sql success ch03
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1
SQL Success
Chapter 3 slides
Stéphane Faroult
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select * from tablename
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select * from movies
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All columns
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variable1
variable2
variable3
Row Data
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select movie_id, title, year_released, country_code from movies
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select * from table
≈
print table
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Restriction
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Restriction
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Restriction
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Restriction
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select * from movies
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select * from movies
where ...
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where country = 'us' select * from movies
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where country = 'us' select * from movies
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where country = 'us' select * from movies
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where country = 'us' select * from movies
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'constant'
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column
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Jaws where title =
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Jaws where title =
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'Jaws' where title =
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Movies
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Movies
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US Movies
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select * from movies where country = 'us'
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select * from movies where country = 'us'
select * from (select * from movies where country = 'us') us_movies where year_released between 1940 and 1949
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ALL MOVIES
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US MOVIES
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US MOVIES, 1940s
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select * from (select * from movies where year_released between 1940 and 1949) movies_from_the_1940s where country = 'us'
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select * from movies where country = 'us' and year_released between 1940 and 1949
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select * from movies where country = 'us' and year_released between 1940 and 1949
or
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select * from movies where country = 'us' and year_released between 1940 and 1949
or not
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select * from movies where country = 'us' or country = 'gb'
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and > or
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and > or
2 + 3 * 4
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and > or
2 + 3 * 4 3 * 4
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and > or
2 + 3 * 4
12
3 * 4
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2 + 12
and > or
2 + 3 * 4
12
3 * 4
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2 + 12
and > or
2 + 3 * 4
14
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where country = 'us' or country = 'gb' and year_released between 1940 and 1949
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where country = 'us' or country = 'gb' and year_released between 1940 and 1949
country = 'gb' and year_released between 1940 and 1949
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Movies
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Movies
1940s
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where (country = 'us' or country = 'gb') and year_released between 1940 and 1949
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French movies from the 1940s
plus
American movies from the 1950s
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select * from movies where (country = 'fr' and year_released between 1940 and 1949) or (country = 'us' and year_released between 1950 and 1959)
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=
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=
<> or !=
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=
<= <
<> or !=
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=
<= <
>
<> or !=
>=
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2 < 10
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2 < 10
'2' < '10'
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2 < 10
'2' < '10'
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2 < 10
'2' < '10'
'2-JUN-1883'>'1-DEC-2056'
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2 < 10
'2' < '10'
'2-JUN-1883'>'1-DEC-2056'
As strings!
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DD/MM/YYYY
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DD/MM/YYYY
MM/DD/YYYY
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Convert EXPLICITLY!
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where issued = <some date>
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where issued = <some date>
Flickr:Yoppy & Rudolf Schuba
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where issued = <some date>
Flickr:Yoppy & Rudolf Schuba
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where issued >= and issued <=
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<Monday 00:00:00> <Friday 00:00:00>
where issued >= and issued <=
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<Monday 00:00:00> <Friday 00:00:00>
where issued >= and issued <=
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Sun Mon Tue Wed Thu Fri Sat
40
41
42
43
44
45
27 28 29 30 1 2 3
4 5 6 7 8 9 10
11 12 13 14 15 16 17
18 19 20 21 22 23 24
25 26 27 28 29 30 31
1 2 3 4 5 6 7
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Sun Mon Tue Wed Thu Fri Sat
40
41
42
43
44
45
27 28 29 30 1 2 3
4 5 6 7 8 9 10
11 12 13 14 15 16 17
18 19 20 21 22 23 24
25 26 27 28 29 30 31
1 2 3 4 5 6 7
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year_released between 1940 and 1949
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year_released between 1940 and 1949
year_released >= 1940 and year_released <= 1949
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where (country = 'us' or country = 'gb') and year_released between 1940 and 1949
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where country in ('us', 'gb') and year_released between 1940 and 1949
where (country = 'us' or country = 'gb') and year_released between 1940 and 1949
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country not in ('us', 'gb')
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like
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like
%
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like
% _
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select * from movies where title not like '%A%' and title not like '%a%'
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select * from movies where upper(title) not like '%A%'
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select * from movies where upper(title) not like '%A%'
83 Flickr:Daniel Moyle 83
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if (ptr == NULL) {
…
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if (ptr == NULL) {
…
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NULL in SQL is NOT a value …
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where column_name = null
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where column_name = null
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where column_name <> null
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where column_name <> null
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where column_name is null
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where column_name is null
where column_name is not null
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Who are the people in the database who are alive?
