From e1900b2b0c0a0b3ab2cf269f04712fa92157e1be Mon Sep 17 00:00:00 2001 From: "Thomas G. Lockhart" Date: Tue, 4 May 1999 02:18:34 +0000 Subject: [PATCH] First version of markup which can run through jade for html. Probably not acceptable yet. Need to check some math symbols and markup. --- doc/src/sgml/sql.sgml | 2270 +++++++++++++++++++++++++++-------------- 1 file changed, 1479 insertions(+), 791 deletions(-) diff --git a/doc/src/sgml/sql.sgml b/doc/src/sgml/sql.sgml index ed56c4515e..9d146409bf 100644 --- a/doc/src/sgml/sql.sgml +++ b/doc/src/sgml/sql.sgml @@ -3,120 +3,133 @@ - This chapter originally appeared as a part of - Stefan Simkovics' Master's Thesis. - - - + This chapter originally appeared as a part of + Stefan Simkovics' Master's Thesis + (). + - SQL has become one of the most popular relational query languages all - over the world. - The name "SQL" is an abbreviation for + SQL has become the most popular relational query language. + The name SQL is an abbreviation for Structured Query Language. In 1974 Donald Chamberlin and others defined the language SEQUEL (Structured English Query Language) at IBM Research. This language was first implemented in an IBM prototype called SEQUEL-XRM in 1974-75. In 1976-77 a revised version - of SEQUEL called SEQUEL/2 was defined and the name was changed to SQL + of SEQUEL called SEQUEL/2 was defined and the name was changed to + SQL subsequently. -A new prototype called System R was developed by IBM in 1977. System R -implemented a large subset of SEQUEL/2 (now SQL) and a number of -changes were made to SQL during the project. System R was installed in -a number of user sites, both internal IBM sites and also some selected -customer sites. Thanks to the success and acceptance of System R at -those user sites IBM started to develop commercial products that -implemented the SQL language based on the System R technology. + A new prototype called System R was developed by IBM in 1977. System R + implemented a large subset of SEQUEL/2 (now SQL) and a number of + changes were made to SQL during the project. + System R was installed in + a number of user sites, both internal IBM sites and also some selected + customer sites. Thanks to the success and acceptance of System R at + those user sites IBM started to develop commercial products that + implemented the SQL language based on the System R technology. -Over the next years IBM and also a number of other vendors announced -SQL products such as SQL/DS (IBM), DB2 (IBM) ORACLE (Oracle Corp.) -DG/SQL (Data General Corp.) SYBASE (Sybase Inc.). + Over the next years IBM and also a number of other vendors announced + SQL products such as + SQL/DS (IBM), + DB2 (IBM), + ORACLE (Oracle Corp.), + DG/SQL (Data General Corp.), + and SYBASE (Sybase Inc.). -SQL is also an official standard now. In 1982 the American National -Standards Institute (ANSI) chartered its Database Committee X3H2 to -develop a proposal for a standard relational language. This proposal -was ratified in 1986 and consisted essentially of the IBM dialect of -SQL. In 1987 this ANSI standard was also accepted as an international -standard by the International Organization for Standardization -(ISO). This original standard version of SQL is often referred to, -informally, as "SQL/86". In 1989 the original standard was extended -and this new standard is often, again informally, referred to as -"SQL/89". Also in 1989, a related standard called {\it Database -Language Embedded SQL} was developed. + SQL is also an official standard now. In 1982 the American National + Standards Institute (ANSI) chartered its Database Committee X3H2 to + develop a proposal for a standard relational language. This proposal + was ratified in 1986 and consisted essentially of the IBM dialect of + SQL. In 1987 this ANSI + standard was also accepted as an international + standard by the International Organization for Standardization + (ISO). + This original standard version of SQL is often referred to, + informally, as "SQL/86". In 1989 the original standard was extended + and this new standard is often, again informally, referred to as + "SQL/89". Also in 1989, a related standard called + Database Language Embedded SQL + (ESQL) was developed. - The ISO and ANSI committees have been working for many years on the + The ISO and ANSI committees + have been working for many years on the definition of a greatly expanded version of the original standard, - referred to informally as "SQL2" or "SQL/92". This version became a - ratified standard - "International Standard \mbox{ISO/IEC 9075:1992}, {\it - Database Language SQL}" - in late 1992. "SQL/92" is the version - normally meant when people refer to "the SQL standard". A detailed - description of "SQL/92" is given in \cite{date}. At the time of - writing this document a new standard informally referred to as "SQL3" - is under development. It is planned to make SQL a turing-complete - language, i.e.\ all computable queries (e.g. recursive queries) will be + referred to informally as SQL2 + or SQL/92. This version became a + ratified standard - "International Standard ISO/IEC 9075:1992, + Database Language SQL" - in late 1992. + SQL/92 is the version + normally meant when people refer to "the SQL standard". A detailed + description of SQL/92 is given in + . At the time of + writing this document a new standard informally referred to + as SQL3 + is under development. It is planned to make SQL a Turing-complete + language, i.e. all computable queries (e.g. recursive queries) will be possible. This is a very complex task and therefore the completion of the new standard can not be expected before 1999. - The Relational Data Model} + The Relational Data Model - As mentioned before, SQL is a relational language. That means it is - based on the "relational data model" first published by E.F. Codd in + As mentioned before, SQL is a relational + language. That means it is + based on the relational data model + first published by E.F. Codd in 1970. We will give a formal description of the relational model in - section + section but first we want to have a look at it from a more intuitive point of view. - A {\it relational database} is a database that is perceived by its - users as a {\it collection of tables} (and nothing else but tables). + A relational database is a database that is perceived by its + users as a collection of tables (and nothing else but tables). A table consists of rows and columns where each row represents a record and each column represents an attribute of the records - contained in the table. Figure \ref{supplier} shows an example of a - database consisting of three tables: -\begin{itemize} -\item SUPPLIER is a table storing the number -(SNO), the name (SNAME) and the city (CITY) of a supplier. -\item PART is a table storing the number (PNO) the name (PNAME) and -the price (PRICE) of a part. -\item SELLS stores information about which part (PNO) is sold by which -supplier (SNO). It serves in a sense to connect the other two tables -together. -\end{itemize} -% -\begin{figure}[h] -\begin{verbatim} + contained in the table. + Figure + shows an example of a database consisting of three tables: + + + + + SUPPLIER is a table storing the number + (SNO), the name (SNAME) and the city (CITY) of a supplier. + + + + + + PART is a table storing the number (PNO) the name (PNAME) and + the price (PRICE) of a part. + + + + + + SELLS stores information about which part (PNO) is sold by which + supplier (SNO). + It serves in a sense to connect the other two tables together. + + + + + The Suppliers and Parts Database + SUPPLIER SNO | SNAME | CITY SELLS SNO | PNO -----+---------+-------- -----+----- 1 | Smith | London 1 | 1 @@ -131,56 +144,132 @@ together. 