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NTAUG
Introduction in to use of SQL
Peter Dominey
Copyright © Peter Dominey 2004, <[email protected]>
SQL
 Some History
SQL
 Some History
 Grew out of IBM’s System/R project in 1974
SQL
 Some History
 Grew out of IBM’s System/R project in 1974
 Originally “Structured English Query
Language” which is why we pronounce it
‘sequel’.
SQL
 Some History
 Grew out of IBM’s System/R project in 1974
 Originally “Structured English Query
Language” which is why we pronounce it
‘sequel’.
 Oracle, in 1979 had SQL as it’s query
language
SQL
 Some History
 Grew out of IBM’s System/R project in 1974
 Originally “Structured English Query
Language” which is why we pronounce it
‘sequel’.
 Oracle, in 1979 had SQL as it’s query
language
 After DB2 arrived and SQL became
accepted, ANSI/ISO standards developed
SQL Used in
SQL Used in






Oracle
SyBase
DB2
SQLServer
MySQL
Others
SQL Overview
 SQL is the standard database language
for most commercial relational databases.
It's wide acceptance stems from its ability
to manage all of the necessary database
manipulations while remaining relatively
easy to learn.
SQL Overview
 SQL is the standard database language
for most commercial relational databases.
It's wide acceptance stems from its ability
to manage all of the necessary database
manipulations while remaining relatively
easy to learn.
 English-like command structure makes it
readable, while providing for the most
complex of database functionality.
SQL Overview
 SQL is the standard database language for most
commercial relational databases. It's wide
acceptance stems from its ability to manage all
of the necessary database manipulations while
remaining relatively easy to learn.
 English-like command structure makes it
readable, while providing for the most complex
of database functionality.
 40+ SQL statements follow the same basic
structure, structural consistency keeps it easy to
read and learn
SQL Structure
 All statements start with
SQL Structure
 All statements start with
 A verb,
SQL Structure
 All statements start with
 A verb,
 select
SQL Structure
 All statements start with
 A verb,
 Select
 Insert
 Delete
 Update
SQL Structure
 All statements start with
 A verb,
 Select
 Insert
 Delete
 Update
 A list of tables and/or fields follow the verb
 Followed by a clause or clauses
SQL Structure
 Consider the following:
 SELECT job_name,machine FROM job
WHERE machine=‘somename’
SQL Structure
 The verb defines this as a SELECT statement, which
retrieves rows from a table. We are selecting two
columns, job_name and machine from the table, job.
 Two clauses follow the SELECT statement with the
keywords FROM and WHERE. The FROM clause
selects the two columns from a table named “job",
while the WHERE clause includes the expression that
we only want data from rows where the machine is
‘somename’. This query's result would be a list of jobs
for the machine ‘somename’.
SQL Structure
 Another example:
 SELECT job_name FROM job WHERE
machine=‘somename’ AND owner=‘root’
SQL Structure
 We have here created a query that no
only selects the jobs that are run on a
particular machine (‘somename’) but
refined it to select only those that are run
on that machine AND owned by the user
‘root’
SQL Structure
 A further example:
 SELECT job_name FROM job WHERE
machine=‘somename’ AND owner=‘fred’
AND
command='/sybasedv/dbaroot/bin/do_dbcc.k
sh -Dmaster -SAUTOSYS_SQL_DEV1'
SQL Structure
 This highlights two important points
SQL Structure
 This highlights two important points
 The any number of clauses can be
appended to refine the statement
SQL Structure
 This highlights two important points
 The any number of clauses can be
appended to refine the statement and
 The text can be included as fully as you
wish, so long as it is enclosed in quotes ‘’
SQL Structure
 This highlights two important points
 The any number of clauses can be
appended to refine the statement and
 The text can be included as fully as you
wish, so long as it is enclosed in quits ‘’
 Please note – ignore MS’s stupid quote marks,
they are just single quotes
SQL clauses
 The extend and power of SQL lays in the
clauses you can construct.
SQL clauses
 The extend and power of SQL lays in the
clauses you can construct.
 Take the earlier statement:
 SELECT job_name FROM job WHERE
machine=‘somename’ AND owner=‘fred’ AND
command='/sybasedv/dbaroot/bin/do_dbcc.ksh Dmaster -SAUTOSYS_SQL_DEV1'
SQL ‘LIKE’ clause
 The extend and power of SQL lays in the
clauses you can construct.
 To make it find jobs that have similar commands we
could have a state:
 SELECT job_name FROM job WHERE
machine=‘somename’ AND owner=‘fred’ AND command
LIKE ‘%dbcc%’
 Here we are finding anything that has the string
dbcc in it from the column ‘command’
 % is used as a wild card.
SQL ‘DISTINCT’ clause
 The extend and power of SQL lays in the
clauses you can construct.
 To find all the machines that have jobs
defined, but only list each unique machines
name:
 SELECT DISTINCT machine FROM job
SQL ‘DISTINCT’ clause
 The extend and power of SQL lays in the
clauses you can construct.
 To find all the machines that have jobs defined, but
only list each unique machines name:
 SELECT DISTINCT machine FROM job
 And then order it in a simple alphabetical order
 SELECT DISTINCT machine FROM job ORDER BY
machine
SQL ‘WHERE’ clause
 We touched earlier on the where clause
SQL ‘WHERE’ clause
 We touched earlier on the where clause
 SELECT job_name FROM job WHERE
machine=‘somename’
And made the use of the simplest form, equals
‘=‘
SQL ‘WHERE’ clause
 We touched earlier on the where clause
 SELECT job_name FROM job WHERE
machine=‘somename’
And made the use of the simplest form and
equals ‘=‘
There are other operators:
SQL ‘WHERE’ clause
 We touched earlier on the where clause
 SELECT job_name FROM job WHERE machine=‘somename’
And made the use of the simplest form and equals ‘=‘
There are other operators:
=
<>
>
<
>=
<=
BETWEEN
LIKE
Equal
Not equal
Greater than
Less than
Greater than or equal
Less than or equal
Between an inclusive range
Search for a pattern
SQL ‘WHERE’ clause
 To extract information where you have a
list of items:
 SELECT job_name FROM job WHERE
machine IN
(‘machine1’,’machinezxt’,’machine1b’)
SQL Select within Select
 SELECT job_name FROM job WHERE
machine IN (SELECT hostname FROM
keymaster)
SQL Information from
multiple tables
 Examine the following statement:
 SELECT keymaster.hostid, job.job_name
FROM keymaster, job WHERE
job.machine=keymaster.hostname
SQL Introduction
 As stated earlier, this was introduction to
SQL and hopefully has provided a taste
of the things that can be done to extract
information directly from the AutoSys
database.
SQL Introduction
 As stated earlier, this was introduction to
SQL and hopefully has provided a taste
of the things that can be done to extract
information directly from the AutoSys
database.
 [email protected]
 www.dominey.biz