By expanding our knowledge of SQL facilities, we can let all the boring work be handled via SQL rather than a lot of middle-tier code, and we can get performance benefits as an added bonus. Here are some SQL techniques to solve problems that would otherwise require a lot of complex coding, freeing up your time to focus on the delivery of great applications.

1. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |
bienvenido

2. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |
Lo siento, no hablo español :-(

3. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |
But I will do my best to help
Pero haré todo lo posible para ayudar

4. 10 Amazing SQL features
Connor McDonald
Database Advocate
Características asombrosas de SQL

5. Copyright © 2018, Oracle and/or its affiliates. All rights reserved.
Connor McDonald

6. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |
6

7. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |
7

8. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |
Me
youtube bit.ly/youtube-connor
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400+ posts mainly on database & development
250 technical videos, new uploads every week
Más de 400 publicaciones principalmente en bases de datos y desarrollo
250 videos técnicos, nuevas cargas cada semana

9. Copyright © 2018, Oracle and/or its affiliates. All rights reserved.
etc...
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10. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |
https://asktom.oracle.com

11. 11

12. SO

13. THE

14. BIG

15. QUESTION

16. IS

17. 17
WHY ?así que la gran pregunta es por qué

18. why talk about SQL ?
18
por qué hablar de SQL

19. it is old !
19
es viejo

20. 20

21. why talk about SQL # 1
21
por qué hablar de SQL

22. NoSQL
22
non relational

23. 23

24. why talk about SQL # 2
24
por qué hablar de SQL

25. developers love cool stuff
25
los desarrolladores aman las cosas geniales

26. MICROSERVICES
26

27. SQL is microservices !
27
SQL es microservicios!

28. 28
"fine-grained to perform a single function"
"Each service is ... minimal, and complete"
https://en.wikipedia.org/wiki/Microservices
select COUNT(*)
from PEOPLE
where GENDER = 'MALE'
multa-granulado para realizar una sola función
Cada servicio es ... mínimo y completo

29. even cooler stuff
29
cosas aún más geniales

30. API
30

31. SQL is entirely APIs !
31
SQL es completamente API

32. 32
"By abstracting the underlying implementation"
"describes the expected behaviour ... but can have multiple implementations"
https://en.wikipedia.org/wiki/Application_programming_interface
select NAME, STREET_NO, ZIP_CODE
from PEOPLE p,
ADDRESS a
where p.AGE > 50
and p.ADDRESS_ID = a.ADDRESS_ID;
Al abstraer la implementación subyacente
describe el comportamiento esperado ... pero puede tener múltiples implementaciones

33. key point
41
punto clave

34. this session is not about ...
42
esta sesión es no acerca de ...

35. being a smart-ass
43
ser inteligente - culo

36. we can do anything ...
44
todo es posible

37. SQL> with x( s, ind ) as
2 ( select sud, instr( sud, '.' )
3 from ( select replace(replace(
4 replace(replace(:board,'-'),'|'),' '),chr(10)) sud
5 from dual )
6 union all
7 select substr(s,1,ind-1)||z||substr(s,ind+1)
8 , instr(s,'.',ind+1)
9 from x
10 , ( select to_char( rownum ) z
11 from dual connect by rownum <= 9 ) z
12 where ind > 0
13 and not exists (
14 select null
15 from ( select rownum lp from dual
16 connect by rownum <= 9 )
17 where z = substr(s,trunc((ind-1)/9)*9+lp,1)
45

38. 18 or z = substr(s,mod(ind-1,9)-8+lp*9,1)
19 or z = substr(s,mod(trunc((ind-1)/3),3)*3
20 +trunc((ind-1)/27)*27+lp
21 +trunc((lp-1)/3)*6,1)
22 )
23 ),
24 result as (
25 select s
26 from x
27 where ind = 0 )
28 select
29 regexp_replace(substr(s,(idx-1)*9+1,9),
30 '(...)(...)(...)',
31 '1|2|3')||
32 case when mod(idx,3)=0 then chr(10)||rpad('-',11,'-') end soln
33 from result,
34 ( select level idx
35 from dual
36 connect by level <= 9 )
46
Ack: Anton Scheffer,
https://technology.amis.nl

39. SQL> variable board varchar2(1000)
SQL> begin :board :=
2 '53.|.7.|...
3 6..|195|...
4 .98|...|.6.
5 -----------
6 8..|.61|..3
7 4..|8.3|..1
8 7..|.2.|..6
9 -----------
10 .6.|...|28.
11 ...|419|..5
12 ...|.8.|.79
13 ';
14 end;
47
5 3 7
6 1 9 5
9 8 6
8 6 1 3
4 8 3 1
7 2 6
6 2 8
4 1 9 5
8 7 9

40. SOLUTION
-----------
534|678|912
672|195|348
198|342|567
-----------
859|761|423
426|853|791
713|924|856
-----------
961|537|284
287|419|635
345|286|179
-----------
48
sud.sql

41. 49
100%
% of developers that
will need to solve Sudoku
as part of their job
% de desarrolladores que
tendrá que resolver Sudoku
como parte de su trabajo