2 | Nut | 8 3 | Bolt | 15 4 | Cam | 25 -\end{verbatim} -\caption{The suppliers and parts database} -\label{supplier} -\end{figure} -% -The tables PART and SUPPLIER may be regarded as {\it entities} and -SELLS may be regarded as a {\it relationship} between a particular -part and a particular supplier. + + + -As we will see later, SQL operates on tables like the ones just -defined but before that we will study the theory of the relational -model. + + The tables PART and SUPPLIER may be regarded as entities and + SELLS may be regarded as a relationship between a particular + part and a particular supplier. + -\subsection{Formal Notion of the Relational Data Model} -\label{formal_notion} -The mathematical concept underlying the relational model is the -set-theoretic {\it relation} which is a subset of the Cartesian -product of a list of domains. This set-theoretic {\it relation} gives -the model its name (do not confuse it with the relationship from the {\it -Entity-Relationship model}). Formally a domain is simply a set of -values. For example the set of integers is a domain. Also the set of -character strings of length 20 and the real numbers are examples of -domains. + + As we will see later, SQL operates on tables like the ones just + defined but before that we will study the theory of the relational + model. + + + + + Formal Notion of the Relational Data Model + + + The mathematical concept underlying the relational model is the + set-theoretic relation which is a subset of the Cartesian + product of a list of domains. This set-theoretic relation gives + the model its name (do not confuse it with the relationship from the + Entity-Relationship model). + Formally a domain is simply a set of + values. For example the set of integers is a domain. Also the set of + character strings of length 20 and the real numbers are examples of + domains. + + + + + The Cartesian product of domains + D1, + D2, + ... + Dk, + written + D1 × + D2 × + ... × + Dk + is the set of all k-tuples + v1, + v2, + ... + vk, + such that + v1 ∈ + D1, + v1 ∈ + D1, + ... + vk ∈ + Dk. + + + + For example, when we have + + k=2, + D1={0,1} and + D2={a,b,c} then + D1 × + D2 is + {(0,a),(0,b),(0,c),(1,a),(1,b),(1,c)}. + + + + + A Relation is any subset of the Cartesian product of one or more + domains: R ⊆ + D1 × + D2 × + ... × + Dk. + -A relation can be viewed as a table (as we already did, remember -figure \ref{supplier} {\it The suppliers and parts database}) where -every tuple is represented by a row and every column corresponds to -one component of a tuple. Giving names (called attributes) to the -columns leads to the definition of a {\it relation scheme}. -% + + For example {(0,a),(0,b),(1,a)} is a relation; + it is in fact a subset of + D1 × + D2 + mentioned above. + + + + The members of a relation are called tuples. Each relation of some + Cartesian product + D1 × + D2 × + ... × + Dk + is said to have arity k and is therefore a set + of k-tuples. + + + + A relation can be viewed as a table (as we already did, remember + where + every tuple is represented by a row and every column corresponds to + one component of a tuple. Giving names (called attributes) to the + columns leads to the definition of a + relation scheme. + + + + + A relation scheme R is a + finite set of attributes + A1, + A2, + ... + Ak. + There is a domain + Di, + for each attribute + Ai, + 1 ≤ i ≤ k, + where the values of the attributes are taken from. We often write + a relation scheme as + R(A1, + A2, + ... + Ak). -\subsubsection{Domains vs. Data Types} -\label{domains} -We often talked about {\it domains} in the last section. Recall that a -domain is, formally, just a set of values (e.g., the set of integers or -the real numbers). In terms of database systems we often talk of {\it -data types} instead of domains. When we define a table we have to make -a decision about which attributes to include. Additionally we -have to decide which kind of data is going to be stored as -attribute values. For example the values of SNAME from the table -SUPPLIER will be character strings, whereas SNO will store -integers. We define this by assigning a {\it data type} to each -attribute. The type of SNAME will be VARCHAR(20) (this is the SQL type -for character strings of length $\le$ 20), the type of SNO will be -INTEGER. With the assignment of a {\it data type} we also have selected -a domain for an attribute. The domain of SNAME is the set of all -character strings of length $\le$ 20, the domain of SNO is the set of -all integer numbers. + + + A relation scheme is just a kind of template + whereas a relation is an instance of a relation + scheme. The relation consists of tuples (and can therefore be + viewed as a table); not so the relation scheme. + + + -\section{Operations in the Relational Data Model} -\label{operations} -In section \ref{formal_notion} we defined the mathematical notion of -the relational model. Now we know how the data can be stored using a -relational data model but we do not know what to do with all these -tables to retrieve something from the database yet. For example somebody -could ask for the names of all suppliers that sell the part -'Screw'. Therefore two rather different kinds of notations for -expressing operations on relations have been defined: -% -\begin{itemize} -\item The {\it Relational Algebra} which is an algebraic notation, -where queries are expressed by applying specialized operators to the -relations. -\item The {\it Relational Calculus} which is a logical notation, -where queries are expressed by formulating some logical restrictions -that the tuples in the answer must satisfy. -\end{itemize} -% -\subsection{Relational Algebra} -\label{rel_alg} -The {\it Relational Algebra} was introduced by E.~F.~Codd in 1972. It -consists of a set of operations on relations: -\begin{itemize} -\item SELECT ($\sigma$): extracts {\it tuples} from a relation that -satisfy a given restriction. Let $R$ be a table that contains an attribute -$A$. $\sigma_{A=a}(R) = \{t \in R \mid t(A) = a\}$ where $t$ denotes a -tuple of $R$ and $t(A)$ denotes the value of attribute $A$ of tuple $t$. -\item PROJECT ($\pi$): extracts specified {\it attributes} (columns) from a -relation. Let $R$ be a relation that contains an attribute $X$. $\pi_{X}(R) = -\{t(X) \mid t \in R\}$, where $t(X)$ denotes the value of attribute $X$ of -tuple $t$. -\item PRODUCT ($\times$): builds the Cartesian product of two -relations. Let $R$ be a table with arity $k_{1}$ and let $S$ be a table with -arity $k_{2}$. $R\times S$ is the set of all $(k_{1}+k_{2})$-tuples -whose first $k_{1}$ components form a tuple in $R$ and whose last -$k_{2}$ components form a tuple in $S$. -\item UNION ($\cup$): builds the set-theoretic union of two -tables. Given the tables $R$ and $S$ (both must have the same arity), -the union $R \cup S$ is the set of tuples that are in $R$ or $S$ or -both. -\item INTERSECT ($\cap$): builds the set-theoretic intersection of two -tables. Given the tables $R$ and $S$, $R \cup S$ is the set of tuples -that are in $R$ and in $S$. We again require that $R$ and $S$ have the -same arity. -\item DIFFERENCE ($-$ or $\setminus$): builds the set difference of -two tables. Let $R$ and $S$ again be two tables with the same -arity. $R-S$ is the set of tuples in $R$ but not in $S$. -\item JOIN ($\Join$): connects two tables by their common -attributes. Let $R$ be a table with the attributes $A,B$ and $C$ and -let $S$ a table with the attributes $C,D$ and $E$. There is one -attribute common to both relations, the attribute $C$. $R \Join S = -\pi_{R.A,R.B,R.C,S.D,S.E}(\sigma_{R.C=S.C}(R \times S))$. What are we -doing here? We first calculate the Cartesian product $R \times -S$. Then we select those tuples whose values for the common -attribute $C$ are equal ($\sigma_{R.C = S.C}$). Now we got a table -that contains the attribute $C$ two times and we correct this by -projecting out the duplicate column. -\begin{example} -\label{join_example} -Let's have a look at the tables that are produced by evaluating the steps -necessary for a join. \\ -Let the following two tables be given: -\begin{verbatim} - R A | B | C S C | D | E + + Domains vs. Data Types + + + We often talked about domains + in the last section. Recall that a + domain is, formally, just a set of values (e.g., the set of integers or + the real numbers). In terms of database systems we often talk of + data types instead of domains. + When we define a table we have to make + a decision about which attributes to include. Additionally we + have to decide which kind of data is going to be stored as + attribute values. For example the values of + SNAME from the table + SUPPLIER will be character strings, + whereas SNO will store + integers. We define this by assigning a data type to each + attribute. The type of SNAME will be + VARCHAR(20) (this is the SQL type + for character strings of length ≤ 20), the type of SNO will be + INTEGER. With the assignment of a data type we also