CALLNO));

          In the above we have defined three columns for the BOOK table as CALLNO, TITLE,
          SUBJECT. Call numbers are defined as numbers, titles and subjects are defined as character
          strings of lengths 20 and 13 respectively. The specification of data type is required and is
          restrictive. Once the book table is defined as above we could not have a book with call
          number QA76.9 since QA76.9 is not a number. For book titles and subjects we must refer to
          specific values by enclosing them in quotes, such as „Introduction to Database Systems‟.

          Suitable definitions for the PATRON table and the LOAN tables would be:

                   CREATE TABLE PATRON (
                    USERID         NUMBER(2) NOT NULL,
                    NAME           VARCHAR2(14),
                    AGE       NUMBER(2),
                    CONSTRAINT   PATRON_PRIMARY_KEY                           PRIMARY           KEY
                   (USERID));


                   CREATE TABLE LOAN (
                    LOANID    NUMBER(3) NOT NULL,
                    CALLNO         NUMBER(3) NOT NULL,
                    USERID    NUMBER(2) NOT NULL,
                    DATEDUE        DATE,
                    DATERET        DATE,
                    FINE      NUMBER(5,2),
                    PAID      VARCHAR2(3),
                    CONSTRAINT   LOANID_PRIMARY_KEY                           PRIMARY           KEY
                   (LOANID));




Altering a Table


       Most SQL systems include a command to allow one to include new columns in an existing table.
       For instance, to add a new column for addresses to the PATRON table one would execute a
       command such as:

       ALTER TABLE tablename

       ADD|DROP column datatype [NULL|NOTNULL];
                                                                                     DATA DEFINITION 11



         Example:
         ALTER TABLE patron
             ADD address CHARACTER(30) ;

             The ALTER TABLE command can typically be used for other purposes such as changing the
             column length or adding a property such as NOT NULL (these may only be allowed in very
             restrictive cases).



Dropping Tables


         To remove or drop a table from the database one uses the DROP TABLE command. To remove
         the BOOK table one executes a command such as:

         DROP TABLE book ;
             This command is very powerful; all rows in the table are deleted and the table object
             disappears.



Copying Tables


         Some SQL systems, such as Oracle, allow the user to create a new table from an old one using
         CREATE TABLE with a subquery. Queries (SELECT statements) are discussed in the next
         chapter. To create a new table SENIORS (age 65 or older) from the PATRON table we could
         execute the command:

                      CREATE TABLE seniors

                      AS

                      SELECT * FROM patron

                      WHERE age >= 65;



             This results in creating a table with the following characteristics:

                      Name                     Null?                Type

                      USERID                  NOT NULL              NUMBER(2)

                      NAME                                          VARCHAR2(14)

                      AGE                                           NUMBER(2)
                                                                                  DATA DEFINITION 12



         The following rows are automatically inserted into the Seniors table:


                   USERID              NAME            AGE

                      25               Das             67

                      35               Smith           72




         The table inherited the columns of the PATRON table since we did not name any. In some
         cases we would need to name the columns. For instance, from the LOAN table we could
         derive a table giving the call number, user id, and the number of days the book was kept:


         CREATE TABLE dayskept (callno, userid, kept) AS

         SELECT (callno, userid, dateret - datedue)

         FROM loan;




Data Types


         Every data value belongs to some data type. ISO SQL has several data types: character,
         numeric, decimal, integer, small integer, float, real, and double precision. A SQL system may
         not provide all these types, and may include others. Most systems provide additional types
         that really are necessary (SQL might be considered deficient on this) such as MONEY, DATE,
         and TIME.

         Some SQL systems simplify the choices; Oracle, for instance, places all the numeric types -
         numeric, integer, small integer, float, real, double precision - into one category: NUMBER. It is
         best, when using a SQL system to refer to its documentation to determine the data types
         available.


         Every data type is either:

                                     Predefined

                                     Constructed

                                     User-defined.
                                                                                               DATA DEFINITION 13



               A user-defined data type is a schema object. A predefined data type is a data type provided by
               the SQL-implementation. A data type is predefined even though the user is required (or
               allowed) to provide certain parameters when specifying it (for example the precision of a
               number).

               A predefined data type is atomic. An atomic type is a data type whose values are not
               composed of values of other data types. The existence of an operation (SUBSTRING,
               EXTRACT) that is capable of selecting part of a string or datetime value does not imply that a
               string or datetime is not atomic.

               A constructed type is either atomic or composite. A composite type is a data type each of
               whose values is composed of zero or more values, each of a declared data type.


 Predefined Types

Numeric types

          There are two classes of numeric type: exact numeric, which includes integer types and types with
          specified precision and scale; and approximate numeric, which is essentially floating point, and for
          which a precision may optionally be specified. Every number has a precision (number of digits),
          and exact numeric types also have a scale (digits after the radix point). Arithmetic operations may
          be performed on operands of different or the same numeric type, and the result is of a numeric
          type that depends only on the numeric type of the operands. If the result cannot be represented
          exactly in the result type, then whether it is rounded or truncated is implementation-defined. An
          exception condition is raised if the result is outside the range of numeric values of the result type, or
          if the arithmetic operation is not defined for the operands.

String types

          A value of character type is a string (sequence) of characters drawn from some character
          repertoire. The characters in a character string S are all drawn from the same character set CS. If
          S is the value of some expression E, then CS is the character set specified for the declared type of
          E.A character string type is either of fixed length, or of variable length up to some implementation-
          defined maximum. A value of character large object (CLOB) type is a string of characters from
          some character repertoire and is always associated with exactly one character set. A character
          large object is of variable length, up to some implementation-defined maximum that is probably
          greater than that of other character strings.

          Either a character string or character large object may be specified as being based on a specific
          character set by specifying CHARACTER SET in the data type; a particular character set chosen
          by the implementation to be the national character set may be specified by specifying NATIONAL
          CHARACTER, NATIONAL CHARACTER VARYING, or NATIONAL CHARACTER LARGE
          OBJECT (or one of several syntactic equivalents) as the data type.

          A value of bit string type is a string of bits (binary digits). A bit string type is either of fixed length, or
          of variable length up to some implementation-defined maximum.
                                                                                   DATA DEFINITION 14




SQL Data Types

      A value of binary string type (known as a binary large object, or BLOB) is a variable length
      sequence of octets, up to an implementation-defined maximum.

      Boolean type

      A value of the Boolean data type is either true or false. The truth value of unknown is sometimes
      represented by the null value.