42. 50
100%
% of developers that need
to get real work done
% de desarrolladores que necesitan
llegar trabajo de verdad hecho

43. real work
51
trabajo de verdad

44. 52
1

45. some controversy...
53
alguna controversia

46. 54
DBA

48. 56Public

49. 57Public

50. DBA friendship is important
58
oc00.sql
La amistad de DBA es importante

51. 59
2

52. totals / subtotals
60

53. "Employee salary list,
plus department total,
plus grand total"
61
"Lista de salario del empleado,
más el total del departamento,
más el gran total "

54. 62

55. SQL> select empno, ename, sal, deptno from emp
2 order by deptno;
EMPNO ENAME SAL DEPTNO
---------- ---------- ---------- ----------
7782 CLARK 2450 10
7839 KING 5000 10
7934 MILLER 1300 10
...
7900 JAMES 950 30
7698 BLAKE 2850 30
7654 MARTIN 1250 30
63
SQL> select deptno,
2 sum(sal)
3 from emp
4 group by deptno
5 order by deptno;
DEPTNO SUM(SAL)
---------- ----------
10 8750
20 10875
30 9400
SQL> select sum(sal) from emp;
SUM(SAL)
----------
29025

56. from 3 to 2
64
rollup

57. SQL> select empno, ename, sal, deptno from emp
2 order by deptno;
EMPNO ENAME SAL DEPTNO
---------- ---------- ---------- ----------
7782 CLARK 2450 10
7839 KING 5000 10
7934 MILLER 1300 10
...
7900 JAMES 950 30
7698 BLAKE 2850 30
7654 MARTIN 1250 30
65
SQL> select deptno,
2 sum(sal)
3 from emp
4 group by rollup(deptno)
5 order by deptno;
DEPTNO SUM(SAL)
---------- ----------
10 8750
20 10875
30 9400
29025

58. still messy...
66
todavía desordenado

59. EMPNO SAL DEPTNO
---------- ---------- ----------
7782 2450 10
7839 5000 10
7934 1300 10
7566 2975 20
7902 3000 20
7876 1100 20
7369 800 20
67
DEPTNO SUM(SAL)
---------- ----------
10 8750
20 10875
30 9400
29025
7782 2450 10
7839 5000 10
7934 1300 10
7566 2975 20
10 8750

60. from 2 to 1
68

61. SQL> select deptno,
2 nvl2(rownum,max(empno),null) empno,
3 nvl2(rownum,max(ename),null) ename,
4 sum(sal)
5 from emp
6 group by rollup(deptno,rownum)
7 order by deptno,empno;
DEPTNO EMPNO ENAME SUM(SAL)
---------- ---------- ---------- ----------
10 7782 CLARK 2450
10 7839 KING 5000
10 7934 MILLER 1300
10 8750
20 7369 SMITH 800
20 7566 JONES 2975
...
30 7900 JAMES 950
30 9400
2902569

62. all totals are possible
70
todos los totales son posibles

63. SQL> select deptno,job,sum(sal) from scott.emp
2 group by CUBE(deptno,job)
3 order by deptno,job;
DEPTNO JOB SUM(SAL)
---------- --------- ----------
10 CLERK 1300
10 MANAGER 2450
10 PRESIDENT 5000
10 8750
20 ANALYST 6000
20 CLERK 1900
20 MANAGER 2975
20 10875
30 CLERK 950
30 MANAGER 2850
30 SALESMAN 5600
30 9400
ANALYST 6000
CLERK 4150
MANAGER 8275
PRESIDENT 5000
SALESMAN 5600
29025
71

64. totally customisable
72
totalmente personalizable

65. SQL> select deptno, job, mgr, sum(sal) from emp
2 group by grouping sets (
3 (deptno),
4 (job,mgr), () ) ;
DEPTNO JOB MGR SUM(SAL)
---------- --------- ---------- ----------
CLERK 7902 800
PRESIDENT 5000
CLERK 7698 950
CLERK 7788 1100
CLERK 7782 1300
SALESMAN 7698 5600
MANAGER 7839 8275
ANALYST 7566 6000
10 8750
20 10875
30 9400
29025
73

66. 74
3

67. error logging
75
registro de errores

68. SQL> insert into MY_TABLE
2 select *
3 from MY_HUGE_GREAT_FAT_TABLE;
76
MY_HUGE_GREAT_FAT_TABLE;

69. 77

70. 78

71. 79

72. 80

73. 81

74. SQL> insert into MY_TABLE
2 select *
3 from MY_HUGE_GREAT_FAT_TABLE;
Elapsed: 06:12:34.00
82

75. SQL> insert into MY_TABLE
2 select *
3 from MY_HUGE_GREAT_FAT_TABLE;
Elapsed: 06:12:34.00
ERROR at line 1:
ORA-01847: day of month must be between 1 and last day of month
83

76. 84

77. 85

78. 86
and then we do this :-)
y luego hacemos esto

79. SQL> select count(*) from MY_TABLE;
COUNT(*)
----------
0
87

80. what we would like
88
lo que nos gustaria

81. keep successful rows
89
mantener registros exitosas

82. skip / bypass bad rows
90
saltar / desviar registros malo

83. hard
91
difícil

84. SQL> insert into MY_TABLE
2 select *
3 from MY_HUGE_GREAT_FAT_TABLE
4 where "not a duplicate"
5 and "datatypes are ok"
6 and "foreign keys are ok"
7 and "check constraints are ok"
92