have selected + a domain for an attribute. The domain of SNAME is the set of all + character strings of length ≤ 20, the domain of SNO is the set of + all integer numbers. + + + + + + Operations in the Relational Data + Model + + + In section + we defined the mathematical notion of + the relational model. Now we know how the data can be stored using a + relational data model but we do not know what to do with all these + tables to retrieve something from the database yet. For example somebody + could ask for the names of all suppliers that sell the part + 'Screw'. Therefore two rather different kinds of notations for + expressing operations on relations have been defined: + + + + + The Relational Algebra which is an algebraic notation, + where queries are expressed by applying specialized operators to the + relations. + + + + + + The Relational Calculus which is a logical notation, + where queries are expressed by formulating some logical restrictions + that the tuples in the answer must satisfy. + + + + + + + Relational Algebra + + + The Relational Algebra was introduced by + E. F. Codd in 1972. It consists of a set of operations on relations: + + + + + SELECT (σ): extracts tuples from a relation that + satisfy a given restriction. Let R be a + table that contains an attribute + A. +σA=a(R) = {t ∈ R ∣ t(A) = a} + where t denotes a + tuple of R and t(A) + denotes the value of attribute A of + tuple t. + + + + + + PROJECT (π): extracts specified + attributes (columns) from a + relation. Let R be a relation + that contains an attribute X. + πX(R) = {t(X) ∣ t ∈ R}, + where t(X) denotes the value of + attribute X of tuple t. + + + + + + PRODUCT (×): builds the Cartesian product of two + relations. Let R be a table with arity + k1 and let + S be a table with + arity k2. + R × S + is the set of all + k1 + + k2-tuples + whose first k1 + components form a tuple in R and whose last + k2 components form a + tuple in S. + + + + + + UNION (∪): builds the set-theoretic union of two + tables. Given the tables R and + S (both must have the same arity), + the union R ∪ S + is the set of tuples that are in R + or S or both. + + + + + + INTERSECT (∩): builds the set-theoretic intersection of two + tables. Given the tables R and + S, + R ∪ S is the set of tuples + that are in R and in + S. + We again require that R and S have the + same arity. + + + + + + DIFFERENCE (− or ∖): builds the set difference of + two tables. Let R and S + again be two tables with the same + arity. R - S + is the set of tuples in R but not in S. + + + + + + JOIN (∏): connects two tables by their common + attributes. Let R be a table with the + attributes A,B + and C and + let S be a table with the attributes + C,D + and E. There is one + attribute common to both relations, + the attribute C. + + R ∏ S = πR.A,R.B,R.C,S.D,S.E(σR.C=S.C(R × S)). + What are we doing here? We first calculate the Cartesian + product + R × S. + Then we select those tuples whose values for the common + attribute C are equal + (σR.C = S.C). + Now we have a table + that contains the attribute C + two times and we correct this by + projecting out the duplicate column. + + + + Let's have a look at the tables that are produced by evaluating the steps + necessary for a join. + Let the following two tables be given: + + + R A | B | C S C | D | E ---+---+--- ---+---+--- - 1 | 2 | 3 3 | a | b - 4 | 5 | 6 6 | c | d - 7 | 8 | 9 -\end{verbatim} -First we calculate the Cartesian product $R \times S$ and get: -\begin{verbatim} + 1 | 2 | 3 3 | a | b + 4 | 5 | 6 6 | c | d + 7 | 8 | 9 + + + + + First we calculate the Cartesian product + R × S and + get: + + R x S A | B | R.C | S.C | D | E ---+---+-----+-----+---+--- 1 | 2 | 3 | 3 | a | b @@ -291,36 +509,65 @@ First we calculate the Cartesian product $R \times S$ and get: 4 | 5 | 6 | 6 | c | d 7 | 8 | 9 | 3 | a | b 7 | 8 | 9 | 6 | c | d -\end{verbatim} -\pagebreak -After the selection $\sigma_{R.C=S.C}(R \times S)$ we get: -\begin{verbatim} + + + + + After the selection + σR.C=S.C(R × S) + we get: + + A | B | R.C | S.C | D | E ---+---+-----+-----+---+--- 1 | 2 | 3 | 3 | a | b 4 | 5 | 6 | 6 | c | d -\end{verbatim} -To remove the duplicate column $S.C$ we project it out by the -following operation: $\pi_{R.A,R.B,R.C,S.D,S.E}(\sigma_{R.C=S.C}(R -\times S))$ and get: -\begin{verbatim} + + + + + To remove the duplicate column + S.C + we project it out by the following operation: + πR.A,R.B,R.C,S.D,S.E(σR.C=S.C(R × S)) + and get: + + A | B | C | D | E ---+---+---+---+--- 1 | 2 | 3 | a | b 4 | 5 | 6 | c | d -\end{verbatim} -\end{example} -\item DIVIDE ($\div$): Let $R$ be a table with the attributes $A,B,C$ -and $D$ and let $S$ be a table with the attributes $C$ and $D$. Then -we define the division as: $R \div S = \{t \mid \forall t_{s} \in S~ -\exists t_{r} \in R$ such that -$t_{r}(A,B)=t~\wedge~t_{r}(C,D)=t_{s}\}$ where $t_{r}(x,y)$ denotes a -tuple of table $R$ that consists only of the components $x$ and -$y$. Note that the tuple $t$ only consists of the components $A$ and -$B$ of relation $R$. -\begin{example} -Given the following tables -\begin{verbatim} + + + + + + + DIVIDE (÷): Let R be a table + with the attributes A, B, C, and D and let + S be a table with the attributes + C and D. + Then we define the division as: + +R ÷ S = {t ∣ ∀ ts ∈ S + ∃ tr ∈ R + + such that +tr(A,B)=t∧tr(C,D)=ts} + where + tr(x,y) + denotes a + tuple of table R that consists only of + the components x and y. + Note that the tuple t only consists of the + components A and + B of relation R. + + + + Given the following tables + + R A | B | C | D S C | D ---+---+---+--- ---+--- a | b | c | d c | d @@ -329,238 +576,359 @@ Given the following tables e | d | c | d e | d | e | f a | b | d | e -\end{verbatim} -$R \div S$ is derived as -\begin{verbatim} + + + R ÷ S + is derived as + + A | B ---+--- a | b e | d -\end{verbatim} -\end{example} -\end{itemize} -% -For a more detailed description and definition of the relational -algebra refer to \cite{ullman} or \cite{date86}. + + + + + -\begin{example} -\label{suppl_rel_alg} -Recall that we formulated all those relational operators to be able to -retrieve data from the database. Let's return to our example of -section \ref{operations} where someone wanted to know the names of all -suppliers that sell the part 'Screw'. This question can be answered -using relational algebra by the following operation: -\begin{displaymath} -\pi_{SUPPLIER.SNAME}(\sigma_{PART.PNAME='Screw'}(SUPPLIER \Join SELLS -\Join PART)) -\end{displaymath} -We call such an operation a query. If we evaluate the above query -against the tables form figure \ref{supplier} {\it The suppliers and -parts database} we will obtain the following result: -\begin{verbatim} + + For a more detailed description and definition of the relational + algebra refer to ullman or + date86. + + + + Recall that we formulated all those relational operators to be able to + retrieve data from the database. Let's return to our example of + section + where someone wanted to know the names of all + suppliers that sell the part Screw. + This question can be answered + using relational algebra by the following operation: + + πSUPPLIER.SNAME(σPART.PNAME='Screw'(SUPPLIER ∏ SELLS ∏ PART)) + + + + + We call such an operation a query. If we evaluate the above query + against the tables from figure + (The suppliers and + parts database) we will obtain the following result: + + SNAME ------- Smith Adams -\end{verbatim} -\end{example} -\subsection{Relational Calculus} -\label{rel_calc} -The relational calculus is based on the {first order logic}. There are -two variants of the relational calculus: -% -\begin{itemize} -\item The {\it Domain Relational Calculus} (DRC), where variables -stand for components (attributes) of the tuples. -\item The {\it Tuple Relational Calculus} (TRC), where variables stand -for tuples. -\end{itemize} -% -We want to discuss the tuple relational calculus only because it is -the one underlying the most relational languages. For a detailed -discussion on DRC (and also TRC) see \cite{date86} or \cite{ullman}. + + + -\subsubsection{Tuple Relational Calculus} -The queries used in TRC are of the following form: -\begin{displaymath} -\{x(A) \mid F(x)\} -\end{displaymath} -where $x$ is a tuple variable $A$ is a set of attributes and $F$ is a -formula. The resulting relation consists of all tuples $t(A)$ that satisfy -$F(t)$. -\begin{example} -If we want to answer the question from example \ref{suppl_rel_alg} -using TRC we formulate the following query: -\begin{displaymath} -\begin{array}{lcll} -\{x(SNAME) & \mid & x \in SUPPLIER~\wedge & \nonumber\\ -& & \exists y \in SELLS\ \exists z \in PART & (y(SNO)=x(SNO)~\wedge \nonumber\\ -& & &~ z(PNO)=y(PNO)~\wedge \nonumber\\ -& & &~ z(PNAME)='Screw')\} \nonumber -\end{array} -\end{displaymath} -Evaluating the query against the tables from figure \ref{supplier} -{\it The suppliers and parts database} again leads to the same result -as in example \ref{suppl_rel_alg}. -\end{example} + + Relational Calculus -\subsection{Relational Algebra vs. Relational Calculus} -\label{alg_vs_calc} -The relational algebra and the relational calculus have the same {\it -expressive power} i.e.