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 <chapter id="tutorial-sql">
  <title>The <acronym>SQL</acronym> Language</title>

  <sect1 id="tutorial-sql-intro">
   <title>Introduction</title>

   <para>
    This chapter provides an overview of how to use
    <acronym>SQL</acronym> to perform simple operations.  This
    tutorial is only intended to give you an introduction and is in no
    way a complete tutorial on <acronym>SQL</acronym>.  Numerous books
    have been written on <acronym>SQL92</acronym>, including <xref
    linkend="MELT93" endterm="MELT93"> and <xref linkend="DATE97"
    endterm="DATE97">.  You should be aware that some language
    features are extensions to the standard.
   </para>

   <para>
    In the examples that follow, we assume that you have created a
    database named <quote>mydb</quote>, as described in the previous
    chapter, and have started <application>psql</application>.
   </para>

   <para>
    Examples in this manual can also be found in source distribution
    in the directory <filename>src/tutorial/</filename>.  Refer to the
    <filename>README</filename> file in that directory for how to use
    them.  To start the tutorial, do the following:

<screen>
<prompt>$</prompt> <userinput>cd <replaceable>....</replaceable>/src/tutorial</userinput>
<prompt>$</prompt> <userinput>psql -s mydb</userinput>
<computeroutput>
...
</computeroutput>

<prompt>mydb=&gt;</prompt> <userinput>\i basics.sql</userinput>
</screen>

    The <literal>\i</literal> command reads in commands from the
    specified files. The <literal>-s</literal> option puts you in
    single step mode which pauses before sending a query to the
    server.  The commands used in this section are in the file
    <filename>basics.sql</filename>.
   </para>
  </sect1>


  <sect1 id="tutorial-concepts">
   <title>Concepts</title>

   <para>
    <indexterm><primary>relational database</primary></indexterm>
    <indexterm><primary>hierarchical database</primary></indexterm>
    <indexterm><primary>object-oriented database</primary></indexterm>
    <indexterm><primary>relation</primary></indexterm>
    <indexterm><primary>table</primary></indexterm>

    <productname>PostgreSQL</productname> is a <firstterm>relational
    database management system</firstterm> (<acronym>RDBMS</acronym>).
    That means it is a system for managing data stored in
    <firstterm>relations</firstterm>.  Relation is essentially a
    mathematical term for <firstterm>table</firstterm>.  The notion of
    storing data in tables is so commonplace today that it might
    seem inherently obvious, but there are a number of other ways of
    organizing databases.  Files and directories on Unix-like
    operating systems form an example of a hierarchical database.  A
    more modern development is the object-oriented database.
   </para>

   <para>
    <indexterm><primary>row</primary></indexterm>
    <indexterm><primary>column</primary></indexterm>

    Each table is a named collection of <firstterm>rows</firstterm>.
    Each row has the same set of named <firstterm>columns</firstterm>,
    and each column is of a specific data type.  Whereas columns have
    a fixed order in each row, it is important to remember that SQL
    does not guarantee the order of the rows within the table in any
    way (unless they are explicitly sorted).
   </para>

   <para>
    <indexterm><primary>cluster</primary></indexterm>

    Tables are grouped into databases, and a collection of databases
    managed by a single <productname>PostgreSQL</productname> server
    instance constitutes a database <firstterm>cluster</firstterm>.
   </para>
  </sect1>


  <sect1 id="tutorial-table">
   <title>Creating a New Table</title>

   <indexterm zone="tutorial-table">
    <primary>CREATE TABLE</primary>
   </indexterm>

   <para>
    You  can  create  a  new  table by specifying the table
    name, along with all column names and their types:

<programlisting>
CREATE TABLE weather (
    city            varchar(80),
    temp_lo         int,           -- low temperature
    temp_hi         int,           -- high temperature
    prcp            real,          -- precipitation
    date            date
);
</programlisting>

    You can enter this into <command>psql</command> with the line
    breaks.  <command>psql</command> will recognize that the command
    is not terminated until the semicolon.
   </para>

