Sql success ch03

SQL Success
Chapter 3 slides
Stéphane Faroult

1

Row Data
variable1

variable2

variable3
6

select movie_id,
title,
year_released,
country_code
from movies
7

select * from table

≈
print table

8

select * from movies
where ...

14

where country = 'us'

15


16


17


18


27

select *
from (select * from movies
select
where country = 'us' us_movies
'us')
where year_released between 1940 and 1949

28

select *
from (select * from movies
where year_released between 1940
and 1949)
movies_from_the_1940s

32

select *
from movies
and year_released between 1940 and 1949

33

select *
from movies

or
34

select *
from movies

or

not
35

or country = 'gb'

36

or country = 'gb'
and year_released between 1940
and 1949

43

or country = 'gb'
and 1949

44

where (country = 'us'
or country = 'gb')
and 1949

47

French movies from the 1940s
plus
American movies from the 1950s
48

where (country = 'fr'
and year_released between
and
or (country = 'us'
and year_released between
and

1940
1949)
1950
1959)

49

2 < 10
'2' < '10'
'2-JUN-1883'>'1-DEC-2056'

57

2 < 10
'2' < '10'
'2-JUN-1883'>'1-DEC-2056'

As strings!
58

where issued = <some date>

62


Flickr:Yoppy & Rudolf Schuba

63


Flickr:Yoppy & Rudolf Schuba

64

where issued >=
and issued <=

67

where issued >= <Monday 00:00:00>
and issued <= <Friday 00:00:00>

68

where issued >= <Monday 00:00:00>
and issued <= <Friday 00:00:00>

69

40
41
42
43
44
45

Sun Mon Tue Wed Thu
27 28 29 30
1
4
5
6
7
8
11 12 13 14 15
18 19 20 21 22
25 26 27 28 29
1
2
3
4
5

Fri
2
9
16
23
30
6

Sat
3
10
17
24
31
7

70

40
41
42
43
44
45

Sun Mon Tue Wed Thu
27 28 29 30
1
4
5
6
7
8
11 12 13 14 15
18 19 20 21 22
25 26 27 28 29
1
2
3
4
5

Fri
2
9
16
23
30
6

Sat
3
10
17
24
31
7

71

year_released between 1940 and 1949

72

year_released between 1940 and 1949
year_released >= 1940
and year_released <= 1949

73

or country = 'gb')

74

or country = 'gb')

where country in ('us', 'gb')

75

country not in ('us', 'gb')

76

where title not like '%A%'
and title not like '%a%'

80

where upper(title)
not like '%A%'

81

where upper(title)
not like '%A%'

82

NULL in SQL
is NOT a value …
86

where column_name is null
where column_name is not null

92

Who are the people
in the database
who are alive?
93

select title, year_released
from movies

96

-

databases
+
-

schemas
+

tables

99

-

databases
+
-

schemas
+
-

tables
+

columns

100

desc movies;
describe table movies

102

desc movies;
d movies

103

desc movies;
d movies
.schema movies
104

concat('hello' , ' world')

111

select title
|| ' was released in '
|| year_released movie_release
from movies

112

select title
|| ' was released in '
|| year_released movie_release
from movies

113

select title
+ ' was released in '
+ cast(year_released
as varchar) movie_release
from movies

114

select concat(title,
' was released in ',
year_released) movie_release
from movies

115

people

Age of people alive?
116

people

born
died

Age of people alive?
117

Alive
died is null

Age
<this year> - born

121

select column1, ...
from some_table
where some_column = some_user_input

122

select f(column1), ...
from some_table

123

select f(column1), ...
from some_table

124

select column1, ...
from some_table
where some_column = f(some_user_input)

125

select column1, ...
from some_table
where f(some_column) = some_user_input

126

case
end

Flickr:Tony Austin

127

color

Y
n

case upper(color)
when 'Y' then 'Color'
when 'N' then 'B&W'
else '?'
end as color,
...

128

color

Y
n

case upper(color)
when 'N' then 'B&W'
else '?'
end as color,
...

129

color

Y
n

Color

case upper(color)
when 'N' then 'B&W'
else '?'
end as color,
...

130

color

Y
n

Color

case upper(color)
when 'N' then 'B&W'
else '?'
end as color,
...

131

color

Y

Color
?

n

case upper(color)
when 'N' then 'B&W'
else '?'
end as color,
...

132

color

Y

Color
?

n

B&W

case upper(color)
when 'N' then 'B&W'
else '?'
end as color,
...

133

color

Y

Color
?

n

B&W

case upper(color)
when 'N' then 'B&W'
else '?'
end as color,
...