\ all queries that can be formulated using -relational algebra can also be formulated using the relational -calculus and vice versa. This was first proved by E.~F.~Codd in -1972. This proof is based on an algorithm -"Codd's reduction -algorithm"- by which an arbitrary expression of the relational -calculus can be reduced to a semantically equivalent expression of -relational algebra. For a more detailed discussion on that refer to -\cite{date86} and -\cite{ullman}. + + The relational calculus is based on the + first order logic. There are + two variants of the relational calculus: -It is sometimes said that languages based on the relational calculus -are "higher level" or "more declarative" than languages based on -relational algebra because the algebra (partially) specifies the order -of operations while the calculus leaves it to a compiler or -interpreter to determine the most efficient order of evaluation. + + + + The Domain Relational Calculus + (DRC), where variables + stand for components (attributes) of the tuples. + + + + + The Tuple Relational Calculus + (TRC), where variables stand for tuples. + + + + -\section{The SQL Language} -\label{sqllanguage} -% -As most modern relational languages SQL is based on the tuple -relational calculus. As a result every query that can be formulated -using the tuple relational calculus (or equivalently, relational -algebra) can also be formulated using SQL. There are, however, -capabilities beyond the scope of relational algebra or calculus. Here -is a list of some additional features provided by SQL that are not -part of relational algebra or calculus: -\pagebreak -% -\begin{itemize} -\item Commands for insertion, deletion or modification of data. -\item Arithmetic capability: In SQL it is possible to involve -arithmetic operations as well as comparisons, e.g. $A < B + 3$. Note -that $+$ or other arithmetic operators appear neither in relational -algebra nor in relational calculus. -\item Assignment and Print Commands: It is possible to print a -relation constructed by a query and to assign a computed relation to a -relation name. -\item Aggregate Functions: Operations such as {\it average}, {\it -sum}, {\it max}, \ldots can be applied to columns of a relation to -obtain a single quantity. -\end{itemize} -% -\subsection{Select} -\label{select} -The most often used command in SQL is the SELECT statement that is -used to retrieve data. The syntax is: -\begin{verbatim} + + We want to discuss the tuple relational calculus only because it is + the one underlying the most relational languages. For a detailed + discussion on DRC (and also + TRC) see date86 or + ullman. + + + + + Tuple Relational Calculus + + + The queries used in TRC are of the following + form: + x(A) ∣ F(x) + + where x is a tuple variable + A is a set of attributes and F is a + formula. The resulting relation consists of all tuples + t(A) that satisfy F(t). + + + + If we want to answer the question from example + + using TRC we formulate the following query: + + {x(SNAME) ∣ x ∈ SUPPLIER ∧ \nonumber + ∃ y ∈ SELLS ∃ z ∈ PART (y(SNO)=x(SNO) ∧ \nonumber + z(PNO)=y(PNO) ∧ \nonumber + z(PNAME)='Screw')} \nonumber + + + + Evaluating the query against the tables from figure + + (The suppliers and parts database) + again leads to the same result + as in example + . + + + + + Relational Algebra vs. Relational Calculus + + + The relational algebra and the relational calculus have the same + expressive power; i.e. all queries that + can be formulated using relational algebra can also be formulated + using the relational calculus and vice versa. + This was first proved by E. F. Codd in + 1972. This proof is based on an algorithm (Codd's reduction + algorithm) by which an arbitrary expression of the relational + calculus can be reduced to a semantically equivalent expression of + relational algebra. For a more detailed discussion on that refer to + date86 and + ullman. + + + + It is sometimes said that languages based on the relational calculus + are "higher level" or "more declarative" than languages based on + relational algebra because the algebra (partially) specifies the order + of operations while the calculus leaves it to a compiler or + interpreter to determine the most efficient order of evaluation. + + + + + + The <acronym>SQL</acronym> Language + + + As most modern relational languages SQL is based on the tuple + relational calculus. As a result every query that can be formulated + using the tuple relational calculus (or equivalently, relational + algebra) can also be formulated using SQL. There are, however, + capabilities beyond the scope of relational algebra or calculus. Here + is a list of some additional features provided by SQL that are not + part of relational algebra or calculus: + + + + + Commands for insertion, deletion or modification of data. + + + + + + Arithmetic capability: In SQL it is possible to involve + arithmetic operations as well as comparisons, e.g. + + A < B + 3. + + Note + that + or other arithmetic operators appear neither in relational + algebra nor in relational calculus. + + + + + + Assignment and Print Commands: It is possible to print a + relation constructed by a query and to assign a computed relation to a + relation name. + + + + + + Aggregate Functions: Operations such as + average, sum, + max, etc. can be applied to columns of a relation to + obtain a single quantity. + + + + + + + Select + + + The most often used command in SQL is the + SELECT statement, + used to retrieve data. The syntax is: + + SELECT [ALL|DISTINCT] - { * | [AS ] [, ... - [, [AS ]]]} - FROM [t_alias_1] - [, ... [, [t_alias_n]]] - [WHERE condition] - [GROUP BY - [,... [, ]] [HAVING condition]] + { * | expr_1 [AS c_alias_1] [, ... + [, expr_k [AS c_alias_k]]]} + FROM table_name_1 [t_alias_1] + [, ... [, table_name_n [t_alias_n]]] + [WHERE condition] + [GROUP BY name_of_attr_i + [,... [, name_of_attr_j]] [HAVING condition]] [{UNION [ALL] | INTERSECT | EXCEPT} SELECT ...] - [ORDER BY [ASC|DESC] - [, ... [, [ASC|DESC]]]]; -\end{verbatim} -Now we will illustrate the complex syntax of the SELECT statement -with various examples. The tables used for the examples are defined in -figure \ref{supplier} {\it The suppliers and parts database}. -% -\subsubsection{Simple Selects} -\begin{example} -Here are some simple examples using a SELECT statement: \\ -\\ -To retrieve all tuples from table PART where the attribute PRICE is -greater than 10 we formulate the following query -\begin{verbatim} - SELECT * - FROM PART - WHERE PRICE > 10; -\end{verbatim} -and get the table: -\begin{verbatim} + [ORDER BY name_of_attr_i [ASC|DESC] + [, ... [, name_of_attr_j [ASC|DESC]]]]; + + + + + Now we will illustrate the complex syntax of the SELECT statement + with various examples. The tables used for the examples are defined in + figure (The suppliers and parts database). + + + + Simple Selects + + + Here are some simple examples using a SELECT statement: + + + Simple Query with Qualification + + To retrieve all tuples from table PART where the attribute PRICE is + greater than 10 we formulate the following query: + + + SELECT * FROM PART + WHERE PRICE > 10; + + + and get the table: + + PNO | PNAME | PRICE -----+---------+-------- 3 | Bolt | 15 4 | Cam | 25 -\end{verbatim} -% -Using "$*$" in the SELECT statement will deliver all attributes from -the table. If we want to retrieve only the attributes PNAME and PRICE -from table PART we use the statement: -\begin{verbatim} + + + + + Using "*" in the SELECT statement will deliver all attributes