   <para>
    White space (i.e., spaces, tabs, and newlines) may be used freely
    in SQL commands.  That means you can type the command aligned
    differently than above, or even all on one line.  Two dashes
    (<quote><literal>--</literal></quote>) introduce comments.
    Whatever follows them is ignored up to the end of the line.  SQL
    is also case insensitive about key words and identifiers, except
    when identifiers are double-quoted to preserve the case (not done
    above).
   </para>

   <para>
    <type>varchar(80)</type> specifies a data type that can store
    arbitrary character strings up to 80 characters in length.
    <type>int</type> is the normal integer type.  <type>real</type> is
    a type for storing single precision floating point numbers.
    <type>date</type> should be self-explanatory.  (Yes, the column of
    type <type>date</type> is also named <literal>date</literal>.
    This may be convenient or confusing -- you choose.)
   </para>

   <para>
    <productname>PostgreSQL</productname> supports the usual
    <acronym>SQL</acronym> types <type>int</type>,
    <type>smallint</type>, <type>real</type>, <type>double
    precision</type>, <type>char(<replaceable>N</>)</type>,
    <type>varchar(<replaceable>N</>)</type>, <type>date</type>,
    <type>time</type>, <type>timestamp</type>, and
    <type>interval</type> as well as other types of general utility
    and a rich set of geometric types.
    <productname>PostgreSQL</productname> can be customized with an
    arbitrary number of user-defined data types.  Consequently, type
    names are not syntactical keywords, except where required to
    support special cases in the <acronym>SQL</acronym> standard.
   </para>

   <para>
    The second example will store cities and their associated
    geographical location:
<programlisting>
CREATE TABLE cities (
    name            varchar(80),
    location        point
);
</programlisting>
    The <type>point</type> type is such a
    <productname>PostgreSQL</productname>-specific data type.
   </para>

   <para>
    <indexterm>
     <primary>DROP TABLE</primary>
    </indexterm>

    Finally, it should be mentioned that if you don't need a table any
    longer or want to recreate it differently you can remove it using
    the following command:
<synopsis>
DROP TABLE <replaceable>tablename</replaceable>;
</synopsis>
   </para>
  </sect1>


  <sect1 id="tutorial-populate">
   <title>Populating a Table With Rows</title>

   <indexterm zone="tutorial-populate">
    <primary>INSERT</primary>
   </indexterm>

   <para>
    The <command>INSERT</command> statement is used to populate a table  with
    rows:

<programlisting>
INSERT INTO weather VALUES ('San Francisco', 46, 50, 0.25, '1994-11-27');
</programlisting>

    Note that all data types use rather obvious input formats.  The
    <type>date</type> column is actually quite flexible in what it
    accepts, but for this tutorial we will stick to the unambiguous
    format shown here.
   </para>

   <para>
    The <type>point</type> type requires a coordinate pair as input,
    as shown here:
<programlisting>
INSERT INTO cities  VALUES ('San Francisco', '(-194.0, 53.0)');
</programlisting>
   </para>

   <para>
    The syntax used so far requires you to remember the order of the
    columns.  An alternative syntax allows you to list the columns
    explicitly:
<programlisting>
INSERT INTO weather (city, temp_lo, temp_hi, prcp, date)
    VALUES ('San Francisco', 43, 57, 0.0, '1994-11-29');
</programlisting>
    You can also list the columns in a different order if you wish or
    even omit some columns, e.g., unknown precipitation:
<programlisting>
INSERT INTO weather (date, city, temp_hi, temp_lo)
    VALUES ('1994-11-29', 'Hayward', 54, 37);
</programlisting>
    Many developers consider explicitly listing the columns better
    style than relying on the order implicitly.
   </para>

   <para>
    Please enter all the commands shown above so you have some data to
    work with in the following sections.
   </para>

   <para>
    <indexterm>
     <primary>COPY</primary>
    </indexterm>

    You could also have used <command>COPY</command> to load large
    amounts of data from flat text files.  This is usually faster
    because the <command>COPY</command> is optimized for this
    application while allowing less flexibility than
    <command>INSERT</command>.  An example would be:

<programlisting>
COPY weather FROM '/home/user/weather.txt';
</programlisting>

    where the path name for the source file must be available to the
    backend server machine, not the client, since the backend server
    reads the file directly.  You can read more about the
    <command>COPY</command> command in the <citetitle>Reference
    Manual</citetitle>.
   </para>
  </sect1>


  <sect1 id="tutorial-select">
   <title>Querying a Table</title>

   <para>
    <indexterm><primary>query</primary></indexterm>
    <indexterm><primary>SELECT</primary></indexterm>

    To retrieve data from a table it is
    <firstterm>queried</firstterm>.  An <acronym>SQL</acronym>
    <command>SELECT</command> statement is used to do this.  The
    statement is divided into a select list (the part that lists the
    columns to be returned), a table list (the part that lists the
    tables from which to retrieve the data), and an optional
    qualification (the part that specifies any restrictions).  For
    example, to retrieve all the rows of
    <classname>weather</classname>, type:
<programlisting>
SELECT * FROM weather;
</programlisting>
    (where <literal>*</literal> means <quote>all columns</quote>) and
    the output should be:
<screen>
     city      | temp_lo | temp_hi | prcp |    date
---------------+---------+---------+------+------------
 San Francisco |      46 |      50 | 0.25 | 1994-11-27
 San Francisco |      43 |      57 |    0 | 1994-11-29
 Hayward       |      37 |      54 |      | 1994-11-29
(3 rows)
</screen>
   </para>

   <para>
    You may specify any arbitrary expressions in the target list.  For 
    example, you can do:
<programlisting>
SELECT city, (temp_hi+temp_lo)/2 AS temp_avg, date FROM weather;
</programlisting>
    This should give:
<screen>
     city      | temp_avg |    date
---------------+----------+------------
 San Francisco |       48 | 1994-11-27
 San Francisco |       50 | 1994-11-29
 Hayward       |       45 | 1994-11-29
(3 rows)
</screen>
    Notice how the <literal>AS</literal> clause is used to relabel the
    output column.  (It is optional.)
   </para>

   <para>
    Arbitrary Boolean operators (<literal>AND</literal>,
    <literal>OR</literal>, and <literal>NOT</literal>) are allowed in
    the qualification of a query.  For example, the following
    retrieves the weather of San Francisco on rainy days:

<programlisting>
SELECT * FROM weather
    WHERE city = 'San Francisco'
    AND prcp > 0.0;
</programlisting>
    Result:
<screen>
     city      | temp_lo | temp_hi | prcp |    date
---------------+---------+---------+------+------------
 San Francisco |      46 |      50 | 0.25 | 1994-11-27
(1 row)
</screen>
   </para>

   <para>
    <indexterm><primary>ORDER BY</primary></indexterm>
    <indexterm><primary>DISTINCT</primary></indexterm>
    <indexterm><primary>duplicate</primary></indexterm>

    As a final note, you can request that the results of a select can
    be returned in sorted order or with duplicate rows removed.  (Just
    to make sure the following won't confuse you,
    <literal>DISTINCT</literal> and <literal>ORDER BY</literal> can be
    used separately.)

<programlisting>
SELECT DISTINCT city
    FROM weather
    ORDER BY city;
</programlisting>

<screen>
     city
---------------
 Hayward
 San Francisco
(2 rows)
</screen>
   </para>
  </sect1>


  <sect1 id="tutorial-join">
   <title>Joins Between Tables</title>

   <indexterm zone="tutorial-join">
    <primary>join</primary>
   </indexterm>

   <para>
    Thus far, our queries have only accessed one table at a time.
    Queries can access multiple tables at once, or access the same
    table in such a way that multiple rows of the table are being
    processed at the same time.  A query that accesses multiple rows
    of the same or different tables at one time is called a
    <firstterm>join</firstterm> query.  As an example, say you wish to
    list all the weather records together with the location of the
    associated city.  In effect, we need to compare the city column of
    each row of the weather table with the name column of all rows in
    the cities table.
    <note>
     <para>
      This  is only a conceptual model.  The actual join may
      be performed in a more efficient manner, but this is invisible
      to the user.
     </para>
    </note>
    This would be accomplished by the following query:

<programlisting>
SELECT *
    FROM weather, cities
    WHERE city = name;
</programlisting>

<screen>
     city      | temp_lo | temp_hi | prcp |    date    |     name      | location
---------------+---------+---------+------+------------+---------------+-----------
 San Francisco |      46 |      50 | 0.25 | 1994-11-27 | San Francisco | (-194,53)
 San Francisco |      43 |      57 |    0 | 1994-11-29 | San Francisco | (-194,53)
(2 rows)
</screen>

   </para>

   <para>
    Observe two things about the result set:
    <itemizedlist>
     <listitem>
      <para>
       There is no result row for the city of Hayward.  This is
       because there is no matching entry in the
       <classname>cities</classname> table for Hayward, so the join
       cannot process the rows in the weather table.  We will see
       shortly how this can be fixed.
      </para>
     </listitem>

     <listitem>
      <para>
       There are two columns containing the city name.  This is
       correct because the lists of columns of the
       <classname>weather</classname> and the
       <classname>cities</classname> tables are concatenated.  In
       practice this is undesirable, though, so you will probably want
       to list the output columns explicitly rather than using
       <literal>*</literal>:
<programlisting>
SELECT city, temp_lo, temp_hi, prcp, date, location
    FROM weather, cities
    WHERE city = name;
</programlisting>
      </para>
     </listitem>
    </itemizedlist>
   </para>

   <formalpara>
    <title>Exercise:</title>

    <para>
     Attempt to find out the semantics of this query when the
     <literal>WHERE</literal> clause is omitted.
    </para>
   </formalpara>

   <para>
    Since the columns all had different names, the parser
    automatically found out which table they belong to, but it is good
    style to fully qualify column names in join queries:

<programlisting>
SELECT weather.city, weather.temp_lo, weather.temp_hi, weather.prcp, weather.date, cities.location
    FROM weather, cities
    WHERE cities.name = weather.city;
</programlisting>
   </para>

   <para>
    Join queries of the kind seen thus far can also be written in this
    alternative form:

<programlisting>
SELECT *
    FROM weather INNER JOIN cities ON (weather.city = cities.name);
</programlisting>

    This syntax is not as commonly used as the one above, but we show
    it here to help you understand the following topics.
   </para>

   <para>
    <indexterm><primary>join</primary><secondary>outer</secondary></indexterm>

    Now we will figure out how we can get the Hayward records back in.
    What we want the query to do is to scan the
    <classname>weather</classname> table and for each row to find the
    matching <classname>cities</classname> row.  If no matching row is
    found we want some <quote>empty values</quote> to be substituted
    for the <classname>cities</classname> table's columns.  This kind
    of query is called an <firstterm>outer join</firstterm>.  (The
    joins we have seen to far are inner joins.)  The command looks
    like this:

<programlisting>
SELECT *
    FROM weather LEFT OUTER JOIN cities ON (weather.city = cities.name);

     city      | temp_lo | temp_hi | prcp |    date    |     name      | location
---------------+---------+---------+------+------------+---------------+-----------
 Hayward       |      37 |      54 |      | 1994-11-29 |               |
 San Francisco |      46 |      50 | 0.25 | 1994-11-27 | San Francisco | (-194,53)
 San Francisco |      43 |      57 |    0 | 1994-11-29 | San Francisco | (-194,53)
(3 rows)
</programlisting>

    In particular, this query is a <firstterm>left outer
    join</firstterm> because the table mentioned on the left of the
    join operator will have each of its rows in the output at least
    once, whereas the table on the right will only have those rows
    output that match some row of the left table, and will have empty
    values substituted appropriately.
   </para>

   <formalpara>
    <title>Exercise:</title>

    <para>
     There are also right outer joins and full outer joins.  Try to
     find out what those do.
    </para>
   </formalpara>

   <para>
    <indexterm><primary>join</primary><secondary>self</secondary></indexterm>
    <indexterm><primary>alias</primary><secondary>for table name in query</secondary></indexterm>