      Datetime types

      There are three datetime types, each of which specifies values comprising datetime fields. A value
      of data type TIMESTAMP comprises values of the datetime fields YEAR (between 0001 and
      9999), MONTH, DAY, HOUR, MINUTE and SECOND. A value of data type TIME comprises
      values of the datetime fields HOUR, MINUTE and SECOND. A value of data type DATE
      comprises values of the datetime fields YEAR (between 0001 and 9999), MONTH and DAY. A
      value of DATE is a valid Gregorian date. A value of TIME is a valid time of day.

      TIMESTAMP and TIME may be specified with a number of (decimal) digits of fractional seconds
      precision.

      TIMESTAMP and TIME may also be specified as being WITH TIME ZONE, in which case every
      value has associated with it a time zone displacement. In comparing values of a data type WITH

      TIME ZONE, the value of the time zone displacement is disregarded.

      Interval types

      A value of an interval type represents the duration of a period of time. There are two classes of
      intervals. One class, called year-month intervals, has a datetime precision that includes a YEAR
      field or a MONTH field, or both. The other class, called day-time intervals, has an express or
      implied interval precision that can include any set of contiguous fields other than YEAR or MONTH.




      Constructed atomic types

      Reference types

      A reference type is a predefined data type, a value of which references (or points to) some site

      holding a value of the referenced type. The only sites that may be so referenced are the rows of

      typed tables. It follows that every referenced type is a structured type.
                                                                                       DATA DEFINITION 15



The null value

               Every data type includes a special value, called the null value, sometimes denoted by the
               keyword NULL. This value differs from other values in the following respects:

               — Since the null value is in every data type, the data type of the null value implied by the
               keyword NULL cannot be inferred; hence NULL can be used to denote the null value only in
               certain contexts, rather than everywhere that a literal is permitted.

          Other attributes for fields

               ISO SQL specifies two additional properties that can be specified for a column: NOT NULL,
               and UNIQUE. If we specify NOT NULL for a column, then whenever a row is inserted or
               updated that column must have a value assigned to it. Null is a special term which applies
               when a field has never been assigned a value; its value is unknown or missing; null is not the
               same as blank characters or zero value.

               If we specify UNIQUE for a column then every row in the table must have a unique value in
               that column. DB2 does not allow the UNIQUE property to be specified in the table definition;
               but one can achieve this by creating a unique index (see the chapter on indexing). We shall
               not use UNIQUE in our examples.
                                                                                          Chapter Three


                  Data Manipulation
                  The SELECT command is primarily used to retrieve data from the database. It is also used
                  when creating a copy of a table, creating views, and can be used to specify rows for updating.
                  In this chapter we concentrate on its use for retrieving data.

              The basic form of the SELECT is
                  SELECT field-list

                  FROM table-list

                  WHERE field-expression

                  GROUP BY group-fields

                  HAVING group-expression

                  ORDER BY field-list;


                  The result of the SELECT is a listing of data derived from some set of tables in the database.
                  The “field-list” specifies the fields to be listed, such as USERID, NAME, AGE. The data listed
                  is obtained from the set of tables (table-list) specified in the FROM clause. The “field-
                  expression” in the WHERE clause specifies a Boolean expression that rows in the “table-list”
                  must satisfy to be included in the listing. The GROUP BY clause is used when we wish to
                  summarize information in the underlying tables. For example, GROUP BY subject causes the
                  rows to be organized into groups, one group for each unique value of the subject field. The
                  HAVING clause is used to specify which groups are to be included. ORDER BY is used to
                  sequence the rows of the listing. The WHERE, GROUP BY, HAVING, and ORDER BY
                  clauses are optional.




 Selecting Columns


                           We illustrate queries that retrieve all rows of a table.

Example 3.1        List the titles of books in the database.

SQL> SELECT title
 2   FROM book;
                                                                             DATA MANIPULATION 17



TITLE
Physics Handbook
Database Systems
HTML
XML
Software Testing
E-Commerce

6 rows selected.

When an SQL system executes the above example it accesses the BOOK table. Since the SELECT does not
involve a WHERE clause all rows of BOOK are accessed and from each row the system extracts and displays
the title. There are as many rows in the result as there are rows in BOOK; the result are shown above.


Example 3.2        List the title and subject for each book.

SQL> SELECT title, subject
 2 FROM book;

TITLE                 SUBJECT
Physics Handbook      Physics
Database Systems      Computing
HTML                  Computing
XML              Computing
Software Testing      Computing
E-Commerce            Business

6 rows selected.


Example 3.3        List all fields for each book.

                       a) SELECT callno, title, subject

                                FROM book;

                       b) SELECT *

                                FROM book;

                   The * above is an abbreviation for “all fields”.

CALLNO        TITLE                            SUBJECT
  100 Physics Handbook               Physics
                                                                                         DATA MANIPULATION 18



   200 Database Systems               Computing
   300 HTML                           Computing
   400 XML                            Computing
   500 Software Testing               Computing
   600 E-Commerce                     Business

              6 rows selected.



Example 3.4         What are the subject areas of the library?

                   SQL> SELECT subject
                    2   FROM book ;

                   SUBJECT
                   Physics
                   Computing
                   Computing
                   Computing
                   Computing
                   Business

                   6 rows selected.

                   The answer to this query has as many lines as there are books in the library. Since there are
                   very few subject areas the result appears awkward. To remove the redundancies from the
                   display we can use the DISTINCT key word; it causes redundant rows to be eliminated:

                    SQL> SELECT DISTINCT subject
                     2   FROM book ;

                    SUBJECT
                    Business
                    Computing
                    Physics



 Selecting Rows


                             In the previous section we were concerned with listing one or more fields from a table;
                             every row of the table corresponded to a line in the listing. Now we consider retrieval
                             of a subset of the rows of a table. To limit the retrieval to specific rows of a table we
                             include the WHERE clause in our commands. The WHERE clause gives the
                                                                                     DATA MANIPULATION 19



                         condition that a row must satisfy to be included; any row of the table not satisfying the
                         condition is not considered. In the following we discuss operators that may appear in
                         conditions:


                  =, <>, >, >=, <, <=
              IN, BETWEEN, AND, LIKE, IS NULL, AND, OR, NOT



Example 3.5       List the titles of Computing books.

