by Manuel Soriano <manu(at)europa3.com> About the author: Manuel is a software consultant and his passion is Linux. He did already worked with computers when one single computer filled a whole room and had 32K Ram. Translated to English by: Dallas L. Gale <unknown(at)unknown.org> Content: Introduction Creating a table Modifying a table Inserting data into a table Selecting data Details of WHERE UPDATE command DELETE command References

SQL Tutorial Part II

Abstract:

In part II of the tutorial we review several basic statements of the SQL language.

Introduction

This is the second part of the SQL course. In this part, we will focus on various SQL commands from the creation of a table, its modification, and/or deletion.

We will focus, above all, on the SELECT command, which is, in my judgment, the most important of all.

I hope that this second part will be enjoyable and instructive for you.

Creating a table

Like we have seen in the first installment, to create a table, the CREATE command with the TABLE qualifier is used. In effect, the CREATE command serves to create:

• users: CREATE USER
• tables: CREATE TABLE
• indexes: CREATE INDEX
• views: CREATE VIEW

The CREATE command indicates to the manager that something is going to be created. Later we will cover what and how.

What we are interested in now is the creation of a table:

Syntax

CREATE TABLE name ( column type [DEFAULT value] [NOT NULL], ...
      [INHERITS (inherits, ...)]
      [CONSTRAINT constraints CHECK (test), CHECK (test)] );

CREATE TABLE countries (
         cod_country integer NOT NULL,
         name varchar(30))
   CONSTRAINT cod_raro CHECK (cod_country > 0 AND cod_country < 154);

With this example we have created a table of countries. Each time that we insert a new row, these conditions will be meet:

• The country code won't be NULL. Upon trying to put a NULL code, the manager will return the error:
  

  ExecAppend: Fail to add null value in not null attribute cod_country
  

• The country code will be greater then 0 and less then 154. Upon trying to insert an erroneous country code, the manager will give us an error:
  

  ExecAppend: rejected due to CHECK constraint cod_raro
  

Note

What does NULL mean? In SQL there exist two states, data and no data. In effect, we can be interested that a field of rows doesn't have data, like zero (0) as well as the spaces are data. SQL introduces the concept of NULL and works with it. A practical example:

I have a table of bills, with the following fields: customer, value, date_issued, date_paid

When I create the row, I will insert the data: customer, value, date_issued

I will leave the date paid null; in this way I will know which bills need to be paid with the following command:

SELECT * FROM bills WHERE date_paid IS NULL;

One can claim that a zero (0) in the field date_paid would do the same thing. It's true, except that zero (0) is not a date, and it prevents creating date_paid of date type and applying appropriate date functions.

Examples of creating with NULL:

insert into countries values (15, NULL);

insert into countries (cod_country) values (27);

The absence of the "name" field implies that this will receive a NULL value.

Modifying a table

In PostgreSQL, modification only deals with adding new columns.

ALTER TABLE table ADD name type;

Where:

Inserting data into a table

Now we will insert data into our table:

INSERT INTO table [(column, column, ...)] VALUES (value-1, value-2,
...)

INSERT INTO table [(column, column, ...)] SELECT ....

As we have seen, there are two forms of inserting data into a table, either line by line or the result of a sub-select that can return one or more rows.

When we insert lines into a table, we will ALWAYS put data in all the columns including those that we don't mention, these are created with NULL values.

If, in the command, we don't specify which columns we are going to fill, it is understood that we are going to give data to all, example:

INSERT INTO countries VALUES (34, 'Spain');

INSERT INTO countries VALUES (34);

INSERT INTO countries (cod_country) VALUES (34);

I recommend that a command embedded in "C" programs or in database functions ALWAYS specify the columns that we are going to touch, in effect, if we add a new column to the table (ALTER TABLE), the next insert an error will occur, Example:

This will give a parser error, given that the population data is missing

Note

PostgreSQL, doesn't generate an error. It creates the line with the "population" field NULL. This is only a particularity of PostgreSQL, any other SQL manager would give an error.