    We can also join a table against itself.  This is called a
    <firstterm>self join</firstterm>.  As an example, suppose we wish
    to find all the weather records that are in the temperature range
    of other weather records.  So we need to compare the
    <structfield>temp_lo</> and <structfield>temp_hi</> columns of
    each <classname>weather</classname> row to the
    <structfield>temp_lo</structfield> and
    <structfield>temp_hi</structfield> columns of all other
    <classname>weather</classname> rows.  We can do this with the
    following query:

<programlisting>
SELECT W1.city, W1.temp_lo AS low, W1.temp_hi AS high,
    W2.city, W2.temp_lo AS low, W2.temp_hi AS high
    FROM weather W1, weather W2
    WHERE W1.temp_lo < W2.temp_lo
    AND W1.temp_hi > W2.temp_hi;

     city      | low | high |     city      | low | high
---------------+-----+------+---------------+-----+------
 San Francisco |  43 |   57 | San Francisco |  46 |   50
 Hayward       |  37 |   54 | San Francisco |  46 |   50
(2 rows)
</programlisting>     

    Here we have relabeled the weather table as <literal>W1</> and
    <literal>W2</> to be able to distinguish the left and right side
    of the join.  You can also use these kinds of aliases in other
    queries to save some typing, e.g.:
<programlisting>
SELECT *
    FROM weather w, cities c
    WHERE w.city = c.name;
</programlisting>
    You will encounter this style of abbreviating quite frequently.
   </para>
  </sect1>


  <sect1 id="tutorial-agg">
   <title>Aggregate Functions</title>

   <indexterm zone="tutorial-agg">
    <primary>aggregate</primary>
   </indexterm>

   <para>
    <indexterm><primary>average</primary></indexterm>
    <indexterm><primary>count</primary></indexterm>
    <indexterm><primary>max</primary></indexterm>
    <indexterm><primary>min</primary></indexterm>
    <indexterm><primary>sum</primary></indexterm>

    Like  most  other relational database products, 
    <productname>PostgreSQL</productname> supports
    aggregate functions.
    An aggregate function computes a single result from multiple input rows.
    For example, there are aggregates to compute the
    <function>count</function>, <function>sum</function>,
    <function>avg</function> (average), <function>max</function> (maximum) and
    <function>min</function> (minimum) over a set of rows.
   </para>

   <para>
    As an example, we can find the highest low-temperature reading anywhere
    with

<programlisting>
SELECT max(temp_lo) FROM weather;
</programlisting>

<screen>
 max
-----
  46
(1 row)
</screen>
   </para>

   <para>
    <indexterm><primary>subquery</primary></indexterm>

    If we want to know what city (or cities) that reading occurred in,
    we might try

<programlisting>
SELECT city FROM weather WHERE temp_lo = max(temp_lo);     <lineannotation>WRONG</lineannotation>
</programlisting>

    but this will not work since the aggregate
    <function>max</function> cannot be used in the
    <literal>WHERE</literal> clause.  However, as is often the case
    the query can be restated to accomplish the intended result; here
    by using a <firstterm>subquery</firstterm>:

<programlisting>
SELECT city FROM weather
    WHERE temp_lo = (SELECT max(temp_lo) FROM weather);
</programlisting>

<screen>
     city
---------------
 San Francisco
(1 row)
</screen>

    This is OK because the sub-select is an independent computation
    that computes its own aggregate separately from what is happening
    in the outer select.
   </para>

   <para>
    <indexterm><primary>GROUP BY</primary></indexterm>
    <indexterm><primary>HAVING</primary></indexterm>

    Aggregates are also very useful in combination with <literal>GROUP
    BY</literal> clauses.  For example, we can get the maximum low
    temperature observed in each city with

<programlisting>
SELECT city, max(temp_lo)
    FROM weather
    GROUP BY city;
</programlisting>

<screen>
     city      | max
---------------+-----
 Hayward       |  37
 San Francisco |  46
(2 rows)
</screen>

    which gives us one output row per city.  We can filter these grouped
    rows using <literal>HAVING</literal>:

<programlisting>
SELECT city, max(temp_lo)
    FROM weather
    GROUP BY city
    HAVING max(temp_lo) < 40;
</programlisting>

<screen>
  city   | max
---------+-----
 Hayward |  37
(1 row)
</screen>

    which gives us the same results for only the cities that have some
    below-forty readings.  Finally, if we only care about cities whose
    names begin with <quote><literal>S</literal></quote>, we might do

<programlisting>
SELECT city, max(temp_lo)
    FROM weather
    WHERE city LIKE 'S%'
    GROUP BY city
    HAVING max(temp_lo) < 40;
</programlisting>
   </para>

   <para>
    It is important to understand the interaction between aggregates and
    SQL's <literal>WHERE</literal> and <literal>HAVING</literal> clauses.
    The fundamental difference between <literal>WHERE</literal> and
    <literal>HAVING</literal> is this: <literal>WHERE</literal> selects
    input rows before groups and aggregates are computed (thus, it controls
    which rows go into the aggregate computation), whereas
    <literal>HAVING</literal> selects group rows after groups and
    aggregates are computed.  Thus, the
    <literal>WHERE</literal> clause must not contain aggregate functions;
    it makes no sense to try to use an aggregate to determine which rows
    will be inputs to the aggregates.  On the other hand,
    <literal>HAVING</literal> clauses always contain aggregate functions.
    (Strictly speaking, you are allowed to write a <literal>HAVING</literal>
    clause that doesn't use aggregates, but it's wasteful; the same condition
    could be used more efficiently at the <literal>WHERE</literal> stage.)
   </para>

   <para>
    Note that we can apply the city name restriction in
    <literal>WHERE</literal>, since it needs no aggregate.  This is
    more efficient than adding the restriction to <literal>HAVING</literal>,
    because we avoid doing the grouping and aggregate calculations
    for all rows that fail the <literal>WHERE</literal> check.
   </para>
  </sect1>


  <sect1 id="tutorial-update">
   <title>Updates</title>

   <indexterm zone="tutorial-update">
    <primary>UPDATE</primary>
   </indexterm>

   <para>
    You can update existing rows using the
    <command>UPDATE</command> command. 
    Suppose you discover the temperature readings are
    all  off  by 2 degrees as of November 28, you may update the
    data as follow:

<programlisting>
UPDATE weather
    SET temp_hi = temp_hi - 2,  temp_lo = temp_lo - 2
    WHERE date > '1994-11-28';
</programlisting>
   </para>

   <para>
    Look at the new state of the data:
<programlisting>
SELECT * FROM weather;

     city      | temp_lo | temp_hi | prcp |    date
---------------+---------+---------+------+------------
 San Francisco |      46 |      50 | 0.25 | 1994-11-27
 San Francisco |      41 |      55 |    0 | 1994-11-29
 Hayward       |      35 |      52 |      | 1994-11-29
(3 rows)
</programlisting>
   </para>
  </sect1>

  <sect1 id="tutorial-delete">
   <title>Deletions</title>

   <indexterm zone="tutorial-delete">
    <primary>DELETE</primary>
   </indexterm>

   <para>
    Suppose you are no longer interested in the weather of Hayward,
    then you can do the following to delete those rows from the table.
    Deletions are performed using the <command>DELETE</command>
    command:
<programlisting>
DELETE FROM weather WHERE city = 'Hayward';
</programlisting>

    All weather recording belonging to Hayward are removed.

<programlisting>
SELECT * FROM weather;
</programlisting>

<screen>
     city      | temp_lo | temp_hi | prcp |    date
---------------+---------+---------+------+------------
 San Francisco |      46 |      50 | 0.25 | 1994-11-27
 San Francisco |      41 |      55 |    0 | 1994-11-29
(2 rows)
</screen>
   </para>

   <para>
    One should be wary of queries of the form
<synopsis>
DELETE FROM <replaceable>tablename</replaceable>;
</synopsis>

    Without a qualification, <command>DELETE</command> will simply
    remove  all  rows from the given table, leaving it
    empty.  The system will not request confirmation before
    doing this.
   </para>
  </sect1>

 </chapter>

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