from + the table. If we want to retrieve only the attributes PNAME and PRICE + from table PART we use the statement: + + SELECT PNAME, PRICE FROM PART WHERE PRICE > 10; -\end{verbatim} -\pagebreak -\noindent In this case the result is: -\begin{verbatim} + + + In this case the result is: + + PNAME | PRICE --------+-------- Bolt | 15 Cam | 25 -\end{verbatim} -Note that the SQL SELECT corresponds to the "projection" in relational -algebra not to the "selection" (see section \ref{rel_alg} {\it -Relational Algebra}). -\\ \\ -The qualifications in the WHERE clause can also be logically connected -using the keywords OR, AND and NOT: -\begin{verbatim} + + + Note that the SQL SELECT corresponds to the + "projection" in relational algebra not to the "selection" + (see section + (Relational Algebra). + + + + The qualifications in the WHERE clause can also be logically connected + using the keywords OR, AND, and NOT: + + SELECT PNAME, PRICE FROM PART WHERE PNAME = 'Bolt' AND (PRICE = 0 OR PRICE < 15); -\end{verbatim} -will lead to the result: -\begin{verbatim} + + + will lead to the result: + + PNAME | PRICE --------+-------- Bolt | 15 -\end{verbatim} -Arithmetic operations may be used in the {\it selectlist} and in the WHERE -clause. For example if we want to know how much it would cost if we -take two pieces of a part we could use the following query: -\begin{verbatim} + + + + + Arithmetic operations may be used in the target list and in the WHERE + clause. For example if we want to know how much it would cost if we + take two pieces of a part we could use the following query: + + SELECT PNAME, PRICE * 2 AS DOUBLE FROM PART WHERE PRICE * 2 < 50; -\end{verbatim} -and we get: -\begin{verbatim} + + + and we get: + + PNAME | DOUBLE --------+--------- Screw | 20 Nut | 16 Bolt | 30 -\end{verbatim} -Note that the word DOUBLE after the keyword AS is the new title of the -second column. This technique can be used for every element of the -{\it selectlist} to assign a new title to the resulting column. This new title -is often referred to as alias. The alias cannot be used throughout the -rest of the query. -\end{example} + -\subsubsection{Joins} -\begin{example} The following example shows how {\it joins} are -realized in SQL: \\ \\ -To join the three tables SUPPLIER, PART and SELLS over their common -attributes we formulate the following statement: -\begin{verbatim} + Note that the word DOUBLE after the keyword AS is the new title of the + second column. This technique can be used for every element of the + target list to assign a new title to the resulting column. This new title + is often referred to as alias. The alias cannot be used throughout the + rest of the query. + + + + + + + Joins + + + The following example shows how joins are + realized in SQL. + + + + To join the three tables SUPPLIER, PART and SELLS over their common + attributes we formulate the following statement: + + SELECT S.SNAME, P.PNAME FROM SUPPLIER S, PART P, SELLS SE WHERE S.SNO = SE.SNO AND P.PNO = SE.PNO; -\end{verbatim} -\pagebreak -\noindent and get the following table as a result: -\begin{verbatim} + + + and get the following table as a result: + + SNAME | PNAME -------+------- Smith | Screw @@ -571,90 +939,139 @@ attributes we formulate the following statement: Blake | Nut Blake | Bolt Blake | Cam -\end{verbatim} -In the FROM clause we introduced an alias name for every relation -because there are common named attributes (SNO and PNO) among the -relations. Now we can distinguish between the common named attributes -by simply prefixing the attribute name with the alias name followed by -a dot. The join is calculated in the same way as shown in example -\ref{join_example}. First the Cartesian product $SUPPLIER\times PART -\times SELLS$ is derived. Now only those tuples satisfying the -conditions given in the WHERE clause are selected (i.e.\ the common -named attributes have to be equal). Finally we project out all -columns but S.SNAME and P.PNAME. -\end{example} -% -\subsubsection{Aggregate Operators} -SQL provides aggregate operators (e.g. AVG, COUNT, SUM, MIN, MAX) that -take the name of an attribute as an argument. The value of the -aggregate operator is calculated over all values of the specified -attribute (column) of the whole table. If groups are specified in the -query the calculation is done only over the values of a group (see next -section). + + -\begin{example} -If we want to know the average cost of all parts in table PART we use -the following query: -\begin{verbatim} + + In the FROM clause we introduced an alias name for every relation + because there are common named attributes (SNO and PNO) among the + relations. Now we can distinguish between the common named attributes + by simply prefixing the attribute name with the alias name followed by + a dot. The join is calculated in the same way as shown in example + . + First the Cartesian product + + SUPPLIER × PART × SELLS + + is derived. Now only those tuples satisfying the + conditions given in the WHERE clause are selected (i.e. the common + named attributes have to be equal). Finally we project out all + columns but S.SNAME and P.PNAME. + + + + + Aggregate Operators + + + SQL provides aggregate operators + (e.g. AVG, COUNT, SUM, MIN, MAX) that + take the name of an attribute as an argument. The value of the + aggregate operator is calculated over all values of the specified + attribute (column) of the whole table. If groups are specified in the + query the calculation is done only over the values of a group (see next + section). + + + Aggregates + + + If we want to know the average cost of all parts in table PART we use + the following query: + + SELECT AVG(PRICE) AS AVG_PRICE FROM PART; -\end{verbatim} -The result is: -\begin{verbatim} + + + + + The result is: + + AVG_PRICE ----------- 14.5 -\end{verbatim} -If we want to know how many parts are stored in table PART we use -the statement: -\begin{verbatim} + + + + + If we want to know how many parts are stored in table PART we use + the statement: + + SELECT COUNT(PNO) FROM PART; -\end{verbatim} -and get: -\begin{verbatim} + + + and get: + + COUNT ------- 4 -\end{verbatim} -\end{example} + -\subsubsection{Aggregation by Groups} -SQL allows to partition the tuples of a table into groups. Then the -aggregate operators described above can be applied to the groups -(i.e. the value of the aggregate operator is no longer calculated over -all the values of the specified column but over all values of a -group. Thus the aggregate operator is evaluated individually for every -group.) -\\ \\ -The partitioning of the tuples into groups is done by using the -keywords \mbox{GROUP BY} followed by a list of attributes that define the -groups. If we have {\tt GROUP BY $A_{1}, \ldots, A_{k}$} we partition -the relation into groups, such that two tuples are in the same group -if and only if they agree on all the attributes $A_{1}, \ldots, -A_{k}$. -\begin{example} -If we want to know how many parts are sold by every supplier we -formulate the query: -\begin{verbatim} + + + + + + + Aggregation by Groups + + + SQL allows one to partition the tuples of a table + into groups. Then the + aggregate operators described above can be applied to the groups + (i.e. the value of the aggregate operator is no longer calculated over + all the values of the specified column but over all values of a + group. Thus the aggregate operator is evaluated individually for every + group.) + + + + The partitioning of the tuples into groups is done by using the + keywords GROUP BY followed by a list of + attributes that define the + groups. If we have + GROUP BY A1, ⃛, Ak + we partition + the relation into groups, such that two tuples are in the same group + if and only if they agree on all the attributes + A1, ⃛, Ak. + + + Aggregates + + If we want to know how many parts are sold by every supplier we + formulate the query: + + SELECT S.SNO, S.SNAME, COUNT(SE.PNO) FROM SUPPLIER S, SELLS SE WHERE S.SNO = SE.SNO GROUP BY S.SNO, S.SNAME; -\end{verbatim} -and get: -\begin{verbatim} + + + and get: + + SNO | SNAME | COUNT -----+-------+------- 1 | Smith | 2 2 | Jones | 1 3 | Adams | 2 4 | Blake | 3 -\end{verbatim} -Now let's have a look of what is happening here: \\ -First the join of the -tables SUPPLIER and SELLS is derived: -\begin{verbatim} + + + + + Now let's have a look of what is happening