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select title, year_released from movies where country = 'us'
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databases - +
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databases -
schemas +
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databases -
schemas +
tables +
-
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databases -
schemas +
tables +
columns +
-
-
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desc movies;
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desc movies;
describe table movies
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desc movies;
describe table movies
\d movies
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desc movies;
describe table movies
\d movies
.schema movies
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compute
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compute
derive
107 Flickr: Etsuko Nakamura
108 Flickr: Etsuko Nakamura
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'hello' ' world' +
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'hello' ' world' ||
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concat( , ) 'hello' ' world'
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select title || ' was released in ' || year_released movie_release from movies where country = 'us'
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select title || ' was released in ' || year_released movie_release from movies where country = 'us'
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select title + ' was released in ' + cast(year_released as varchar) movie_release from movies where country = 'us'
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select concat(title, ' was released in ', year_released) movie_release from movies where country = 'us'
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people
Age of people alive?
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people born died
Age of people alive?
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Alive
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died
Alive is null
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died
Alive is null
Age
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died
Alive is null
Age born <this year> -
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select from some_table where some_column = some_user_input
column1, ...
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select from some_table where some_column = some_user_input
f(column1), ...
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select from some_table where some_column = some_user_input
f(column1), ...
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select from some_table where some_column = f(some_user_input)
column1, ...
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select from some_table where f(some_column) = some_user_input
column1, ...
127 Flickr:Tony Austin
case end
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Y
n
color case upper(color) when 'Y' then 'Color' when 'N' then 'B&W' else '?' end as color, ...
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Y
n
color case upper(color) when 'Y' then 'Color' when 'N' then 'B&W' else '?' end as color, ...
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Y
n
color case upper(color) when 'Y' then 'Color' when 'N' then 'B&W' else '?' end as color, ...
Color
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case upper(color) when 'Y' then 'Color' when 'N' then 'B&W' else '?' end as color, ...
Y
n
color
Color
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case upper(color) when 'Y' then 'Color' when 'N' then 'B&W' else '?' end as color, ...
Y
n
color
Color
?
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case upper(color) when 'Y' then 'Color' when 'N' then 'B&W' else '?' end as color, ...
Y
n
color
Color
B&W
?
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case upper(color) when 'Y' then 'Color' when 'N' then 'B&W' else '?' end as color, ...
Y
n
color
Color
B&W
?
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case column_name when null then end
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case column_name when null then end
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case upper(color) when 'Y' then 'Color' when 'N' then 'B&W' else '?' end as color,
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when 1929 then 'passed away'
case died when 1920 then 'passed away' when 1921 then 'passed away'
when 1922 then 'passed away'
when 1923 then 'passed away'
when 1924 then 'passed away'
when 1925 then 'passed away'
when 1926 then 'passed away'
when 1927 then 'passed away'
when 1928 then 'passed away'
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case when died is null then 'alive and kicking' else 'passed away' end as status
died is null
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Flickr:Sanath Kumar
Some useful functions
more in appendix B ...
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round( )
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round(
trunc(
)
)
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round(
trunc( )
3 3.141592, 0)
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round(
trunc( 3.141592)
3
3
3.141592, 0)
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3.141592, 3) round(
trunc( 3.141592)
3.142
3
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3.141592, 3)
3.141592, 3) round(
trunc(
3.142
3.141
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upper(), lower()
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substr(
upper(), lower()
)
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substr(
upper(), lower()
'Citizen Kane', 5, 3)
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substr(
trim(
upper(), lower()
)
)
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substr(
trim(
upper(), lower()
)
' Oops ') 'Oops'
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substr(
trim(
replace(
upper(), lower()
)
)
)
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'Sheep', 'ee', 'i')
substr(
trim(
replace(
upper(), lower()
)
)
'Ship'
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upper(), lower()
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substring(
upper(), lower()
)
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substring(
upper(), lower()
'Citizen Kane', 5, 3)
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substring(
ltrim(
upper(), lower()
)
)
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substring(