85. SQL> exec DBMS_ERRLOG.CREATE_ERROR_LOG('EMP')
93

86. ERR$_EMP
94

87. DBMS_ERRLOG.CREATE_ERROR_LOG (
dml_table_name IN VARCHAR2,
err_log_table_name IN VARCHAR2 := NULL,
err_log_table_owner IN VARCHAR2 := NULL,
...
95

88. SQL> desc ERR$_EMP
Name Null? Type
----------------------------- -------- ----------------
ORA_ERR_NUMBER$ NUMBER
ORA_ERR_MESG$ VARCHAR2(2000)
ORA_ERR_ROWID$ ROWID
ORA_ERR_OPTYP$ VARCHAR2(2)
ORA_ERR_TAG$ VARCHAR2(2000)
EMPNO VARCHAR2(4000)
ENAME VARCHAR2(4000)
JOB VARCHAR2(4000)
MGR VARCHAR2(4000)
HIREDATE VARCHAR2(4000)
SAL VARCHAR2(4000)
COMM VARCHAR2(4000)
DEPTNO VARCHAR2(4000)
96

89. 97

90. example
98
ejemplo

91. add to EMP from NEW_DATA
99

92. SQL> select * from NEW_DATA;
EMPNO SAL DEPTNO
---------- ---------- ----------
1000 5000 20
100X 3550 10
2000 2500 50
7934 4000 20
100
non-numeric
no dept 50
duplicate

93. SQL> exec dbms_errlog.create_error_log( 'EMP' );
PL/SQL procedure successfully completed.
SQL> insert into EMP (empno,sal,deptno)
2 select empno,sal,deptno
3 from NEW_DATA
4 LOG ERRORS REJECT LIMIT UNLIMITED;
1 row created.
101
50

94. SQL> select ORA_ERR_OPTYP$ op, ORA_ERR_MESG$, EMPNO
2 from ERR$_EMP
OP ORA_ERR_MESG$ EMPNO
-- ------------------------------------------------------------ -----
I ORA-01722: invalid number 100X
I ORA-02291: integrity constraint (SCOTT.FK_DEPTNO) violated 2000
I ORA-00001: unique constraint (SCOTT.PK_EMP) violated 7934
102

95. 103
4

96. partitioned outer join
104
unión externa particionada

97. 105
SQL> select *
2 from timeslots;
HR
--
8
9
10
11
12
13
14
15
16
SQL> select *
2 from bookings;
HR ROOM WHO
------- ---------- -------
8 Room2 PETE
9 Room1 JOHN
11 Room1 MIKE
14 Room2 JILL
15 Room2 JANE
16 Room1 SAM

98. bookings by hour
106
conventional outer join
reservas por hora
unión exterior convencional

99. 107
SQL> SELECT hrs.hr, t1.room, t1.who
2 from timeslots hrs
3 left outer join bookings t1
4 on hrs.hr = t1.hr
5 order by 1
HR ROOM WHO
------- ---------- ----------
8 Room2 PETE
9 Room1 JOHN
10
11 Room1 MIKE
12
13
14 Room2 JILL
15 Room2 JANE
16 Room1 SAM
107

100. bookings by hour per room
108
reservas por hora por habitacion

101. 109
HR ROOM WHO
------- ---------- ----------
8 Room2 PETE
9
10
11
12
13
14 Room2 JILL
15 Room2 JANE
16
HR ROOM WHO
------- ---------- ----------
8
9 Room1 JOHN
10
11 Room1 MIKE
12
13
14
15
16 Room1 SAM

102. 110
SQL> select *
2 from timeslots;
HR
--
8
9
10
11
12
13
14
15
16
x "Room 1"
x "Room 2"
...
x "Room n"

103. partitioned outer join
111
dividido unión externa

104. SQL> SELECT hrs.hr, t1.room, t1.who
2 FROM bookings t1
3 PARTITION BY (t1.room)
4 RIGHT OUTER JOIN timeslots ON (hrs.hr = t1.hr)
5 order by 1,2
HR ROOM WHO
--------- ---------- ----------
8 Room1
9 Room1 JOHN
10 Room1
11 Room1 MIKE
12 Room1
13 Room1
14 Room1
15 Room1
16 Room1 SAM
8 Room2 PETE
9 Room2
10 Room2
11 Room2
12 Room2
13 Room2
14 Room2 JILL
15 Room2 JANE
16 Room2 112

105. 113
5

106. subquery factoring
114
factorización de subconsulta

107. common table expressions
115
expresiones de tabla comunes

108. WITH clause
116

109. SQL> WITH last_hire AS
2 ( select deptno, max(hiredate)
3 from emp
4 group by deptno
5 )
6 select * from last_hire;
DEPTNO MAX(HIRED
---------- ---------
30 03-DEC-81
20 12-JAN-83
10 23-JAN-82
117

110. "who cares?....... more code, same result"
118
A quién le importa? ....... más código, mismo resultado

111. WITH last_hire AS
(
select deptno, max(hiredate)
from emp
group by deptno
)
select * from last_hire;
119

112. why is it cool ?
120
Por qué es genial?