here. + First the join of the + tables SUPPLIER and SELLS is derived: + + S.SNO | S.SNAME | SE.PNO -------+---------+-------- 1 | Smith | 1 @@ -665,10 +1082,14 @@ tables SUPPLIER and SELLS is derived: 4 | Blake | 2 4 | Blake | 3 4 | Blake | 4 -\end{verbatim} -Next we partition the tuples into groups by putting all tuples -together that agree on both attributes S.SNO and S.SNAME: -\begin{verbatim} + + + + + Next we partition the tuples into groups by putting all tuples + together that agree on both attributes S.SNO and S.SNAME: + + S.SNO | S.SNAME | SE.PNO -------+---------+-------- 1 | Smith | 1 @@ -682,101 +1103,153 @@ together that agree on both attributes S.SNO and S.SNAME: 4 | Blake | 2 | 3 | 4 -\end{verbatim} -In our example we got four groups and now we can apply the aggregate -operator COUNT to every group leading to the total result of the query -given above. -\end{example} -% - Note that for the result of a query using GROUP BY and aggregate -operators to make sense the attributes grouped by must also appear in -the {\it selectlist}. All further attributes not appearing in the GROUP -BY clause can only be selected by using an aggregate function. On -the other hand you can not use aggregate functions on attributes -appearing in the GROUP BY clause. + + -\subsubsection{Having} + + In our example we got four groups and now we can apply the aggregate + operator COUNT to every group leading to the total result of the query + given above. + + + -The HAVING clause works much like the WHERE clause and is used to -consider only those groups satisfying the qualification given in the -HAVING clause. The expressions allowed in the HAVING clause must -involve aggregate functions. Every expression using only plain -attributes belongs to the WHERE clause. On the other hand every -expression involving an aggregate function must be put to the HAVING -clause. -\begin{example} -If we want only those suppliers selling more than one part we use the -query: -\begin{verbatim} + + Note that for the result of a query using GROUP BY and aggregate + operators to make sense the attributes grouped by must also appear in + the target list. All further attributes not appearing in the GROUP + BY clause can only be selected by using an aggregate function. On + the other hand you can not use aggregate functions on attributes + appearing in the GROUP BY clause. + + + + + Having + + + The HAVING clause works much like the WHERE clause and is used to + consider only those groups satisfying the qualification given in the + HAVING clause. The expressions allowed in the HAVING clause must + involve aggregate functions. Every expression using only plain + attributes belongs to the WHERE clause. On the other hand every + expression involving an aggregate function must be put to the HAVING + clause. + + + Having + + + If we want only those suppliers selling more than one part we use the + query: + + SELECT S.SNO, S.SNAME, COUNT(SE.PNO) FROM SUPPLIER S, SELLS SE WHERE S.SNO = SE.SNO GROUP BY S.SNO, S.SNAME HAVING COUNT(SE.PNO) > 1; -\end{verbatim} -and get: -\begin{verbatim} + + + and get: + + SNO | SNAME | COUNT -----+-------+------- 1 | Smith | 2 3 | Adams | 2 4 | Blake | 3 -\end{verbatim} -\end{example} + + + + + -\subsubsection{Subqueries} -In the WHERE and HAVING clauses the use of subqueries (subselects) is -allowed in every place where a value is expected. In this case the -value must be derived by evaluating the subquery first. The usage of -subqueries extends the expressive power of SQL. -\begin{example} -If we want to know all parts having a greater price than the part -named 'Screw' we use the query: -\begin{verbatim} + + Subqueries + + + In the WHERE and HAVING clauses the use of subqueries (subselects) is + allowed in every place where a value is expected. In this case the + value must be derived by evaluating the subquery first. The usage of + subqueries extends the expressive power of + SQL. + + + Subselect + + + If we want to know all parts having a greater price than the part + named 'Screw' we use the query: + + SELECT * FROM PART WHERE PRICE > (SELECT PRICE FROM PART WHERE PNAME='Screw'); -\end{verbatim} -The result is: -\begin{verbatim} + + + + + The result is: + + PNO | PNAME | PRICE -----+---------+-------- 3 | Bolt | 15 4 | Cam | 25 -\end{verbatim} -When we look at the above query we can see -the keyword SELECT two times. The first one at the beginning of the -query - we will refer to it as outer SELECT - and the one in the WHERE -clause which begins a nested query - we will refer to it as inner -SELECT. For every tuple of the outer SELECT the inner SELECT has to be -evaluated. After every evaluation we know the price of the tuple named -'Screw' and we can check if the price of the actual tuple is -greater. -\\ \\ -\noindent If we want to know all suppliers that do not sell any part -(e.g. to be able to remove these suppliers from the database) we use: -\begin{verbatim} + + + + + When we look at the above query we can see + the keyword SELECT two times. The first one at the beginning of the + query - we will refer to it as outer SELECT - and the one in the WHERE + clause which begins a nested query - we will refer to it as inner + SELECT. For every tuple of the outer SELECT the inner SELECT has to be + evaluated. After every evaluation we know the price of the tuple named + 'Screw' and we can check if the price of the actual tuple is + greater. + + + + If we want to know all suppliers that do not sell any part + (e.g. to be able to remove these suppliers from the database) we use: + + SELECT * FROM SUPPLIER S WHERE NOT EXISTS (SELECT * FROM SELLS SE WHERE SE.SNO = S.SNO); -\end{verbatim} -In our example the result will be empty because every supplier sells -at least one part. Note that we use S.SNO from the outer SELECT within -the WHERE clause of the inner SELECT. As described above the subquery -is evaluated for every tuple from the outer query i.e. the value for -S.SNO is always taken from the actual tuple of the outer SELECT. -\end{example} + + -\subsubsection{Union, Intersect, Except} + + In our example the result will be empty because every supplier sells + at least one part. Note that we use S.SNO from the outer SELECT within + the WHERE clause of the inner SELECT. As described above the subquery + is evaluated for every tuple from the outer query i.e. the value for + S.SNO is always taken from the actual tuple of the outer SELECT. + + + + -These operations calculate the union, intersect and set theoretic -difference of the tuples derived by two subqueries: -\begin{example} -The following query is an example for UNION: -\begin{verbatim} + + Union, Intersect, Except + + + These operations calculate the union, intersect and set theoretic + difference of the tuples derived by two subqueries. + + + Union, Intersect, Except + + + The following query is an example for UNION: + + SELECT S.SNO, S.SNAME, S.CITY FROM SUPPLIER S WHERE S.SNAME = 'Jones' @@ -784,16 +1257,22 @@ The following query is an example for UNION: SELECT S.SNO, S.SNAME, S.CITY FROM SUPPLIER S WHERE S.SNAME = 'Adams'; -\end{verbatim} + + gives the result: -\begin{verbatim} + + SNO | SNAME | CITY -----+-------+-------- 2 | Jones | Paris 3 | Adams | Vienna -\end{verbatim} -Here an example for INTERSECT: -\begin{verbatim} + + + + + Here an example for INTERSECT: + + SELECT S.SNO, S.SNAME, S.CITY FROM SUPPLIER S WHERE S.SNO > 1 @@ -801,18 +1280,22 @@ Here an example for INTERSECT: SELECT S.SNO, S.SNAME, S.CITY FROM SUPPLIER S WHERE S.SNO > 2; -\end{verbatim} -gives the result: -\begin{verbatim} + + + gives the result: + + SNO | SNAME | CITY -----+-------+-------- 2 | Jones | Paris -\end{verbatim} The only tuple returned by both parts of the query is the one having $SNO=2$. -\pagebreak + + -\noindent Finally an example for EXCEPT: -\begin{verbatim} + + Finally an example for EXCEPT: + + SELECT S.SNO, S.SNAME, S.CITY FROM SUPPLIER S WHERE S.SNO > 1 @@ -820,298 +1303,503 @@ The only tuple returned by both parts of the query is the one having $SNO=2$. SELECT S.SNO, S.SNAME, S.CITY FROM SUPPLIER S WHERE S.SNO > 3; -\end{verbatim} -gives the result: -\begin{verbatim} + + + gives the result: + + SNO | SNAME | CITY -----+-------+-------- 2 | Jones | Paris 3 | Adams | Vienna -\end{verbatim} -\end{example} -% -\subsection{Data Definition} -\label{datadef} -% -There is a set of commands used