ltrim(
upper(), lower()
)
' Oops ') 'Oops '
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substring(
ltrim(
upper(), lower()
)
' Oops ') 'Oops '
rtrim()
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substring(
ltrim(
replace(
upper(), lower()
)
)
)
rtrim()
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'Sheep', 'ee', 'i')
substring(
ltrim(
replace(
upper(), lower()
)
)
rtrim()
'Ship'
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Current date
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MARCH FEBRUARY
Current date
Date Arithmetic
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MARCH
Current date
Date Arithmetic
+ 1 month
+ 30 days
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dateadd(month, 1, date_col)
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dateadd(month, 1, date_col)
date_col + 1 month
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dateadd(month, 1, date_col)
date_col + 1 month
date_col + interval'1 month'
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dateadd(month, 1, date_col)
date_col + 1 month
date_col + interval'1 month'
date_add(date_col, interval 1 month)
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dateadd(month, 1, date_col)
date_col + 1 month
date_col + interval'1 month'
date_add(date_col, interval 1 month)
add_months(date_col, 1)
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dateadd(month, 1, date_col)
date_col + 1 month
date_col + interval'1 month'
date_add(date_col, interval 1 month)
add_months(date_col, 1)
date_col + decimal_number
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dateadd(month, 1, date_col)
date_col + 1 month
date_col + interval'1 month'
date_add(date_col, interval 1 month)
add_months(date_col, 1)
date_col + decimal_number
date(date_col, '1 month')
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'28-DEC-1895'
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'28-DEC-1895'
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'28-DEC-1895'
DBMS date
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'12/28/1895'
DBMS date
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cast( as )
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y z x
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(x + y)
z
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(x + y)
z
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No duplicates
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No duplicates
Identifier
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select country from movies
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distinct
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distinct
select distinct country from movies
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Aggregate functions
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select country, year_released, title from movies
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us 1942 Casablanca
us 1990 Goodfellas
ru 1925 Bronenosets Potyomkin
us 1982 Blade Runner
us 1977 Annie Hall
hk 1986 Ying hung boon sik
in 1975 Sholay
us 1954 On The Waterfront
gb 1962 Lawrence Of Arabia
gb 1949 The Third Man
it 1948 Ladri di biciclette
us 1941 Citizen Kane
de 1985 Das Boot
se 1957 Det sjunde inseglet
fr 1997 Le cinquième élément
it 1966 Il buono, il brutto, il cattivo
jp 1954 Shichinin no Samurai
in 1955 Pather Panchali
nz 2001 The Lord of the Rings
fr 1946 La belle et la bête
...
select country, year_released, title from movies
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de 1985 Das Boot
fr 1997 Le cinquième élément
fr 1946 La belle et la bête
fr 1942 Les Visiteurs du Soir
gb 1962 Lawrence Of Arabia
gb 1949 The Third Man
hk 1986 Ying hung boon sik
in 1975 Sholay
in 1955 Pather Panchali
it 1948 Ladri di biciclette
it 1966 Il buono, il brutto, il cattivo
jp 1954 Shichinin no Samurai
nz 2001 The Lord of the Rings
ru 1925 Bronenosets Potyomkin
se 1957 Det sjunde inseglet
us 1942 Casablanca
us 1990 Goodfellas
us 1982 Blade Runner
us 1977 Annie Hall
us 1954 On The Waterfront
...
select country, year_released, title from movies
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de 1985 Das Boot
fr 1997 Le cinquième élément
fr 1946 La belle et la bête
fr 1942 Les Visiteurs du Soir
gb 1962 Lawrence Of Arabia
gb 1949 The Third Man
hk 1986 Ying hung boon sik
in 1975 Sholay
in 1955 Pather Panchali
it 1948 Ladri di biciclette
it 1966 Il buono, il brutto, il cattivo
jp 1954 Shichinin no Samurai
nz 2001 The Lord of the Rings
ru 1925 Bronenosets Potyomkin
se 1957 Det sjunde inseglet
us 1942 Casablanca
us 1990 Goodfellas
us 1982 Blade Runner
us 1977 Annie Hall
us 1954 On The Waterfront
...
select country, year_released, title from movies
194
group by
195
group by
select country, count(*) number_of_movies from movies group by country
count(*)
196
group by
select country, count(*) number_of_movies from movies group by country
country
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group by
select country, count(*) number_of_movies from movies group by country
country
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de 1985 Das Boot
fr 1997 Le cinquième élément
fr 1946 La belle et la bête
fr 1942 Les Visiteurs du Soir
gb 1962 Lawrence Of Arabia
gb 1949 The Third Man
hk 1986 Ying hung boon sik
in 1975 Sholay
in 1955 Pather Panchali
it 1948 Ladri di biciclette
it 1966 Il buono, il brutto, il cattivo
jp 1954 Shichinin no Samurai
nz 2001 The Lord of the Rings
ru 1925 Bronenosets Potyomkin
se 1957 Det sjunde inseglet
us 1942 Casablanca
us 1990 Goodfellas
us 1982 Blade Runner
us 1977 Annie Hall
us 1954 On The Waterfront
...
select country, year_released, title from movies
1
3
2
1
2
2
1 1
1 1
17
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select country, year_released, count(*) number_of_movies from movies group by country, year_released
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select country, year_released, count(*) number_of_movies from movies group by country, year_released
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select count(*) number_of_movies from movies
202
where
203
where
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where
205
where
206
where
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distinct, group by
208
distinct, group by
209
distinct, group by
210
distinct, group by
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distinct, group by
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count(*)
min(
max(
avg(
count(col)
col)
col)
col)
213
Earliest release year by country?