113. good solution metaphor
121
buena solución metáfora

114. relational is a rigorous model ...
122
relacional es un modelo riguroso...

115. relational is the dominant model ...
123
relacional es el modelo dominante...

116. relational ... can be complicated
124
relacional ... puede ser complicado

117. not our fault
125
no es nuestra culpa

118. Codd & Date
126

119. "data is represented as mathematical n-ary
relations, an n-ary relation being a subset of the
Cartesian product of n domains."
127
"los datos se representan como matemáticos n-ary
relaciones, una n-ary relación siendo un subconjunto
de la Producto cartesiano de n dominios ".

120. 128

121. procedural world
129
mundo procedural

122. step by step
130
paso a paso

123. "First, get the total salary paid by each department,
then get the average of these totals,
then list those departments above that average"
131
SQL ?
"primero, obtenga el salario total pagado por cada departamento,
entonces obtener el promedio de estos totales,
entonces enumerar esos departamentos por encima de ese promedio "

124. "First, get the total salary paid by department...
SQL> WITH dept_salaries AS (
2 SELECT dname, SUM(sal) dept_sal
3 FROM emp e, dept d
4 WHERE e.deptno = d.deptno
5 GROUP BY dname),
132

125. "...then get the average of these totals...
6 avg_sal AS ( SELECT AVG(dept_sal) avsal
7 FROM dept_salaries)
133

126. "...then list those departments above average."
8 SELECT * FROM dept_salaries d, avg_sal a
9 WHERE d.dept_sal > a.avsal
10 ORDER BY d.dname;
134

127. SQL> WITH dept_salaries AS (
2 SELECT dname, SUM(sal) dept_sal
3 FROM emp e, dept d
4 WHERE e.deptno = d.deptno
5 GROUP BY dname),
6 avg_sal AS ( SELECT AVG(dept_sal) avsal
7 FROM dept_salaries)
8 SELECT * FROM dept_salaries d, avg_sal a
9 WHERE d.dept_sal > a.avsal
10 ORDER BY d.dname;
135

128. programmer's approach....
136
enfoque del programador....

129. ... relational solution
137
... solución relacional

130. the "finishing touches"
138
los "toques finales"

131. everyone loves JSON
139
todos aman a JSON

132. recall: partitioned outer join
140
recordar: unión externa particionada

133. 141
SQL> with raw_data as (
2 select
3 hrs.hr,
4 t1.room,
5 t1.who
6 from bookings t1
7 partition by (t1.room)
8 right outer join hrs
9 on (hrs.hr = t1.hr)
10 order by
11 hr, room
12 )
13 select
14 json_arrayagg(
15 json_object(key room||to_char(hr) value who )
16 order by hr ) as meetings
17 from raw_data ;
[{"Room1-08":null},
{"Room1-09":"JOHN"},
{"Room1-10":null},
{"Room1-11":"MIKE"},
{"Room1-12":null},
...
...
{"Room2-14":"JILL"},
{"Room2-15":null},
{"Room2-16":"JANE"}]

134. 142
6

135. transposition
143
transposición

136. rows to columns, colums to rows
144
filas a columnas, columnas a filas

137. "I need sales by product
for each quarter....now"
145
"Necesito ventas por producto
por cada trimestre .... ahora "

138. SQL> select product, trunc(txn_date,'Q') mth, sum(quantity) total
3 from SALES
4 group by product,trunc(txn_date,'Q')
5 order by 1,2;
PRODUCT MTH TOTAL
-------------------- --- ----------
CHAINSAW JAN 251473
CHAINSAW APR 254830
CHAINSAW JUL 251994
CHAINSAW OCT 243748
HAMMER JAN 249889
HAMMER APR 256566
HAMMER JUL 252992
HAMMER OCT 249104
SCREW DRIVER JAN 245988
SCREW DRIVER APR 249219
SCREW DRIVER JUL 252128
SCREW DRIVER OCT 244721
SPADE JAN 242434
SPADE APR 254090
SPADE JUL 259613
...
146

139. 147

140. "That’s wrong!...surely you know
I wanted it ACROSS the page"
148
"Eso está mal! ... seguramente lo sabes
yo lo queria A TRAVÉS DE la página"

141. 149

142. pivot clause
150
cláusula pivote

143. SQL> select *
2 from (select product,
3 trunc(txn_date,'Q') mth,
4 quantity
5 from sales )
6 pivot( sum(quantity) for mth in
7 ( 'JAN',
8 'APR',
9 'JUL',
10 'OCT') )
11 order by 1
12 /
PRODUCT 'JAN' 'APR' 'JUL' 'OCT'
-------------------- ---------- ---------- ---------- ----------
CHAINSAW 251473 254830 251994 243748
HAMMER 249889 256566 252992 249104
SCREW DRIVER 245988 249219 252128 244721
SPADE 242434 254090 259613 248428
WHEEL BARROW 243899 249327 252296 254137 151