We still have another type of INSERT, which is fed from a sub-select.

This type of insert is used very often to create temporary tables or tables to carry out a concrete task of speculative calculations.

The part replaced is that which touches the data itself, this comes from the SELECT instructions that were carried out previously and the inserting of the data. The instruction SELECT can return one or more rows, this instruction SELECT has the same restrictions of the same SELECT.

Selecting data

I wanted to arrive at this point! :-))

We have covered required SQL commands, the SQL language without SELECT would be like beans without sausage.

The SELECT command allows us to access data, but with the reservation that searches, unions of tables, functions with the data, and with the search rules can be carried out.

An example:

select * from countries;

SELECT a.name, SUM(population)
    FROM countries a, states b, counties c
    WHERE b.cod_country = a.cod_country
        AND (c.cod_country = b.cod_country
        AND c.state_code = b.state_code)
        AND population IS NOT NULL
        GROUP BY a.name
        ORDER BY sum ASC;

Let me explain, I requested the populations of all of the countries ordered by the population in an ascending order.

For this I have added a new column (population) to the counties table.

create table counties (cod_country int,
                        state_code int,
                        county_code int,
                        county_name varchar(60),
                        population int);
insert into counties values (1, 1, 1, 'Country 1, State 1, County 1',
5435);
insert into counties values (2, 1, 1, 'Country 2, State 1, County 1',
7832);
insert into counties values (3, 1, 1, 'Country 3, State 1, County 1',
4129);
insert into counties values (1, 2, 1, 'Country 1, State 2, County 1',
76529);
insert into counties values (2, 2, 1, 'Country 2, State 2, County 1',
9782);
insert into counties values (3, 2, 1, 'Country 3, State 2, County 1',
852);
insert into counties values (1, 3, 1, 'Country 1, State 3, County 1',
3433);
insert into counties values (2, 3, 1, 'Country 2, State 3, County 1',
7622);
insert into counties values (3, 3, 1, 'Country 3, State 3, County 1',
2798);
insert into counties values (1, 1, 2, 'Country 1, State 1, County 2',
7789);
insert into counties values (2, 1, 2, 'Country 2, State 1, County 2',
76511);
insert into counties values (3, 1, 2, 'Country 3, State 1, County 2',
98);
insert into counties values (1, 2, 2, 'Country 1, State 2, County 2',
123865);
insert into counties values (2, 2, 2, 'Country 2, State 2, County 2',
886633);
insert into counties values (3, 2, 2, 'Country 3, State 2, County 2',
982345);
insert into counties values (1, 3, 2, 'Country 1, State 3, County 2',
22344);
insert into counties values (2, 3, 2, 'Country 2, State 3, County 2',
179);
insert into counties values (3, 3, 2, 'Country 3, State 3, County 2',
196813);
insert into counties values (1, 1, 3, 'Country 1, State 1, County 3',
491301);
insert into counties values (2, 1, 3, 'Country 2, State 1, County 3',
166540);
insert into counties values (3, 1, 3, 'Country 3, State 1, County 3',
165132);
insert into counties values (1, 2, 3, 'Country 1, State 2, County 3',
0640);
insert into counties values (2, 2, 3, 'Country 2, State 2, County 3',
65120);
insert into counties values (3, 2, 3, 'Country 3, State 2, County 3',
1651462);
insert into counties values (1, 3, 3, 'Country 1, State 3, County 3',
60650);
insert into counties values (2, 3, 3, 'Country 2, State 3, County 3',
651986);
insert into counties values (3, 3, 3, 'Country 3, State 3, County 3',
NULL);
commit work;

Now, we can't do it with ALTER TABLE, but should use UPDATE and I haven't explained it, so use the "cut & paste" and everyone will be happy :-))

Now we can execute the QUERY, and the results should be:

name     |    sum
- ---------+-------
country 1| 705559
country 2|1212418
country 3|2804018
(3 rows)

   sum
- ------
791986
(1 row)

!!!!!! One Difference !!!!!!