134

case column_name
when null then
end

136

case column_name
when null then
end

137

case upper(color)
when 'N' then 'B&W'
else '?'
end as color,

138

case died
when 1920
when 1921
when 1922
when 1923
when 1924
when 1925
when 1926
when 1927
when 1928

then
then
then
then
then
then
then
then
then

'passed
'passed
'passed
'passed
'passed
'passed
'passed
'passed
'passed

away'
away'
away'
away'
away'
away'
away'
away'
away'
139

case
when died is
'alive
else 'passed
end as status

null then
and kicking'
away'

140

Some useful
functions
more in appendix B ...
Flickr:Sanath Kumar

141

round(3.141592, 0)

3

trunc()

144

round(3.141592, 0)

3

trunc(3.141592)

3

145

round(3.141592, 3)

3.142

trunc(3.141592)

3

146

round(3.141592, 3)

3.142

trunc(3.141592, 3)

3.141

147

upper(), lower()
substr()

149

upper(), lower()
substr('Citizen Kane', 5, 3)

150

upper(), lower()
substr()
trim( )

151

upper(), lower()
substr()
trim( ' Oops

')

'Oops'

152

upper(), lower()
substr()
trim( )

replace()

153

upper(), lower()
substr()
trim( )

replace('Sheep', 'ee', 'i')
'Ship'
154

upper(), lower()
substring()

156

upper(), lower()

substring('Citizen Kane', 5, 3)

157

upper(), lower()
substring()
ltrim()

158

upper(), lower()
substring()
ltrim(' Oops

')

'Oops

'

159

upper(), lower()
substring()
ltrim(' Oops

')

'Oops

'

rtrim()

160

upper(), lower()
substring()
ltrim()

rtrim()
replace()
161

upper(), lower()
substring()
ltrim()

rtrim()
replace('Sheep', 'ee', 'i')
'Ship'
162

Current date
Date Arithmetic
FEBRUARY
MARCH

164

Current date
Date Arithmetic
MARCH

+ 1 month
+ 30 days
165

dateadd(month, 1, date_col)

166

date_col + 1 month

167

date_col + 1 month
date_col + interval'1 month'

168

date_col + 1 month
date_add(date_col, interval 1 month)

169

date_col + 1 month
add_months(date_col, 1)

170

date_col + 1 month
date_col + decimal_number

171

date_col + 1 month
date_col + decimal_number
date(date_col, '1 month')
172

select country from movies

184

distinct
select distinct country
from movies

188

select country, year_released, title
from movies

190

from movies
us
us
ru
us
us
hk
in
us
gb
gb
it
us
de
se
fr
it
jp
in
nz
fr
...

1942
1990
1925
1982
1977
1986
1975
1954
1962
1949
1948
1941
1985
1957
1997
1966
1954
1955
2001
1946

Casablanca
Goodfellas
Bronenosets Potyomkin
Blade Runner
Annie Hall
Ying hung boon sik
Sholay
On The Waterfront
Lawrence Of Arabia
The Third Man
Ladri di biciclette
Citizen Kane
Das Boot
Det sjunde inseglet
Le cinquième élément
Il buono, il brutto, il cattivo
Shichinin no Samurai
Pather Panchali
The Lord of the Rings
La belle et la bête

191

from movies
de
fr
fr
fr
gb
gb
hk
in
in
it
it
jp
nz
ru
se
us
us
us
us
us
...

1985
1997
1946
1942
1962
1949
1986
1975
1955
1948
1966
1954
2001
1925
1957
1942
1990
1982
1977
1954

Das Boot
Les Visiteurs du Soir
Lawrence Of Arabia
The Third Man
Ying hung boon sik
Sholay
Pather Panchali
Ladri di biciclette
Det sjunde inseglet
Casablanca
Goodfellas
Blade Runner
Annie Hall
On The Waterfront

192

from movies
de
fr
fr
fr
gb
gb
hk
in
in
it
it
jp
nz
ru
se
us
us
us
us
us
...

1985
1997
1946
1942
1962
1949
1986
1975
1955
1948
1966
1954
2001
1925
1957
1942
1990
1982
1977
1954

Das Boot
Lawrence Of Arabia
The Third Man
Ying hung boon sik
Sholay
Pather Panchali
Ladri di biciclette
Det sjunde inseglet
Casablanca
Goodfellas
Blade Runner
Annie Hall
On The Waterfront

193

group by
select country,
count(*) number_of_movies
from movies
group by country
195

group by
select country
country,
from movies
group by country
196

group by
select country
country,
from movies
group by country
197

from movies
de
fr
fr
fr
gb
gb
hk
in
in
it
it
jp
nz
ru
se
us
us
us
us
us
...