                  SQL> SELECT title
                   2  FROM book
                   3  WHERE subject = 'Computing';

                  TITLE
                  Database Systems
                  HTML
                  XML
                  Software Testing

The condition subject = ‘Computing’ is evaluated for each row of BOOK. If the expression evaluates to
true then the row contributes to the result.


Example 3.6       List the book with call number 200.

                  SQL> SELECT title
                   2 FROM book
                   3 WHERE callno = 200 ;

                  TITLE
                  Database Systems



 Arithmetic Operations


                         The standard operators +, -, *, / are available for addition, subtraction, multiplication
                         and division respectively. These can be applied to the fields being retrieved or to
                         fields within the WHERE clause. The use of parentheses is encouraged to force, or
                         clarify, the order of computation. Expressions in parentheses are evaluated first.
                         Unless parentheses or priorities dictate otherwise, an expression is evaluated from left
                                                                                     DATA MANIPULATION 20



                          to right. * and / have equal priority; likewise + and - have equal priority. However, *
                          and / have higher priority (hence evaluated first) than + and -.


Example 3.7      List patrons fines in Canadian Dollars (assuming one US dollar is equivalent to one and half
Canadian dollars).

SQL> SELECT callno, userid, fine*1.5
 2 FROM loan;

CALLNO USERID FINE*1.5
  100     10           0
  200     10           0
  300     20          75
  500     30          75
  600     40          15

Example 3.8        List loans where the fine is over 50 Canadian dollars.

SQL> SELECT *
 2   FROM loan
 3   WHERE (fine*1.5) > 50.00;

LOANID CALLNO                    USERID DATEDUE DATERET                       FINE     PAID
   3     300                            20    05-AUG-88                                       50        No
   4     500                            30   26-APR-90                                        50        Yes


 Boolean Operators


              The condition specified in the WHERE clause can be a Boolean expression involving AND, OR,
              and NOT. The priority of the Boolean operators from highest to lowest is NOT, AND, OR. Of
              course parentheses can be used to clarify or force evaluation to be performed in a certain order.


Example 3.9        List the call numbers of books borrowed by patron 30 or patron 40 and where the fine paid
is greater than $2.00.

SQL> SELECT DISTINCT callno
 2 FROM loan
 3 WHERE fine > 2.00
 4 AND (userid=30 OR userid=40) ;
                                                                                        DATA MANIPULATION 21



  CALLNO
   500
   600

The results could be different if parenthesis is not used. (This is not evident in our data set.)

Special Operators for the WHERE clause


                          Four operators are available to handle special cases:

                 LIKE is used when searching for the appearance of a particular character string.

                 BETWEEN is used when searching for a value within some range.

                 IS NULL is used to test for a field not having been assigned any value.

                 IN is used to test for a field having a value contained in some set of values.



             LIKE


                 LIKE is used with character data to determine the presence of a substring. Special notations
                 are available to specify unknown or irrelevant characters in the field being tested:

                 a single unknown character: _ (underscore)

                 any number of unknown characters: %


Example 3.10      List books with Database in the title.

        SQL> SELECT *
 2    FROM book
 3    WHERE title LIKE '%Database%';

  CALLNO TITLE                    SUBJECT
   200 Database Systems        Computing

                 In example 3.10 each BOOK title is examined to determine if it contains the character string
                 Database.

Example 3.11      List books with titles having an o as the second character.
                                                                                    DATA MANIPULATION 22



SQL> SELECT *
 2 FROM book
 3 WHERE title LIKE '_o%';

 CALLNO      TITLE                                   SUBJECT
  500 Software Testing           Computing
               In this example the title field of each row in BOOK is examined to determine if it has an o in the
               second character position.

          BETWEEN

               The between operator is used with numeric data to determine if some field lies in a certain
               range.

Example 3.12    List books with call numbers between 200 and 400.
               SQL> SELECT *

                2     FROM book

                3     WHERE callno BETWEEN 200 AND 400 ;



                 CALLNO TITLE                       SUBJECT

               --------- -------------------- -------------

                    200 Database Systems          Computing

                    300 HTML                    Computing

                    400 XML                   Computing

               Note that this is the same as the command:

                     SQL> SELECT *

                      2 FROM book

                      3 WHERE (callno>=200) AND (callno<=400);



          IS NULL


               NULL is a keyword that must be used to determine whether or not a field has been assigned a
               value. Note that in our database the date returned field is not assigned any value until a book
               is returned. If a book is returned on time then no value is assigned to the fine or paid fields.
                                                                                   DATA MANIPULATION 23



Example 3.13   List the books currently out on loan.

SQL> SELECT callno
 2 FROM loan
 3 WHERE dateret IS NULL;

 CALLNO
  300
  500
  600


Example 3.14   List the books that have been returned by patron 100.

SQL> SELECT callno
 2 FROM loan
 3 WHERE (userid=10) AND (dateret IS NOT NULL);

 CALLNO
  100
  200

          IS NOT NULL is the expression used to determine if a field of a row has been assigned a value. It is
          not permitted to use the expressions DATERET = NULL, or DATERET <> NULL.

          IN

          The set of values used for comparison can be either explicitly specified or given as a subquery. We
          illustrate the first case here and leave subqueries for a later section.


Example 3.15   List the names of patrons whose user id is 100, 200, 300, or 350.

SQL> SELECT name
 2 FROM patron
 3 WHERE userid IN (10,20,30);

               NAME
               Niall
               King
               Wong

               The list of values used for comparison is enclosed in parentheses; the name of a patron is
               listed if the userid is in the list.
                                                                                  DATA MANIPULATION 24



Example 3.16    List all Computing and Business titles.

SQL> SELECT title
 2 FROM book
 3 WHERE subject IN ('Computing','Business');


               TITLE
               Database Systems
               HTML
               XML
               Software Testing
               E-Commerce

System Variables

           SQL systems have system variables used to hold values of general use or interest. All systems
           have the variable USER which holds the user id of the current logged on user. Special uses of
           USER can be made if it also corresponds to a column of one or more tables in the database.
           Certainly the system does make use of it to determine if the current user has the access privileges
           pertinent to a request (see the section on DCL).

                       Systems like Oracle and DB2 have many other variables such as: CURRENT DATE,
                       CURRENT TIME, CURRENT TIMESTAMP, CURRENT TIMEZONE. Oracle has a
                       variable SYSDATE which can be used to determine the current time and/or date.


Example 3.17   List patrons who have outstanding books. We shall use Oracle‟s SYSDATE in this
example. Any system that includes date as a data type would likely permit arithmetic operations and
comparisons.