Let's look at the states table, it is missing the state 3, we do:

INSERT INTO states VALUES (3, 1, 'State 3, Country 1');
INSERT INTO states VALUES (3, 2, 'State 3, Country 2');
INSERT INTO states VALUES (3, 3, 'State 3, Country 3');

name     |    sum
- ---------+-------
country 1| 791986
country 2|1872205
country 3|3003629

We are missing the state 3 from each country.

Now for those that have been lost, remember that the joins between tables were EXACT, it only extracts data if the condition are exact.

Let's look at the first part of the WHERE: b.cod_country = a.cod_country

This means that I join the country table with the states where the country code is equal, now remember the country data that we inserted:

Don't execute this, is only used as an illustration.

create table countries (cod_country integer, name varchar(30));
insert into countries values (1, 'country 1');
insert into countries values (2, 'country 2');
insert into countries values (3, 'country 3');
commit work;

create table states (state_code int,
                        cod_country int,
                        state_name varchar(30));
insert into states values (1, 1, 'State 1, Country 1');
insert into states values (2, 1, 'State 2, Country 1');
insert into states values (1, 2, 'State 1, Country 2');
insert into states values (2, 2, 'State 2, Country 2');
insert into states values (1, 3, 'State 1, Country 3');
insert into states values (2, 3, 'State 2, Country 3');
commit work;

        AND (c.cod_country = b.cod_country
        AND c.state_code = b.state_code)

The state exists in the counties table but NOT in the states table.

For those that haven't understood, take an aspirin, go walk your dog (if you don't have a dog, go walk without a dog), breath a little fresh air and comeback to begin from the first exercise.

Is is very important to understand how the joining of data is carried out, without this the development that we do can have unpredictable results.

Let's shift gears and start with the SELECT command syntax.

SELECT [DISTINCT] expression1 [AS nom-attribute] {, expression-i [as
nom-attribute-i]}
       [INTO TABLE classname]
       [FROM from-list]
       [WHERE where-clause]
       [GROUP BY attr_name1 {, attr_name-i....}]
       [ORDER BY attr_name1 [ASC | DESC ] [USING op1 ] {,
nom-attribute-i...}]
       [UNION {ALL} SELECT ...]

manu=> select cod_country from countries;
cod_country
- -----------
          1
          2
          3
(3 rows)

manu=> select cod_country as countr from countries;
countr
- ------
     1
     2
     3
(3 rows)

We have seen that the commands SELECT not only returns items from the DB but it can also modify them:

This will return the pay increment of a pay increase more then 10%.

Let's look at the functions that we have available:

These were a few of the functions that exist in SQL, these are those that are defined in ANSI SQL and are also present in Postgres95.

Details of WHERE

Until now, we have seen that the section of WHERE from the SELECT we put things like:

AND column = value

This is a small example of what we put or combine:

AND, OR, NOT, IN, IN ALL, =, !=, >, <, (SELECT....), LIKE also the parenthesis are relevant, example:

WHERE
   column IN (SELECT DISTINCT column FROM table WHERE ....)
   column IN ('value1','value2','value3',...)
   (column = 'value' and column = 'other_value' OR column != 'value')

WHERE column LIKE '%Pepito%'

WHERE column LIKE 'Pepito%'

WHERE column LIKE '%Pepito'

There's not enough time here to list all of the possible options used with WHERE, the limit is in the imagination of the programmer or the limits of the individual process parser.

Now we can leave the SELECT command and concentrate on the last two.

UPDATE command

The UPDATE command allows modification of one or more rows, depending on the defined condition in WHERE

UPDATE table SET column-1 = expression-1
                 [, column-i = expression-i]
       [WHERE condition]

DELETE command

DELETE FROM table
       [WHERE condition]

References

SQL: Introduction to SQL. Installation of PostgreSQL, first article of the series.

2002-10-22, generated by lfparser version 2.32