1985
1997
1946
1942
1962
1949
1986
1975
1955
1948
1966
1954
2001
1925
1957
1942
1990
1982
1977
1954

Das Boot
Lawrence Of Arabia
The Third Man
Ying hung boon sik
Sholay
Pather Panchali
Ladri di biciclette
Det sjunde inseglet
Casablanca
Goodfellas
Blade Runner
Annie Hall
On The Waterfront

1
3
2
1
2
2
1
1

1
1

17
198

select country,
year_released,
from movies
group by country,
year_released

199

select country,
year_released,
from movies
group by country,
year_released

200

select count(*) number_of_movies
from movies

201

count(*) count(col)
min(col)
max(col)

avg(col)
212

Earliest release year
by country?

213

Earliest release year
by country?
select country,
min(year_released) oldest_movie
from movies
group by country

214

select country,
from movies
group by country

215

select *
from (
select country,
from movies
group by country
) earliest_movies_per_country
where oldest_movie < 1940

216

having
select country,
from movies
group by country

217

having
select country,
from movies
group by country
having min(year_released) < 1940

218

SORT

Flickr: Randy Robertson

219

select country,
from movies
group by country
having country = 'us'

220

select country,
from movies
group by country

221

having

Result of aggregate
223

Nulls?
known + unknown = unknown

225

Aggregate functions

ignore
Nulls

FLickr: Linda Åslund

226

select max(died) most_recent_death
from people

227

select max(died) most_recent_death
from people
where died is not null

228

select count(*) people_count,
count(born) birth_year_count,
count(died) death_year_count
from people

233

select count(distinct colname)

235

select country,
count(distinct year_released)
number_of_years
from movies
group by country

236

select country,
count(*) number_of_years
from (select distinct country,
year_released
from movies) t
group by country

237

How many people
are both
actors and directors?

238

How many people
are both

239

How many people
are both

240

How many people
are both

241

How many people
are both

242

How many people
are both

243

How many people
are both

244

How many people
are both

credits
245

movieid

peopleid

8
8
8
8
10
10
10
10
10
12
12
12
136
136
136
136
115
115
115
...

37
38
39
40
11
12
15
16
17
11
11
12
378
433
434
435
38
359
360

credited_as

D
A
A
A
A
A
D
A
A
A
D
A
D
A
A
A
A
D
A
246

movieid

peopleid

8
8
8
8
10
10
10
10
10
12
12
12
136
136
136
136
115
115
115
...

37
38
39
40
11
12
15
16
17
11
11
12
378
433
434
435
38
359
360

credited_as

D
A
A
A
A
A
D
A
A
A
D
A
D
A
A
A
A
D
A

select peopleid,
credited_as
from credits

247

movieid

peopleid

8
8
8
8
10
10
10
10
10
12
12
12
136
136
136
136
115
115
115
...

37
38
39
40
11
12
15
16
17
11
11
12
378
433
434
435
38
359
360

credited_as

D
A
A
A
A
A
D
A
A
A
D
A
D
A
A
A
A
D
A

select peopleid,
credited_as
from credits

248

movieid

peopleid

8
8
8
8
10
10
10
10
10
12
12
12
136
136
136
136
115
115
115
...

37
38
39
40
11
12
15
16
17
11
11
12
378
433
434
435
38
359
360

credited_as

D
A
A
A
A
A
D
A
A
A
D
A
D
A
A
A
A
D
A

select peopleid,
credited_as
from credits

249

peopleid

11
11
12
15
16
17
37
38
39
40
359
360
361
378
379
380
442
442
443
...

credited_as

A
D
A
D
A
A
D
A
A
A
D
A
A
D
A
A
A
D
A

select distinct
peopleid,
credited_as
from credits
where credited_as
in ('A', 'D')

250

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')) all_actors_and_directors

252

select peopleid, count(*) as number_of_roles
from ( select distinct
peopleid,
credited_as
from credits
where credited_as
group by peopleid
having count(*) = 2

253

select count(*) number_of_acting_directors
from (
select peopleid, count(*) as number_of_roles
from ( select distinct
peopleid,
credited_as
from credits
where credited_as
group by peopleid
having count(*) = 2 ) acting_directors

254

Rows are selected with where + conditions.
Beware of or.
Beware of nulls.
Beware of dates.

255

Beware of or.
Beware of nulls.
Beware of dates.
Many functions. case ... end for conditional
display.

256

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.

257

Sql success ch03

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