SQL> SELECT userid
 2 FROM loan
 3 WHERE SYSDATE > datedue;

 USERID
   10
   10


 Column Functions


           SQL offers special functions, also called aggregate functions, to determine maximums, minimums,
           averages, totals and counts for entire columns. These are MAX, SUM, AVG, and COUNT
                                                                           DATA MANIPULATION 25



          respectively. Note that AVG and SUM are defined for numeric values only, and that their
          computations exclude NULL values.

Example 3.18   What is the largest fine paid for an overdue book?

SQL> SELECT MAX(fine)
 2 FROM loan;

MAX(FINE)
  50

Example 3.19   How much has the library assessed in fines?

SQL> SELECT SUM(fine)
 2 FROM loan;

SUM(FINE)
  110


Use of COUNT

          ISO SQL specifies that COUNT can be used in just two ways. First, we can use COUNT(*) to
          count the number of rows which satisfy a query. Second, we can use COUNT with DISTINCT to
          count the number of unique values in a column. We illustrate this use of COUNT in the next
          section.

Example 3.20   How many books are in the libraries?

SQL> SELECT COUNT(*)
 2 FROM book ;

COUNT(*)
  6

Example 3.21   How many times has a fine been assessed?

SQL> SELECT COUNT(fine)
 2 FROM loan
 3 WHERE fine > 0;

COUNT(FINE)
   3

Example 3.22   How many computing books are there?
                                                                                  DATA MANIPULATION 26




SQL> SELECT COUNT(*)
 2 FROM book
 3 WHERE subject='Computing';

COUNT(*)
  4


          This use of COUNT, counting rows, does not involve any elimination of null values. That is, if a row
          has all null values it will be counted.


          Use of Distinct

          ISO SQL permits the specification of DISTINCT with an aggregate function; the effect is to remove
          duplicate values prior to the function being applied.


Example 3.23   How many subject areas are there?

SQL> SELECT COUNT(DISTINCT subject)
 2 FROM book;

COUNT(DISTINCTSUBJECT)
----------------------
                3

Example 3.24   How many patrons have borrowed books?

SQL> SELECT COUNT(DISTINCT userid)
 2 FROM loan;

COUNT(DISTINCTUSERID)
---------------------
                4

               Whenever DISTINCT is used, the argument must be a simple field reference as shown above.



Ordering the Result

          The ORDER BY clause is used to force the result to be ordered by one or more column values in
          either ascending or descending order.
                                                                                           DATA MANIPULATION 27




Example 3.25 List books in alphabetical order by title.
SQL> SELECT callno, title, subject
 2 FROM book
 3 ORDER BY title;

  CALLNO       TITLE                 SUBJECT
   200 Database Systems      Computing
   600 E-Commerce Business
   300 HTML           Computing
   100 Physics Handbook      Physics
   500 Software Testing      Computing
   400 XML            Computing

6 rows selected.

             The default is ascending order; this could be specified explicitly by coding ORDER BY title ASC.
             Instead of specifying a field name we can refer to it indirectly by its relative position in the field-list.
             For the above we could have used: ORDER BY 2.


Example 3.26       List books in subject order and within subject order them by call number.

                           SQL> SELECT *
 2    FROM book
 3    ORDER BY subject ASC, callno DESC;

  CALLNO        TITLE                SUBJECT
   600 E-Commerce Business
   500 Software Testing      Computing
   400 XML                   Computing
   300 HTML           Computing
   200 Database Systems      Computing
   100 Physics Handbook      Physics

6 rows selected.

                   Note that the result is ordered first by subject; biology is first, followed by business, then
                   computing and finally mathematics. Within each group the ordering is by call number.
                                                                                     DATA MANIPULATION 28




 Grouping Data

          The GROUP BY clause is used to specify one or more fields that are to be used for organizing
          rows into groups. Rows are grouped together that have the same value(s) for the specified field(s).
          The only simple fields that can be displayed are the ones used for grouping; any result from other
          fields must be specified using a column function. The column function will be applied to a group of
          rows instead of to the entire table.

Example 3.27   For each patron list the number of books he has borrowed.

SQL> SELECT userid, COUNT(*)
 2 FROM loan
 3 GROUP BY userid;

 USERID    COUNT(*)
   10      2
   20      1
   30      1
   40      1

               The effect of this SELECT is to

               1.cause the SQL system to group the rows of loan by user id

               2.display the user id for each group and a count of the number of rows in the group

               A common error is to include a field in the listing that is not unique for the group. For example,

               SQL> SELECT userid, callno, COUNT(*)

                2 FROM loan

                3 GROUP BY userid;

               SELECT userid, callno, COUNT(*)

                        *

               ERROR at line 1:

               ORA-00979: not a GROUP BY expression

               The above would be incorrect because callno is not single valued for a group. When GROUP
               BY is used each element of the select list must be single valued; each element must either be
               specified in the GROUP BY or be the result of a column function.

SQL> SELECT userid, callno, COUNT(*)
                                                                                 DATA MANIPULATION 29



 2 FROM loan
 3 GROUP BY userid, callno;

 USERID CALLNO COUNT(*)
   10     100      1
   10     200   1
   20     300      1
   30     500   1
   40     600   1


Example 3.28   For each patron list his total fines paid.

SQL> SELECT userid, SUM(fine)
 2 FROM loan
 3 GROUP BY userid;

 USERID SUM(FINE)
   10    0
   20   50
   30   50
   40   10

          In the above we see some patrons have not paid a fine but are still listed. To exclude rows from
          the grouping process (and from the SELECT) we specify the appropriate WHERE clause.

Example 3.29   For each patron who has paid a fine, list his total.

SQL> SELECT userid, SUM(fine)
 2 FROM loan
 3 WHERE fine <>0
 4 GROUP BY userid;

 USERID SUM(FINE)
   20   50
   30   50
           40 10

          The only difference between the two preceding examples is that the latter does not report anything
          for patrons who have not paid any fines.

Restricting groups using HAVING

          In the foregoing examples all groups have been reported. To eliminate groups from the result we
          use the HAVING clause specifying an appropriate group oriented boolean expression.
                                                                                    DATA MANIPULATION 30



Example 3.30 List the patron id‟s for those who have paid more than $30 in fines on books with call
numbers greater than 400.