214
select country, min(year_released) oldest_movie from movies group by country
Earliest release year by country?
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select country, min(year_released) oldest_movie from movies group by country
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select country, min(year_released) oldest_movie from movies group by country
select * from ( ) earliest_movies_per_country where oldest_movie < 1940
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select country, min(year_released) oldest_movie from movies group by country
having
218
select country, min(year_released) oldest_movie from movies group by country
having min(year_released) < 1940
having
219 Flickr: Randy Robertson
SORT
219
220
group by country having country = 'us'
select country, min(year_released) oldest_movie from movies
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where country = 'us' group by country
select country, min(year_released) oldest_movie from movies
222 Flickr: Dano 222
223
having
Result of aggregate
224
Nulls?
225
Nulls?
known + unknown = unknown
226
FLickr: Linda Åslund
Aggregate functions
ignore Nulls
226
227
select max(died) most_recent_death from people
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select max(died) most_recent_death from people where died is not null
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count(*)
230
count(*)
231
count(col)
232
count(col)
233
select count(*) people_count, count(born) birth_year_count, count(died) death_year_count from people
234
select count(colname)
235
select count(distinct colname)
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select country, count(distinct year_released) number_of_years from movies group by country
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select country, count(*) number_of_years from (select distinct country, year_released from movies) t group by country
238
How many people are both
actors and directors?
239
How many people are both
actors and directors?
240
How many people are both
actors and directors?
241
How many people are both
actors and directors?
242
How many people are both
actors and directors?
243
How many people are both
actors and directors?
244
How many people are both
actors and directors?
245
How many people are both
actors and directors?
credits
246
8 37 D 8 38 A 8 39 A 8 40 A 10 11 A 10 12 A 10 15 D 10 16 A 10 17 A 12 11 A 12 11 D 12 12 A 136 378 D 136 433 A 136 434 A 136 435 A 115 38 A 115 359 D 115 360 A ...
movieid peopleid credited_as
247
8 37 D 8 38 A 8 39 A 8 40 A 10 11 A 10 12 A 10 15 D 10 16 A 10 17 A 12 11 A 12 11 D 12 12 A 136 378 D 136 433 A 136 434 A 136 435 A 115 38 A 115 359 D 115 360 A ...
movieid peopleid credited_as
select peopleid, credited_as from credits
248
8 37 D 8 38 A 8 39 A 8 40 A 10 11 A 10 12 A 10 15 D 10 16 A 10 17 A 12 11 A 12 11 D 12 12 A 136 378 D 136 433 A 136 434 A 136 435 A 115 38 A 115 359 D 115 360 A ...
movieid peopleid credited_as
38 A
38 A
select peopleid, credited_as from credits
249
8 37 D 8 38 A 8 39 A 8 40 A 10 11 A 10 12 A 10 15 D 10 16 A 10 17 A 12 11 A 12 11 D 12 12 A 136 378 D 136 433 A 136 434 A 136 435 A 115 38 A 115 359 D 115 360 A ...
movieid peopleid credited_as
38 A
38 A
11 A
11 A
select peopleid, credited_as from credits
250
peopleid credited_as
11 A 11 D 12 A 15 D 16 A 17 A 37 D 38 A 39 A 40 A 359 D 360 A 361 A 378 D 379 A 380 A 442 A 442 D 443 A ...
select distinct peopleid, credited_as from credits where credited_as in ('A', 'D')
251
select distinct peopleid, credited_as from credits where credited_as in ('A', 'D')
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( ) all_actors_and_directors
select distinct peopleid, credited_as from credits where credited_as in ('A', 'D')
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select peopleid, count(*) as number_of_roles from group by peopleid having count(*) = 2
( ) all_actors_and_directors
select distinct peopleid, credited_as from credits where credited_as in ('A', 'D')
254
select peopleid, count(*) as number_of_roles from group by peopleid having count(*) = 2
( ) all_actors_and_directors
select distinct peopleid, credited_as from credits where credited_as in ('A', 'D')
select count(*) number_of_acting_directors from (
) acting_directors
255
Rows are selected with where + conditions. Beware of or. Beware of nulls. Beware of dates.
256
Rows are selected with where + conditions. Beware of or. Beware of nulls. Beware of dates. Many functions. case ... end for conditional display.
257
Rows are selected with where + conditions. Beware of or. Beware of nulls. Beware of dates. Many functions. case ... end for conditional display.
You must use distinct or group by to remove duplicates from a result set if there is no key.
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