144. or ...
152

145. "That’s wrong!...surely you know
I wanted it DOWN the page"
153
"Eso está mal! ... seguramente lo sabes
yo lo queria ABAJO la página"

146. SQL> desc SALES_ACROSS
Name Null? Type
----------------------------- -------- -------------
PRODUCT VARCHAR2(20)
Q1 NUMBER
Q2 NUMBER
Q3 NUMBER
Q4 NUMBER
154

147. unpivot clause
155
cláusula no dinámica

148. SQL> select *
2 from SALES_ACROSS
3 UNPIVOT
4 ( quantity for quarter in (Q1,Q2,Q3,Q4) )
5 /
PRODUCT QUARTER QUANTITY
-------------------- ------- ----------
CHAINSAW Q1 251473
CHAINSAW Q2 254830
CHAINSAW Q3 251994
CHAINSAW Q4 243748
HAMMER Q1 249889
HAMMER Q2 256566
HAMMER Q3 252992
HAMMER Q4 249104
SCREW DRIVER Q1 245988
SCREW DRIVER Q2 249219
SCREW DRIVER Q3 252128
SCREW DRIVER Q4 244721
...
row values
become "quantity"
column names
become "quarter" entries
156

149. 157
7

150. most of us know about analytics
158
la mayoría de nosotros sabemos sobre análisis

151. SQL> select row_number() OVER ( order by sal )
2 from emp
3 ...
159
https://bit.ly/analytic_sql

152. 160
"Show me lowest salary for each department..."
SQL> select deptno, min(sal)
2 from emp
3 group by deptno;
"...and I need to know who has that lowest salary"
SQL> select deptno, empno, min(sal)
2 from emp
3 group by deptno;
ORA-00979: not a GROUP BY expression
Muéstrame el salario más bajo para cada departamento ...
... y necesito saber quién tiene el salario más bajo

153. KEEP extension
161

154. SQL> select deptno, min(sal), min(empno)
2 KEEP ( dense_rank FIRST order by sal) empno
3 from emp
4 group by deptno
5 /
DEPTNO MIN(SAL) EMPNO
---------- ---------- ----------
10 1300 7934
20 800 7369
30 950 7900
Emp 7934 has the
lowest salary in dept 10
162
Emp 7934 tiene el salario más
bajo en el departamento 10

155. 163
8

156. every system ...
cada sistema

157. ... I've worked on
165
he trabajado en

158. struggles with cAsE
lucha con caso

159. no correlation ☺
167
but its my fault
sin correlación
pero es mi culpa

160. SQL> select surname
2 from names;
SURNAME
------------------------------
jones
brown
SMITH
sigh...

161. SQL> select initcap(surname)
2 from names;
SURNAME
------------------------------
Jones
Brown
Smith
Mcdonald

162. and it just gets worse...
170
y empeora

163. SQL> select *
2 from customers
3 where cust_name = 'ADAMS';
COUNTRY CREATED CUST_NAME
------------ --------- ------------
AUS 07-NOV-16 ADAMS

164. SQL> select *
2 from customers
3 where upper(cust_name) = 'ADAMS';
COUNTRY CREATED CUST_NAME
------------ --------- ------------
AUS 07-NOV-16 Adams
AUS 07-NOV-16 ADAMS
AUS 07-NOV-16 adams

165. 173

166. 174
SQL> select * from customers
2 where upper(cust_name) = 'ADAMS';

167. 175

168. SQL> select column_name
2 from user_ind_columns
3 where index_name = 'CUST_IX';
COLUMN_NAME
------------------------------
CUST_NAME
SQL> select * from customers
2 where upper(cust_name) = 'ADAMS';
-------------------------------------------------------
| Id | Operation | Name | Rows | Bytes |
-------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 152 |
|* 1 | TABLE ACCESS FULL| CUSTOMERS | 1 | 152 |
-------------------------------------------------------

169. SQL> create index cust_ix
2 on customers ( cust_name );
Index created.
SQL> create index cust_ix2
2 on customers ( upper(cust_name) );
Index created.

170. 178
DML slower
more contention
more redo/undo
DML más lento
más contención
más rehacer / deshacer

171. 179
"not my problem"
"no es mi problema"

172. 180

173. SQL> alter table customers shrink space;
*
ERROR at line 1:
ORA-10631: SHRINK clause should not be specified

174. 182
a better way
una mejor manera

175. 183
column level collation
cotejo a nivel de columna

176. 184

177. SQL> CREATE TABLE CUSTOMERS
2 (
3 COUNTRY VARCHAR2(128),
4 CREATED DATE,
5 CUST_NAME VARCHAR2(150) COLLATE BINARY_CI
6 );
Table created.
"case insenstive"

178. SQL> create index cust_ix
2 on customers ( cust_name);
Index created.
SQL> set autotrace traceonly explain
SQL> select * from customers
2 where cust_name = 'ADAMS';
-----------------------------------------------------------------
| Id | Operation | Name | Rows |
-----------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 |
| 1 | TABLE ACCESS BY INDEX ROWID BATCHED| CUSTOMERS | 1 |
|* 2 | INDEX RANGE SCAN | CUST_IX | 1 |
-----------------------------------------------------------------

179. 187
"what is so special about that?"
Qué tiene de especial eso?