SQL> SELECT userid
 2 FROM loan
 3 WHERE callno > 400
 4 GROUP BY userid
 5 HAVING SUM(fine) > 30;

 USERID
   30

Interaction of clauses in the SELECT

           The previous example has used all components of the SELECT command. It is important to
           understand the order in which the above SELECT is processed.

                       The WHERE is done first

                       GROUP BY second, and

                       HAVING third.

           The rows of LOAN are accessed; each row of LOAN which satisfies the WHERE clause is retained
           for further processing (the grouping). So only those rows of LOAN which correspond to books with
           call numbers larger than 400 are retained. These rows are organized into groups according to the
           specifications in the GROUP BY clause. In our case the rows are grouped by userid. When a
           HAVING clause is present each group must satisfy the condition in order to be displayed in the
           result; in our case each group must have a total for fine that is greater than $30.




 Joins


           A SELECT which performs a join is one which specifies more than one table in the FROM clause.
           That is, it corresponds to a situation where it is necessary to retrieve information from more than
           one table.

           Example 3.31            Suppose we wish to list the names of patrons, their id‟s, and the call numbers
           of the books they have borrowed. There are two tables we use to get the information: PATRON
           and LOAN. What we need to do is specify that a row of PATRON should be matched with a row of
           LOAN whenever they have the same value for the user id field. Note that one row of PATRON can
           be matched with many rows of LOAN since a patron is expected to borrow many books. With SQL
           it is necessary for us to specify this join condition explicitly:
                                                                                DATA MANIPULATION 31



SQL> SELECT patron.name, patron.userid, loan.callno
 2 FROM patron, loan
 3 WHERE patron.userid = loan.userid;

             NAME              USERID             CALLNO
             Wong 10           100
             Wong 10           200
             King 20           300
             Niall   30        500
             Jones 40          600

             Note that we have used prefixes for our field specifications. This is only necessary whenever
             there would be ambiguity regarding the table where the field appears. In this case prefixes are
             only necessary for the user id field.

             If we forgot to include the clause

             WHERE patron.userid = loan.userid

             and had just typed

                 SELECT patron.name, patron.userid, loan.callno

                 FROM patron, loan


             our SELECT would produce a result referred to as a cartesian product. For our sample
             database we would have 7*5=35 rows in the result, since PATRON has 7 rows and LOAN has
             5 rows. Without the WHERE clause each row of PATRON would be joined with every row of
             LOAN.

              NAME USERID              CALLNO
              Wong     10              100
              Colin    15              100
              King     20              100
              Das      25              100
              Niall 30 100
              Smith    35               100
              Jones    40               100
              Wong     10               200
              Colin    15               200
              King     20               200
              Das      25               200
              Niall 30 200
              Smith    35               200
              Jones    40               200
                                                                                     DATA MANIPULATION 32



                 (repeats for callno 300, 400, 500, and 600; not shown above.)

Example 3.32 Suppose we wish to list the names of patrons who have books out on loan. The information
needed to do this is found in two tables: LOAN contains the record of books loaned out (specifically we are
interested in those rows where the DATERET column has no value) and PATRON contains the name for
each patron. We need to match up a selected row of LOAN with the pertinent row of PATRON; this is
done by requiring them to have the same value for the USERID field.

SQL> SELECT name
 2 FROM loan, patron
 3 WHERE loan.dateret IS NULL
 4 AND loan.userid = patron.userid ;

                NAME
                King
                Niall
                Jones


            Aliases

                Sometimes it is necessary and often convenient to use an alias (an alternate name) for a table.
                An alias is specified in the FROM clause immediately following the actual table name. In the
                next example we need the alias - a table is joined with itself - a self-join. It may be useful to
                think of the join being performed between two copies of the same table.

Example 3.33 List each patrons name and the number of other patrons older than him/her. In the
following, one “copy” of the PATRON table is referred to as A; the other as B.
SQL> SELECT a.name, COUNT(*)
 2 FROM patron a, patron b
 3 WHERE a.age < b.age
 4 GROUP BY a.userid, a.name;

NAME           COUNT(*)
Wong             4
Colin           3
King            5
Das             1
Niall           6
Jones           2

                Note the GROUP BY clause in the example; it illustrates an important point regarding the
                elements listed by the query. We have grouped the response using two fields: USERID and
                NAME. In the SELECT clause we have included NAME and COUNT(*). If we grouped only
                by USERID, then NAME would not be considered by SQL to be single-valued for each group.
                                                                                        DATA MANIPULATION 33



                 As far as SQL is concerned, NAME could have a different value in each row of a group.
                 Everything included in the SELECT must be single-valued for a group when GROUP BY is
                 used.

Outer Join

             ISO SQL does not provide for the outer join operation, but it is a useful form of join for many
             situations. Some systems (such as Oracle) provide the outer join and other systems (such as
             DB2) do not. Let us examine the very simple database request

                 For each book in the library list its title and the number of times it has been loaned out.

             One approach that comes quickly to mind is
SQL> SELECT title, COUNT(*)
 2 FROM book b, loan l
 3 WHERE b.callno=l.callno
 4 GROUP BY b.callno, title;

                 TITLE              COUNT(*)
                 Physics Handbook           1
                 Database Systems           1
                 HTML                       1
                 Software Testing           1
                 E-Commerce                 1

             This query does give us correct counts for those books that have been loaned out, but nothing is
             listed for any book that has never been loaned out at all. Such books will not be matched to any
             row of LOAN and therefore do not contribute to the result.

             Let us consider now how Oracle and the outer join can be used to formulate a simple and correct
             query. In the WHERE clause where we specify the join condition (“b.callno=l.callno”) Oracle allows
             us to place a “(+)” to designate a column which is to be matched with an imaginary row of null‟s if
             there are no matches otherwise. Instead of specifying COUNT(*) we specify COUNT(l.userid):

SQL> SELECT title, COUNT(l.userid)
 2 FROM book b, loan l
 3 WHERE b.callno=l.callno(+)
 4 GROUP BY b.callno, title;

                 TITLE          COUNT(L.USERID)
                 Physics Handbook     1
                 Database Systems    1
                 HTML                    1
                 XML                     0
                 Software Testing            1
                 E-Commerce                      1
                                                                                     DATA MANIPULATION 34



                6 rows selected.

                For the above, if a row of BOOK is not matched on call number to a row of LOAN then it will be
                matched to an imaginary row where all column values are null. Hence every row of BOOK is
                matched to something and the title and a count will be produced. Note that Oracle permits
                COUNT(l.userid) to be specified without DISTINCT. Oracle‟s COUNT(...) ignores null‟s and
                produces a value of zero when a book is matched to a row of NULL‟s.