for data definition included in the -SQL language. + + + + + + -\subsubsection{Create Table} -\label{create} -The most fundamental command for data definition is the -one that creates a new relation (a new table). The syntax of the -CREATE TABLE command is: -% -\begin{verbatim} - CREATE TABLE - ( - [, + + Data Definition + + + There is a set of commands used for data definition included in the + SQL language. + + + + Create Table + + + The most fundamental command for data definition is the + one that creates a new relation (a new table). The syntax of the + CREATE TABLE command is: + + + CREATE TABLE table_name + (name_of_attr_1 type_of_attr_1 + [, name_of_attr_2 type_of_attr_2 [, ...]]); -\end{verbatim} -% -\begin{example} -To create the tables defined in figure \ref{supplier} the -following SQL statements are used: -\begin{verbatim} + + + + Table Creation + + + To create the tables defined in figure + the + following SQL statements are used: + + CREATE TABLE SUPPLIER (SNO INTEGER, SNAME VARCHAR(20), CITY VARCHAR(20)); - + + + CREATE TABLE PART (PNO INTEGER, PNAME VARCHAR(20), PRICE DECIMAL(4 , 2)); -\end{verbatim} -\begin{verbatim} + + + CREATE TABLE SELLS (SNO INTEGER, PNO INTEGER); -\end{verbatim} -\end{example} + + + + + -% -\subsubsection{Data Types in SQL} -The following is a list of some data types that are supported by SQL: -\begin{itemize} -\item INTEGER: signed fullword binary integer (31 bits precision). -\item SMALLINT: signed halfword binary integer (15 bits precision). -\item DECIMAL ($p \lbrack,q\rbrack $): signed packed decimal number of $p$ -digits precision with assumed $q$ of them right to the decimal -point. $(15\ge p \ge q \ge 0)$. If $q$ is omitted it is assumed to be 0. -\item FLOAT: signed doubleword floating point number. -\item CHAR($n$): fixed length character string of length $n$. -\item VARCHAR($n$): varying length character string of maximum length -$n$. -\end{itemize} + + Data Types in <acronym>SQL</acronym> -\subsubsection{Create Index} -Indices are used to speed up access to a relation. If a relation $R$ -has an index on attribute $A$ then we can retrieve all tuples $t$ -having $t(A) = a$ in time roughly proportional to the number of such -tuples $t$ rather than in time proportional to the size of $R$. + + The following is a list of some data types that are supported by + SQL: -To create an index in SQL the CREATE INDEX command is used. The syntax -is: -\begin{verbatim} - CREATE INDEX - ON ( ); -\end{verbatim} -% -\begin{example} -To create an index named I on attribute SNAME of relation SUPPLIER -we use the following statement: -\begin{verbatim} + + + + INTEGER: signed fullword binary integer (31 bits precision). + + + + + + SMALLINT: signed halfword binary integer (15 bits precision). + + + + + + DECIMAL (p[,q]): + signed packed decimal number of + p + digits precision with assumed + q + of them right to the decimal point. + +(15 ≥ p ≥ qq ≥ 0). + + If q + is omitted it is assumed to be 0. + + + + + + FLOAT: signed doubleword floating point number. + + + + + + CHAR(n): + fixed length character string of length + n. + + + + + + VARCHAR(n): + varying length character string of maximum length + n. + + + + + + + + Create Index + + + Indices are used to speed up access to a relation. If a relation R + has an index on attribute A then we can + retrieve all tuples t + having + t(A) = a + in time roughly proportional to the number of such + tuples t + rather than in time proportional to the size of R. + + + + To create an index in SQL + the CREATE INDEX command is used. The syntax is: + + + CREATE INDEX index_name + ON table_name ( name_of_attribute ); + + + + + + Create Index + + + To create an index named I on attribute SNAME of relation SUPPLIER + we use the following statement: + + CREATE INDEX I ON SUPPLIER (SNAME); -\end{verbatim} -\end{example} -% -The created index is maintained automatically, i.e.\ whenever a new tuple -is inserted into the relation SUPPLIER the index I is adapted. Note -that the only changes a user can percept when an index is present -are an increased speed. + + -\subsubsection{Create View} -A view may be regarded as a {\it virtual table}, i.e.\ a table that -does not {\it physically} exist in the database but looks to the user -as if it did. By contrast, when we talk of a {\it base table} there is -really a physically stored counterpart of each row of the table -somewhere in the physical storage. + + The created index is maintained automatically, i.e. whenever a new tuple + is inserted into the relation SUPPLIER the index I is adapted. Note + that the only changes a user can percept when an index is present + are an increased speed. + + + + -Views do not have their own, physically separate, distinguishable -stored data. Instead, the system stores the {\it definition} of the -view (i.e.\ the rules about how to access physically stored {\it base -tables} in order to materialize the view) somewhere in the {\it system -catalogs} (see section \ref{catalogs} {\it System Catalogs}). For a -discussion on different techniques to implement views refer to section -\ref{view_impl} {\it Techniques To Implement Views}. + + Create View -In SQL the CREATE VIEW command is used to define a view. The syntax -is: -\begin{verbatim} - CREATE VIEW - AS -\end{verbatim} -where {\tt $<$select\_stmt$>$ } is a valid select statement as defined -in section \ref{select}. Note that the {\tt $<$select\_stmt$>$ } is -not executed when the view is created. It is just stored in the {\it -system catalogs} and is executed whenever a query against the view is -made. -\begin{example} Let the following view definition be given (we use -the tables from figure \ref{supplier} {\it The suppliers and parts -database} again): -\begin{verbatim} + + A view may be regarded as a virtual table, + i.e. a table that + does not physically exist in the database but looks to the user + as if it does. By contrast, when we talk of a base table there is + really a physically stored counterpart of each row of the table + somewhere in the physical storage. + + + + Views do not have their own, physically separate, distinguishable + stored data. Instead, the system stores the definition of the + view (i.e. the rules about how to access physically stored base + tables in order to materialize the view) somewhere in the system + catalogs (see section ). For a + discussion on different techniques to implement views refer to + + SIM98. + + + + In SQL the CREATE VIEW + command is used to define a view. The syntax + is: + + + CREATE VIEW view_name + AS select_stmt + + + where select_stmt + is a valid select statement as defined + in section . + Note that select_stmt is + not executed when the view is created. It is just stored in the + system catalogs + and is executed whenever a query against the view is made. + + + + Let the following view definition be given (we use + the tables from figure again): + + CREATE VIEW London_Suppliers AS SELECT S.SNAME, P.PNAME FROM SUPPLIER S, PART P, SELLS SE WHERE S.SNO = SE.SNO AND P.PNO = SE.PNO AND S.CITY = 'London'; -\end{verbatim} -Now we can use this {\it virtual relation} {\tt London\_Suppliers} as -if it were another base table: -\begin{verbatim} + + + + + Now we can use this virtual relation + London_Suppliers as + if it were another base table: + + SELECT * FROM London_Suppliers WHERE P.PNAME = 'Screw'; -\end{verbatim} -will return the following table: -\begin{verbatim} + + + which will return the following table: + + SNAME | PNAME -------+------- Smith | Screw -\end{verbatim} -To calculate this result the database system has to do a {\it hidden} -access to the base tables SUPPLIER, SELLS and PART first. It -does so by executing the query given in the view definition against -those base tables. After that the additional qualifications (given in the -query against the view) can be applied to obtain the resulting table. -\end{example} + + -\subsubsection{Drop Table, Drop Index, Drop View} -To destroy a table (including all tuples stored in that table) the -DROP TABLE command is used: -\begin{verbatim} - DROP TABLE ; -\end{verbatim} -% -\begin{example} -To destroy the SUPPLIER table use the following statement: -\begin{verbatim} + + To calculate this result the database system has to do a + hidden + access to the base tables SUPPLIER, SELLS and PART first. It + does so by executing the query given