180. SQL> select * from customers
2 where cust_name = 'ADAMS';
COUNTRY CREATED CUST_NAME
------------ --------- ----------------
AUS 07-NOV-16 Adams
AUS 08-NOV-16 ADAMS
AUS 09-NOV-16 adams

181. 189
binary_ci
SQL> select * from customers
2 where cust_name = 'ADAMS';
COUNTRY CREATED CUST_NAME
------------ --------- ------------
AUS 07-NOV-16 Adams
AUS 08-NOV-16 ADAMS
AUS 09-NOV-16 adams

182. 190
binary_ai
SQL> select * from customers
2 where cust_name = 'ADAMS';
COUNTRY CREATED CUST_NAME
------------ --------- -----------
AUS 07-NOV-16 Adams
AUS 08-NOV-16 ADAMS
AUS 09-NOV-16 adams
AUS 10-NOV-16 adáms
adáms

183. 191
column | table | user

184. SQL> alter table people default collation binary_ai;
new columns only
solo columnas nuevas

185. 193
9

186. query block naming
194
consulta de nombres de bloques

187. C#, C++ ESB Tuxedo
Weblogic
Stored
Procedure
195

188. for (int i = 0; i < WinningCombinations.Count; ++i)
{
if (WinningCombinations[i].Investment > 0 &&
WinningCombinations[i].PrimaryDividend > MinDividendDeadHeat)
{
maxDivisor =
Math.Max(maxDivisor, WinningCombinations[i].Divisor);
}
}
for (int i = 0; i < WinningCombinations.Count; ++i)
{
if (WinningCombinations[i].Investment > 0 &&
WinningCombinations[i].PrimaryDividend > MinDividendDeadHeat)
{
WinningCombinations[i].Divisor =
maxDivisor / WinningCombinations[i].Divisor;
sumNewDivisors += WinningCombinations[i].Divisor;
}
}196

189. no comments
197
sin comentarios

190. 198

191. "C# is self-documenting"
199
C# es uno mismo-documentando

192. SQL can be complex
200
SQL puede ser complejo

193. SQL should "self document"
201
SQL debería "auto documentarse"

194. query blocks = self documenting SQL
202
bloques de consulta = SQL autodocumentado

195. select emp.*
from emp,
( select trunc(hiredate,'YYYY'), max(empno) empno
from emp
where empno > 0
group by trunc(hiredate,'YYYY') ) x,
( select deptno, avg(sal)
from emp
group by deptno ) y
where x.empno = emp.empno
and y.deptno = emp.deptno
203

196. Id | Operation | Name |
----------------------------------------------|
0 | SELECT STATEMENT | |
1 | HASH JOIN | |
2 | TABLE ACCESS BY INDEX ROWID | EMP |
3 | NESTED LOOPS | |
4 | VIEW | |
5 | SORT GROUP BY | |
6 | TABLE ACCESS BY INDEX ROWID| EMP |
7 | INDEX FULL SCAN | E2 |
8 | INDEX RANGE SCAN | E1 |
9 | VIEW | |
10 | SORT GROUP BY | |
11 | TABLE ACCESS BY INDEX ROWID | EMP |
12 | INDEX RANGE SCAN | E2 |
204

197. ?
205
select emp.*
from emp,
( select trunc(hiredate,'YYYY'), max(empno) empno
from emp
where empno > 0
group by trunc(hiredate,'YYYY') ) x,
( select deptno, avg(sal)
from emp
group by deptno ) y
where x.empno = emp.empno
and y.deptno = emp.deptno
Id | Operation | Name |
----------------------------------------------|
0 | SELECT STATEMENT | |
1 | HASH JOIN | |
2 | TABLE ACCESS BY INDEX ROWID | EMP |
3 | NESTED LOOPS | |
4 | VIEW | |
5 | SORT GROUP BY | |
6 | TABLE ACCESS BY INDEX ROWID| EMP |
7 | INDEX FULL SCAN | E2 |
8 | INDEX RANGE SCAN | E1 |
9 | VIEW | |
10 | SORT GROUP BY | |
11 | TABLE ACCESS BY INDEX ROWID | EMP |
12 | INDEX RANGE SCAN | E2 |

198. select emp.*
from emp,
( select /*+ QB_NAME(YR_HIRE) */
trunc(hiredate,'YYYY'), max(empno) empno
from emp
where empno > 0
group by trunc(hiredate,'YYYY') ) x,
( select /*+ QB_NAME(AV_SAL) */
deptno, avg(sal)
from emp
group by deptno ) y
where x.empno = emp.empno
and y.deptno = emp.deptno
206
select emp.*
from emp,
( select /*+ QB_NAME(YR_HIRE) */
trunc(hiredate,'YYYY'), max(empno) empno
from emp
where empno > 0
group by trunc(hiredate,'YYYY') ) x,
( select /*+ QB_NAME(AV_SAL) */
deptno, avg(sal)
from emp
group by deptno ) y
where x.empno = emp.empno
and y.deptno = emp.deptno