 Nested Queries


            SQL allows us to nest one query inside another, but only in the WHERE clause and the HAVING
            clause. ISO SQL permits a subquery only on the right hand side of an operator. The operators
            available are IN, EXISTS, and the relational operators =, <>, >, >=, <, <=. When a subquery will
            return just a single row (normally a single field value) SQL allows the use of a relational operator.
            When a subquery returns more than one row (a set of rows) a relational operator must be used
            with ALL or ANY.

            Use of IN

                The IN operator is used to determine if some value is present in a list of values. That list can
                be explicitly specified (covered previously) or generated by a subquery.

Example 3.34 List names and ages of patrons who have books out on loan. We shall proceed by giving
two separate queries to accomplish this and then we specify it as one nested query. Consider the query

SQL> SELECT userid
 2 FROM loan
 3 WHERE dateret IS NULL;

                  USERID
                    20
                    30
                    40

We can now specify and execute the query:

SQL> SELECT name, age
 2 FROM patron
 3* WHERE userid IN (20,30,40);

                NAME AGE
                Jones 41
                Niall 17
                King 21
                                                                                DATA MANIPULATION 35




These two queries can easily be combined; we replace the list (100,250,400) with the first
subquery:

SQL> SELECT name, age
 2 FROM patron
 3 WHERE userid IN
 4 (SELECT userid FROM loan
 5 WHERE dateret IS NULL) ;

Example 3.35    List names of patrons who have borrowed a computing or history book.

SQL> SELECT name
 2 FROM patron
 3 WHERE userid IN
 4    (SELECT userid FROM loan
 5    WHERE callno IN
 6             (SELECT callno FROM book
 7             WHERE subject IN
 8     ('Business','Computing')));

                NAME
                Wong
                King
                Niall
                Jones

           Let‟s analyze the above SELECT; it is composed of three queries. The innermost query is a
           simple one and we can consider it separately. That is, we can consider that the database system
           replaces it by a list of call numbers that have been retrieved from the BOOK table. The “middle”
           query retrieves user id‟s where the person has borrowed a book in the computing or history
           categories. The outer query lists the names of these people.

           Simple Comparison Operators: =, <, ...

           We use two examples to illustrate the use of the comparison operators with subqueries. To the
           beginning SQL user, the need for subqueries in these cases is not obvious.


Example 3.36 Who has paid the largest fine? This is such a simple question, but unfortunately it is not
trivial to formulate the correct SQL query. One may be first tempted to express the query as

                SELECT userid, MAX(fine)
                FROM loan;
                                                                                   DATA MANIPULATION 36



However, this is not correct since MAX is a function which operates on the whole table and hence is single-
valued and userid is multi-valued - there are multiple values, one for each row. We cannot mix these two types
of expressions.

To explain the correct formulation of the query, we begin by constructing the query in two parts. First (and
this corresponds to the innermost query we shall use) we find the largest fine:

SQL> SELECT MAX(fine)
 2 FROM loan ;

MAX(FINE)
  50

            This query becomes our nested query and all that we need to do is compare each fine to this
            maximum value:

SQL> SELECT userid
 2 FROM loan
 3 WHERE fine = (SELECT MAX(fine)
 4    FROM loan) ;

  USERID
    20
    30

                The „equals‟ is permitted for testing with respect to the subquery since it is known that the
                subquery returns just one value.

Example 3.37     What is the name of the oldest patron?

SQL> SELECT name
 2 FROM patron
 3 WHERE age =
 4 (SELECT MAX(age)
 5 FROM patron);

NAME
Smith

Correlated Subqueries

            The previous subqueries have been simple in that there was no “interaction” between rows of the
            outer table and rows of the inner table.
                                                                                        DATA MANIPULATION 37



Example 3.38 Suppose we wish to list the names of patrons who have borrowed more than one book. The
PATRON table has the names of patrons and we need to access the relevant rows of LOAN for each patron
to determine how many books have been borrowed.


 1 SELECT name
 2 FROM patron
 3 WHERE 2 <= (SELECT COUNT(*)
 4    FROM loan
 5    WHERE loan.userid = patron.userid)

NAME
--------------
Wong

                     We can think of the subquery being executed once for each row of PATRON. For each row of
                     PATRON the loan table is accessed and a count made of the number of rows retrieved. If
                     that count is greater than or equal to 2 then the patrons name is listed.

Exists

                     Sometimes one is only concerned with whether or not a subquery retrieves any rows. The
                     EXISTS operator evaluates to true or false according to whether a subquery retrieves at least
                     one or no rows respectively.


Example 3.39 Which titles have been borrowed by patrons?
SQL> SELECT title
 2 FROM book
 3 WHERE EXISTS
 4   (SELECT *
 5   FROM loan
 6   WHERE loan.callno = book.callno);

TITLE
Physics Handbook
Database Systems
HTML
Software Testing
E-Commerce

                 In this example a book title is listed only when the subquery retrieves one or more rows. Note that
                 Database Systems is not listed. To list the books which have not been borrowed at all one just
                 replaces the EXISTS above by NOT EXISTS.
                                                                                      DATA MANIPULATION 38



Use of ALL, ANY

These two qualifications can easily lead to difficulties and so we have left them till last. Any of the comparison
operators: =, <, >, <>, <=, >=, can be used with ANY or ALL to test a specific value against a list of
values. The following outlines alternative approaches/operators.

                  original                  alternative
                  = ANY                     IN
                  <> ANY                    NOT IN
                  >= ALL                    = ... MAX(..) ...
                  <= ALL                    = ... MIN(..) ...


Example 3.40 Determine the name of the oldest library patron. This was done previously in example 37.
Using >=ALL we can reformulate the query as

SQL> SELECT name
 2 FROM patron
 3 WHERE age >=ALL
 4  (SELECT age FROM patron);

NAME
Smith

We consider example 37 to be a clearer statement and in general we suggest the use of alternatives to the use of
ALL and ANY.


 Set Operations

             ISO SQL provides the UNION operator to combine the results of two SELECTs. Some SQL
             implementations include DIFFERENCE or MINUS to subtract one result from another, and
             INTERSECTION to determine the rows in common for two results

Union

                 These operators require their operands to be union compatible. This means that the columns
                 of one select must agree in number and type with the other select. The results of two
                 SELECTs can be combined using UNION.