in the view definition against + those base tables. After that the additional qualifications (given in the + query against the view) can be applied to obtain the resulting + table. + + + + + Drop Table, Drop Index, Drop View + + + To destroy a table (including all tuples stored in that table) the + DROP TABLE command is used: + + + DROP TABLE table_name; + + + + + To destroy the SUPPLIER table use the following statement: + + DROP TABLE SUPPLIER; -\end{verbatim} -\end{example} -% -The DROP INDEX command is used to destroy an index: -\begin{verbatim} - DROP INDEX ; -\end{verbatim} -% -Finally to destroy a given view use the command DROP VIEW: -\begin{verbatim} - DROP VIEW ; -\end{verbatim} + + -\subsection{Data Manipulation} -% -\subsubsection{Insert Into} -Once a table is created (see section \ref{create}), it can be filled -with tuples using the command INSERT INTO. The syntax is: -\begin{verbatim} - INSERT INTO ( - [, [,...]]) - VALUES ( - [, [, ...]]); -\end{verbatim} -% -\begin{example} -To insert the first tuple into the relation SUPPLIER of figure -\ref{supplier} {\it The suppliers and parts database} we use the -following statement: -\begin{verbatim} + + The DROP INDEX command is used to destroy an index: + + + DROP INDEX index_name; + + + + + Finally to destroy a given view use the command DROP VIEW: + + + DROP VIEW view_name; + + + + + + + Data Manipulation + + + Insert Into + + + Once a table is created (see + ), it can be filled + with tuples using the command INSERT INTO. + The syntax is: + + + INSERT INTO table_name (name_of_attr_1 + [, name_of_attr_2 [,...]]) + VALUES (val_attr_1 + [, val_attr_2 [, ...]]); + + + + + To insert the first tuple into the relation SUPPLIER of figure + we use the + following statement: + + INSERT INTO SUPPLIER (SNO, SNAME, CITY) VALUES (1, 'Smith', 'London'); -\end{verbatim} -% -To insert the first tuple into the relation SELLS we use: -\begin{verbatim} + + + + + To insert the first tuple into the relation SELLS we use: + + INSERT INTO SELLS (SNO, PNO) VALUES (1, 1); -\end{verbatim} -\end{example} + + + -\subsubsection{Update} -To change one or more attribute values of tuples in a relation the -UPDATE command is used. The syntax is: -\begin{verbatim} - UPDATE - SET = - [, ... [, = ]] - WHERE ; -\end{verbatim} -% -\begin{example} -To change the value of attribute PRICE of the part 'Screw' in the -relation PART we use: -\begin{verbatim} + + Update + + + To change one or more attribute values of tuples in a relation the + UPDATE command is used. The syntax is: + + + UPDATE table_name + SET name_of_attr_1 = value_1 + [, ... [, name_of_attr_k = value_k]] + WHERE condition; + + + + + To change the value of attribute PRICE of the part 'Screw' in the + relation PART we use: + + UPDATE PART SET PRICE = 15 WHERE PNAME = 'Screw'; -\end{verbatim} -The new value of attribute PRICE of the tuple whose name is 'Screw' is -now 15. -\end{example} + + -\subsubsection{Delete} -To delete a tuple from a particular table use the command DELETE -FROM. The syntax is: -\begin{verbatim} - DELETE FROM - WHERE ; -\end{verbatim} -\begin{example} -To delete the supplier called 'Smith' of the table SUPPLIER the -following statement is used: -\begin{verbatim} + + The new value of attribute PRICE of the tuple whose name is 'Screw' is + now 15. + + + + + Delete + + + To delete a tuple from a particular table use the command DELETE + FROM. The syntax is: + + + DELETE FROM table_name + WHERE condition; + + + + + To delete the supplier called 'Smith' of the table SUPPLIER the + following statement is used: + + DELETE FROM SUPPLIER WHERE SNAME = 'Smith'; -\end{verbatim} -\end{example} -% -\subsection{System Catalogs} -\label{catalogs} -In every SQL database system {\it system catalogs} are used to keep -track of which tables, views indexes etc. are defined in the -database. These system catalogs can be queried as if they were normal -relations. For example there is one catalog used for the definition of -views. This catalog stores the query from the view definition. Whenever -a query against a view is made, the system first gets the {\it -view-definition-query} out of the catalog and materializes the view -before proceeding with the user query (see section \ref{view_impl} -{\it Techniques To Implement Views} for a more detailed -description). For more information about {\it system catalogs} refer to -\cite{date}. + + + + -\subsection{Embedded SQL} + + System Catalogs -In this section we will sketch how SQL can be embedded into a host -language (e.g.\ C). There are two main reasons why we want to use SQL -from a host language: -% -\begin{itemize} -\item There are queries that cannot be formulated using pure SQL -(i.e. recursive queries). To be able to perform such queries we need a -host language with a greater expressive power than SQL. -\item We simply want to access a database from some application that -is written in the host language (e.g.\ a ticket reservation system -with a graphical user interface is written in C and the information -about which tickets are still left is stored in a database that can be -accessed using embedded SQL). -\end{itemize} -% -A program using embedded SQL in a host language consists of statements -of the host language and of embedded SQL (ESQL) statements. Every ESQL -statement begins with the keywords EXEC SQL. The ESQL statements are -transformed to statements of the host language by a {\it precompiler} -(mostly calls to library routines that perform the various SQL -commands). + + In every SQL database system + system catalogs are used to keep + track of which tables, views indexes etc. are defined in the + database. These system catalogs can be queried as if they were normal + relations. For example there is one catalog used for the definition of + views. This catalog stores the query from the view definition. Whenever + a query against a view is made, the system first gets the + view definition query out of the catalog + and materializes the view + before proceeding with the user query (see + + SIM98 + for a more detailed + description). For more information about system catalogs refer to + DATE. + + -When we look at the examples throughout section \ref{select} we -realize that the result of the queries is very often a set of -tuples. Most host languages are not designed to operate on sets so we -need a mechanism to access every single tuple of the set of tuples -returned by a SELECT statement. This mechanism can be provided by -declaring a {\it cursor}. After that we can use the FETCH command to -retrieve a tuple and set the cursor to the next tuple. -\\ \\ -For a detailed discussion on embedded SQL refer to \cite{date}, -\cite{date86} or \cite{ullman}. + + Embedded <acronym>SQL</acronym> + + + In this section we will sketch how SQL can be + embedded into a host language (e.g. C). + There are two main reasons why we want to use SQL + from a host language: + + + + + There are queries that cannot be formulated using pure SQL + (i.e. recursive queries). To be able to perform such queries we need a + host language with a greater expressive power than + SQL. + + + + + + We simply want to access a database from some application that + is written in the host language (e.g. a ticket reservation system + with a graphical user interface is written in C and the information + about which tickets are still left is stored in a database that can be + accessed using embedded SQL). + + + + + + + A program using embedded SQL in a host language consists of statements + of the host language and of embedded SQL (ESQL) statements. Every ESQL + statement begins with the keywords EXEC SQL. The ESQL statements are + transformed to statements of the host language by a precompiler + (which usually inserts + calls to library routines that perform the various SQL + commands). + + + + When we look at the examples throughout section + we + realize that the result of the queries is very often a set of + tuples. Most host languages are not designed to operate on sets so we + need a mechanism to access every single tuple of the set of tuples + returned by a SELECT statement. This mechanism can be provided by + declaring a cursor. + After that we can use the FETCH command to + retrieve a tuple and set the cursor to the next tuple. + + + + For a detailed discussion on embedded SQL + refer to date, + date86 or ullman. + + + +