199. Id | Operation | Name | Query Block
----------------------------------------------|--------------
0 | SELECT STATEMENT | |
1 | HASH JOIN | |
2 | TABLE ACCESS BY INDEX ROWID | EMP |
3 | NESTED LOOPS | |
4 | VIEW | |
5 | SORT GROUP BY | |
6 | TABLE ACCESS BY INDEX ROWID| EMP |
7 | INDEX FULL SCAN | E2 |
8 | INDEX RANGE SCAN | E1 |
9 | VIEW | |
10 | SORT GROUP BY | |
11 | TABLE ACCESS BY INDEX ROWID | EMP |
12 | INDEX RANGE SCAN | E2 |
SEL$1
SEL$1
AV_SAL
AV_SAL
AV_SAL
AV_SAL
SEL$1
YR_HIRE
YR_HIRE
YR_HIRE
YR_HIRE
207

200. 208
10

201. most of us know about analytics #2
209
la mayoría de nosotros sabemos sobre análisis

202. hypothetical analytics
analítica hipotética

203. "if I was paid $3000,
then where would I rank in
each department?"
"si me pagaran $ 3000,
entonces, dónde clasificaría en
cada departamento?"

204. SQL> select
2 deptno,
3 rank(3000) within group
4 ( order by sal ) as ranking
5 from emp
6 group by deptno;
DEPTNO RANKING
---------- ----------
10 2
20 4
30 7
40 2

205. 213
11

206. ignore nulls extension
214
ignorar la extensión nula

207. 215
"fill in the blanks"
"Rellenar los espacios en blanco"

208. 216
SQL> select dt, val
2 from t
3 order by dt;
DT VAL
--------- ----------
02-JAN-11 195
03-JAN-11
04-JAN-11
05-JAN-11
06-JAN-11 129
07-JAN-11
08-JAN-11
09-JAN-11
10-JAN-11 87
11-JAN-11
...
195
195
195
129
129
129
87

209. 217
SQL> select dt, val,
2 case when val is not null
3 then to_char(row_number() over (order by dt),'fm0000')||'-'||val
4 end max_val
5 from t
6 order by dt;
DT VAL MAX_VAL
--------- ---------- -----------
02-JAN-11 195 0001-195
03-JAN-11
04-JAN-11
05-JAN-11
06-JAN-11 129 0005-129
07-JAN-11
08-JAN-11
09-JAN-11
10-JAN-11 87 0009-87
11-JAN-11
...

210. 218
SQL> select dt, val,
2 max(max_val) over (order by dt) max_val_str
3 from ( select dt, val,
4 case when val is not null
5 then to_char(row_number() over (order by dt),'fm0000')||'-'||val
6 end max_val
7 from t ) order by dt;
DT VAL MAX_VAL_STR
--------- ---------- ------------------
02-JAN-11 195 0001-195
03-JAN-11 0001-195
04-JAN-11 0001-195
05-JAN-11 0001-195
06-JAN-11 129 0005-129
07-JAN-11 0005-129
08-JAN-11 0005-129
09-JAN-11 0005-129
10-JAN-11 87 0009-87
11-JAN-11 0009-87
...

211. 219
SQL> select dt, val,
2 to_number(substr(max(max_val) over (order by dt),5)) max_val
3 from ( select dt, val,
4 case when val is not null
5 then to_char(row_number() over (order by dt),'fm0000')||val
6 end max_val
7 from t ) order by dt
8 /
DT VAL MAX_VAL
--------- ---------- ----------
02-JAN-11 195 195
03-JAN-11 195
04-JAN-11 195
05-JAN-11 195
06-JAN-11 129 129
07-JAN-11 129
08-JAN-11 129
09-JAN-11 129
10-JAN-11 87 87
11-JAN-11 87

212. 220
SQL> select dt, val,
2 last_value(val ignore nulls) over (order by dt) val
3 from t
4 order by dt;
DT VAL VAL
--------- ---------- ----------
02-JAN-11 195 195
03-JAN-11 195
04-JAN-11 195
05-JAN-11 195
06-JAN-11 129 129
07-JAN-11 129
08-JAN-11 129
09-JAN-11 129
10-JAN-11 87 87
11-JAN-11 87

213. 221
12

214. STOPKEY optimization
222
Optimización de STOPKEY

215. 223
"employees by hiredate, recent first"
"empleados por fecha de contratación , reciente primero "

216. SQL> select empno, ename, hiredate
2 from emp
3 where rownum <= 5
4 order by hiredate desc;
EMPNO ENAME HIREDATE
---------- ---------- -------------------
7654 MARTIN 28/09/1981 00:00:00
7566 JONES 02/04/1981 00:00:00
7521 WARD 22/02/1981 00:00:00
7499 ALLEN 20/02/1981 00:00:00
7369 SMITH 17/12/1980 00:00:00
224

217. inline view
225
vista en línea

218. SQL> select *
2 from (
3 select empno, ename, hiredate
4 from emp
5 order by hiredate desc
6 )
7 where rownum <= 5;
EMPNO ENAME HIREDATE
---------- ---------- ---------
7876 ADAMS 12-JAN-83
7788 SCOTT 09-DEC-82
7934 MILLER 23-JAN-82
7900 JAMES 03-DEC-81
7902 FORD 03-DEC-81
226