Example 3.41      List the call numbers of books borrowed by user 200, and users with id‟s larger than 300.

SQL> SELECT callno
 2 FROM loan
                                                                                     DATA MANIPULATION 39



 3    WHERE userid = 20
 4     UNION
 5    SELECT callno
 6    FROM loan
 7    WHERE userid > 30 ;

  CALLNO
   300
   600

The result of the above is the union of two sets - the union of the result of the two SELECTs.
SQL permits any number of SELECTs to be combined with UNION. Note that redundant rows
in the result were eliminated; if this is not desired then one specifies UNION ALL.

Difference

Example 3.42 Suppose we wish to determine which computing books have not been borrowed from the
library. One way to approach this is to use two SELECTs. The first of these would retrieve the call numbers
of computing books from the BOOK table. The second query would retrieve the call numbers of books in
rows of the LOAN table. If we „subtract‟ the second from the first, we will be left with those of the first query
which were not present in the second query.

SQL> SELECT callno
 2 FROM book
 3 WHERE subject='Computing'
 4 MINUS
 5 SELECT callno FROM loan;

  CALLNO
   400


             Intersection
Example 3.43 Suppose we wish to determine which computing books have been borrowed. We can
proceed as above using two SELECTs, but now we want to determine what rows (call numbers) the two
queries have in common:

         SQL> SELECT callno FROM book WHERE subject='Computing'
               2 INTERSECT
               3 SELECT callno FROM loan;
                CALLNO
                 200
                 300
                 500
                                                                                     Chapter Four



  Updating The Database
          In this Chapter we introduce Data Manipulation Language statements responsible for updating
          the database.

          There are three commands for updating:

          1. UPDATE modify rows of tables

          2. DELETE remove rows from tables

          3. INSERT add new rows to tables




Modifying Rows

      The general form of the UPDATE command is
          UPDATE table

      SET field-assignments

      WHERE condition
          The field assignments are of the form field = expression and are used to assign specific values
          to the fields of a row. The expressions must be of the appropriate type for the data type of the
          corresponding column. These expressions cannot be subqueries or involve the aggregate
          operators (AVG, COUNT, ...). The WHERE clause is optional; if absent then the UPDATE
          applies to all rows.
                                                                                       DATA UPDATING 42




Example 4.1.      Increase every patron‟s age by 10.

SQL> UPDATE patron
 2 SET age=age+10;

7 rows updated.

SQL> select * from patron;

        userid           name              age
        100              Wong              32
        150              Colin             41
        200              King              31
        250              Das               77
        300              Niall             27
        350              Smith             82
        400              Jones             51


                  Note that every row of PATRON is modified since there is no WHERE clause. Each row of
                  PATRON is modified according to the field assignments. There is only one field assignment:
                  AGE=AGE+10. The effect of this is to cause the current value of age in a row to be
                  incremented by 10; the value of this expression becomes the new value of the AGE field for
                  the row.

                  Example 4.2. Determine fines for books at the rate of one cent a day. In this example we
                  want to modify only the Loan row for userid 30.

aSQL> edit
Wrote file afiedt.buf

 1 UPDATE loan
 2 SET fine = (datedue - SYSDATE) * 0.01
 3 WHERE dateret is NULL
 4* AND userid = 30
SQL> /

1 row updated.

SQL> SELECT *
 2 FROM loan
 3 WHERE userid = 30;

  LOANID         CALLNO       USERID DATEDUE DATERET                     FINE       PAID
                                                                                           DATA UPDATING 43



     4             500                      30 26-APR-90                               327.62           Yes


 Deleting Rows


                   The general form of the DELETE command is

             DELETE
                   FROM table

                   WHERE condition;


                   The effect of DELETE is to remove rows from a table; the rows deleted are those that satisfy
                   the condition specified in the WHERE clause. The WHERE clause is optional; if absent then
                   all rows are deleted.


Example 4.3.       Remove Computing books from the database.

                          DELETE FROM book
                          WHERE subject=‟Computing‟;
4 rows deleted.

SQL> select * from book;

  CALLNO TITLE           SUBJECT
   100 Physics Handbook Physics
   600 E-Commerce      Business

2 rows selected.

Note: If referential integrity is implemented (as illustrated in the next chapter) we will get the following error
message.

SQL> DELETE FROM book
 2 WHERE subject='Computing';
 DELETE FROM book
      *
             ERROR at line 1:
ORA-02292: integrity constraint (SCOTT.BOOK_FOREIGN_KEY) violated - child record found.

Example 4.4.       Remove all loan records for patron “King”.
                                                                                              DATA UPDATING 44



                        DELETE FROM loan
                        WHERE userid = (SELECT userid
                                            FROM patron
                                            WHERE name=‟King‟);



 Inserting New Rows

           In this section we illustrate how new rows are appended to a table. There are two forms of the INSERT
           command
               a) INSERT

                    INTO table (field-list)

                    VALUES (constant, constant, ... );




               b) INSERT

                        INTO table (field-list)

                        subquery;

                        The first form is used to insert a single row in a table; the second form is used to
                        insert multiple rows that come from one or more existing tables. If all fields are
                        included and the values given in order, then the field list can be omitted. Example 4.5
                        illustrates how one adds one row to a database.


Example 4.5.    Add a new patron to the database.

INSERT INTO patron (userid, name, age)
  VALUES (90,'Dattani',20);

           SQL> SELECT * FROM PATRON;

 USERID NAME                   AGE
   10 Wong               22
   15 Colin            31
   20 King             21
   25 Das              67
   30 Niall            17
   35 Smith             72
   40 Jones            41
   90 Dattani           20
                                                                                    DATA UPDATING 45




8 rows selected.

This method is clumsy and some other approach is needed if one is to add several rows to a table. SQL
systems typically provide a forms-based interface, or a load utility, for entering many rows or to load a
database.

The second form for INSERT is illustrated in Example 4.6.

Example 4.6.       Create a table of senior citizens.

                          CREATE TABLE seniors
                               (userid NUMERIC NOT NULL,
                                name CHARACTER(30) NOT NULL);

                          INSERT INTO seniors
                                SELECT userid, name
                                FROM patron
                                WHERE age >= 65 ;
                                                                                            DATA UPDATING 48



                                                                                     Chapter Five



                             Views
                All of our discussions to this point have dealt with tables. Views are similar to tables;
                in many cases they can be used interchangeably. A view is defined using the
                CREATE VIEW command and is defined in terms of tables or other views. A view
                exists in definition only; it does not occupy space in the database as a table does; it is
                materialized by the database system whenever it is used or referenced. There are
                two reasons for using views: convenience and security.