219. SQL> select *
2 from (
3 select
4 empno, ename, hiredate,
5 row_number() over ( order by hiredate desc) rn
6 from emp
7 )
8 where rn <= 5;
227

220. SQL> select empno, ename, hiredate
2 from emp
3 order by hiredate desc
4 fetch first 5 rows only;
EMPNO ENAME HIREDATE
---------- ---------- ---------
7876 ADAMS 12-JAN-83
7788 SCOTT 09-DEC-82
7934 MILLER 23-JAN-82
7900 JAMES 03-DEC-81
7902 FORD 03-DEC-81
228

221. 229
"TL;DR ... my app can do it"
"TL; DR ... mi la aplicación puede hacerlo"

222. public static void Paging(Connection conn ) throws Exception
{
PreparedStatement sql_stmt =
conn.prepareStatement(
"select empno, ename, hiredate
from emp
order by hiredate desc");
ResultSet rset = sql_stmt.executeQuery();
int i = 0;
while( rset.next() )
{
...
i = i + 1;
if (i > 5) {
break;
}
}
rset.close();
}
230

224. demo
232
oc01.sql

225. let the database know
233
deja el base de datos saber

226. SQL> select *
2 from (
3 select empno, ename, hiredate
4 from emp
5 order by hiredate desc
6 )
7 where rownum <= 5;
234
------------------------------------------------
| Id | Operation | Name | Rows |
------------------------------------------------
| 0 | SELECT STATEMENT | | 5 |
|* 1 | COUNT STOPKEY | | |
| 2 | VIEW | | 14 |
|* 3 | SORT ORDER BY STOPKEY| | 14 |
| 4 | TABLE ACCESS FULL | EMP | 14 |
------------------------------------------------

227. SQL> select empno, ename, hiredate
2 from emp
3 order by hiredate desc
4 fetch first 5 rows only;
235
-------------------------------------------------
| Id | Operation | Name | Rows |
-------------------------------------------------
| 0 | SELECT STATEMENT | | 14 |
|* 1 | VIEW | | 14 |
|* 2 | WINDOW SORT PUSHED RANK| | 14 |
| 3 | TABLE ACCESS FULL | EMP | 14 |
-------------------------------------------------

228. 236
13

229. scalar queries
237
consultas escalares

230. SQL> select
2 ( select dname
3 from dept
4 where deptno = e.deptno ) dname,
5 decode(empno, 7499,
6 ( select max(sal) from emp ),
7 -1)
8 from
9 ( select * from emp
10 where sal > 0 ) e
11 where
12 ( select max(hiredate) from emp ) < sysdate
13 /
scalar
anywhere an
expression could be
238

231. "I am not impressed"
239
"No estoy impresionado"

232. SQL> create or replace
2 function CALC_TAX(p int) return number is
3 begin
4 dbms_lock.sleep(1);
5 return p;
6 end;
7 /
Function created.
240

233. SQL> create table T
2 as select rownum r, mod(rownum,5) r1 from dual
3 connect by level <= 30;
Table created.
1,2,3,..., 30
0,1,2,3,4,0,1,2,3,4, ...
241

234. SQL> select r, calc_tax(r1) tax from T;
R TAX
---------- ----------
1 1
2 2
...
28 3
29 4
30 0
30 rows selected.
Elapsed: 00:00:30.01
242

235. SQL> select r,
2 ( select calc_tax(r1) from dual) as tax
3 from T;
R TAX
---------- ----------
1 1
2 2
...
28 3
29 4
30 0
30 rows selected.
Elapsed: 00:00:05.01 243

236. subquery caching
244

237. 245
bonus

238. 246

239. 247

240. 248
"talking" to your database
... makes it faster
"hablando" a su base de datos
... lo hace más rápido

241. 249
example
ejemplo

242. 250
STORES
CUSTOMERS
SALES

243. select prod_id, max(amount)
from stores st,
customers c,
sales s
where s.cust_id = c.cust_id(+)
and c.store_id = st.store_id
and s.amount > 10
group by prod_id
251
hash outer join ? nested loop ?
STORES first ?
sort merge ?

244. ---------------------------------------------------
| Id | Operation | Name | Rows |
---------------------------------------------------
| 0 | SELECT STATEMENT | | 100 |
| 1 | HASH GROUP BY | | 100 |
|* 2 | HASH JOIN | | 990K |
| 3 | NESTED LOOPS SEMI | | 5000 |
| 4 | TABLE ACCESS FULL| CUSTOMERS | 5000 |
|* 5 | INDEX UNIQUE SCAN| STORE_IX | 50 |
|* 6 | TABLE ACCESS FULL | SALES | 990K |
---------------------------------------------------
252

245. 253
can we do better ?
add indexes ?
rewrite query ?
result cache ?
materialized view ?
podemos hacerlo mejor?

246. 254
share your knowledge with the db
oc04.sql
compartir tu conocimiento con el db

247. wrap up
255

248. SQL
256

249. very cool
257
muy genial

250. very powerful
258
muy poderoso

251. less code
259
menos código

252. never too early to start
260
nunca es demasiado temprano para comenzar

254. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |
Thank you!
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