 Creating Views


                         The CREATE VIEW command is used to create a view; it has the general
                         syntax:

                    CREATE VIEW view-name (column-specification-list)

                    AS select-specification

                    WITH CHECK OPTION;



                The column-specification-list is the list of columns that appear in the view. This can
                be omitted when each column in the view is derived directly and unambiguously from
                a column of an underlying table. The select-specification is the SELECT statement
                which defines the view. The WITH CHECK OPTION is optional and is concerned with
                security aspects of the view.

                As an example, suppose we wanted to supply our patrons with a view of the LOAN
                table consisting of the call number and date due columns for those books that are
                currently out on loan. Consider the definition BOOKSONLOAN:


                        CREATE VIEW BOOKSONLOAN AS
                        SELECT LOAN.LOANID, BOOK.CALLNO, BOOK.TITLE
                        FROM BOOK, LOAN
                        WHERE BOOK.CALLNO = LOAN.CALLNO
                        AND LOAN.DATERET IS NULL;

One can query the data using the SELECT syntax discussed in Chapter 3.

                         SELECT * FROM BOOKSONLOAN ;
                                                                                   DATA UPDATING 49




Dropping views


         ISO SQL does not include a command to drop (remove) a view, but SQL systems
         generally include a DROP statement for this purpose. So, to remove the view
         OUT_BOOKS from the system one would execute:

         DROP VIEW BOOKSONLOAN;




Advantages of Views

         The view mechanism of SQL is a very useful tool for providing a form of security in the
         database system. A view represents a subset of some underlying tables. The users
         perception is simplified and what may be sensitive data is excluded from a user‟s view.
         For example, it may be undesirable for people to know who has the book they want. If
         somehow we can force users to use BOOKSONLOAN instead of LOAN then we have
         excluded (hidden) the sensitive field userid in LOAN from them.



Grouped Views

             A grouped view is one where the GROUP BY clause has been used in the definition.
             Such views are very useful, but unfortunately they are subject to numerous
             restrictions in ISO SQL. Consider the view:

                    SQL> CREATE VIEW loans_by_book (callno, book_count)
                     2 AS
                     3 SELECT callno, COUNT(*)
                     4 FROM loan
                     5 GROUP BY callno;

                    View created.

             ISO SQL does not allow one to use a WHERE clause, a GROUP BY clause, or a
             HAVING clause with respect to a grouped view referenced in a SELECT. For
             example,

             SELECT * FROM loans_by_book WHERE book_count > 2 ;

             is not acceptable since the SELECT references a grouped view and contains a
             WHERE clause on that view. As well, if one of the tables/views in the FROM clause
             of a SELECT references a grouped view then no other tables/views can be
             referenced. For example,

             SELECT loans_by_book.callno, title

                 FROM loans_by_book, book
                                                                                DATA UPDATING 50



               WHERE loans_by_book.callno = book.callno;


         is illegal since there are two tables/views in the FROM clause and one of these is a
         grouped view. If a SELECT references a grouped view in it‟s FROM clause, then an
         associated WHERE, GROUP BY, or HAVING is not permitted. Some SQL
         implementations are more liberal in their treatment of grouped views.


Check Option

         The WITH CHECK OPTION phrase is optional, but certainly recommended if the view
         could be used for updating the database. Regardless of whether or not the WITH
         CHECK OPTION is specified the user of a view is restricted to retrieving only that
         portion of the database specified in the view. However, that is not the case for the
         update operations of INSERT and UPDATE. Consider the view

                  SQL> CREATE VIEW computing_books
                   2 AS
                   3 SELECT * FROM book
                   4 WHERE subject='Computing';

                  View created.

         A SELECT command referencing this view can only access computing books, but it
         is possible in the absence of WITH CHECK OPTION to insert non-computing books or
         change a

                  SQL> INSERT INTO computing_books
                   2 VALUES
                   3 (111,'Twentieth Century','History');



                  1 row created.

         and insert the history text into the database. This book, however vanishes from the
         view; we cannot retrieve it using COMPUTING_BOOKS.

                  SQL> select * from computing_books;

                    CALLNO TITLE                      SUBJECT
                  --------- -------------------- -------------
                      200 Database Systems Computing
                      300 HTML                    Computing
                      400 XML                   Computing
                      500 Software Testing Computing

         A similar situation exists for the UPDATE command. To avoid this kind of behavior
         we just include the WITH CHECK OPTION when we define the view.

                  SQL> CREATE VIEW computing_books
                   2 AS
                                                                                DATA UPDATING 51



             3 SELECT * FROM book
             4 WHERE subject='Computing'
             5 WITH CHECK OPTION;

            View created.

    This option tells the system to check and reject updates (INSERTs and UPDATEs) for
    rows that vanish from the view.

            SQL> INSERT INTO computing_books
             2 VALUES
             3 (111,'Twentieth Century','History');
            INSERT INTO computing_books
                  *
            ERROR at line 1:
            ORA-01402: view WITH CHECK OPTION where-clause violation



Updating through Views

Some views are inherently non updatable. That is, for some views an update operation
does not make any sense and must be disallowed. For example, consider the update
operation

            SQL> UPDATE loans_by_book
             2 SET book_count = 25
             3 WHERE callno=100;
            UPDATE loans_by_book
               *
            ERROR at line 1:
            ORA-01732: data manipulation operation not legal on this view

Updating the BOOK_COUNT field does not make any sense; it doesn‟t even correspond
to a field in an underlying real table. What views can be updated sensibly, and which
cannot, is an area of current research in database systems. Consequently, SQL systems
are quite restrictive on what types of views can be updated. In general, a view is
updateable if it corresponds to a simple row and column subset of a single table. The
specific conditions that an updateable view must meet are:

           The FROM clause specifies exactly one table.


           The columns are derived directly from underlying columns: no arithmetic
            expressions, no aggregate functions, no DISTINCT specification.


           The WHERE clause does not have a subquery, a GROUP BY clause, or a
            HAVING clause.


           In the future these restrictions will in all likelihood be relaxed; at the present
            time some database systems have eased these restrictions. For instance,
                                                           DATA UPDATING 52



DB2 allows a view to be updated even if the WHERE clause contains a
subquery as long as the FROM clause in the subquery and the “outer” FROM
clause reference different tables.

								
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