forked from saisha-satta/MySQL-CheatSheet
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathReferenceGuide.txt
713 lines (484 loc) · 22.6 KB
/
ReferenceGuide.txt
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
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
1. Login to MySQL
a. mysql5 -u mysqladmin -p
2. quit
a. Quit MySQL
3. show databases;
a. Display all databases
4. CREATE DATABASE test2;
a. Create a database
5. USE test2;
a. Make test2 the active database
6. SELECT DATABASE();
a. Show the currently selected database
7. DROP DATABASE IF EXISTS test2;
a. Delete the named database
b. Slide about building tables (2)
8. CREATE TABLE student(
first_name VARCHAR(30) NOT NULL,
last_name VARCHAR(30) NOT NULL,
email VARCHAR(60) NULL,
street VARCHAR(50) NOT NULL,
city VARCHAR(40) NOT NULL,
state CHAR(2) NOT NULL DEFAULT "PA",
zip MEDIUMINT UNSIGNED NOT NULL,
phone VARCHAR(20) NOT NULL,
birth_date DATE NOT NULL,
sex ENUM('M', 'F') NOT NULL,
date_entered TIMESTAMP,
lunch_cost FLOAT NULL,
student_id INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY
);
a. VARCHAR(30) : Characters with an expected max length of 30
b. NOT NULL : Must contain a value
c. NULL : Doesn't require a value
d. CHAR(2) : Contains exactly 2 characters
e. DEFAULT "PA" : Receives a default value of PA
f. MEDIUMINT : Value no greater then 8,388,608
g. UNSIGNED : Can't contain a negative value
h. DATE : Stores a date in the format YYYY-MM-DD
i. ENUM('M', 'F') : Can contain either a M or F
j. TIMESTAMP : Stores date and time in this format YYYY-MM-DD-HH-MM-SS
k. FLOAT: A number with decimal spaces, with a value no bigger than 1.1E38 or smaller than -1.1E38
l. INT : Contains a number without decimals
m. AUTO_INCREMENT : Generates a number automatically that is one greater then the previous row
n. PRIMARY KEY (SLIDE): Unique ID that is assigned to this row of data
I. Uniquely identifies a row or record
II. Each Primary Key must be unique to the row
III. Must be given a value when the row is created and that value cannot be NULL
IV. The original value cannot be changed It should be short
V. Its probably best to auto increment the value of the key
o. Atomic Data & Table Templating
As your database increases in size, you are going to want everything to be organized, so that it can perform your queries quickly. If your tables are set up properly, your database will be able to crank through hundreds of thousands of bits of data in seconds.
How do you know how to best set up your tables though? Just follow some simple rules:
Every table should focus on describing just one thing. Ex. Customer Table would have name, age, location, contact information. It shouldnt contain lists of anything such as interests, job history, past address, products purchased, etc.
After you decide what one thing your table will describe, then decide what things you need to describe that thing. Refer to the customer example given in the last step.
Write out all the ways to describe the thing and if any of those things requires multiple inputs, pull them out and create a new table for them. For example, a list of past employers.
Once your table values have been broken down, we refer to these values as being atomic. Be careful not to break them down to a point in which the data is harder to work with. It might make sense to create a different variable for the house number, street name, apartment number, etc.; but by doing so you may make your self more work? That decision is up to you?
p. Some additional rules to help you make your data atomic: Dont have multiple columns with the same sort of information. Ex. If you wanted to include a employment history you should create job1, job2, job3 columns. Make a new table with that data instead.
Dont include multiple values in one cell. Ex. You shouldnt create a cell named jobs and then give it the value: McDonalds, Radio Shack, Walmart, Normalized Tables
q. What does normalized mean?
Normalized just means that the database is organized in a way that is considered standardized by professional SQL programmers. So if someone new needs to work with the tables theyll be able to understand how to easily.
Another benefit to normalizing your tables is that your queries will run much quicker and the chance your database will be corrupted will go down.
r. What are the rules for creating normalized tables:
The tables and variables defined in them must be atomic Each row must have a Primary Key defined. Like your social security number identifies you, the Primary Key will identify your row.
You also want to eliminate using the same values repeatedly in your columns. Ex. You wouldnt want a column named instructors, in which you hand typed in their names each time. You instead, should create an instructor table and link to its key.
Every variable in a table should directly relate to the primary key. Ex. You should create tables for all of your customers potential states, cities and zip codes, instead of including them in the main customer table. Then you would link them using foreign keys. Note: Many people think this last rule is overkill and can be ignored!
No two columns should have a relationship in which when one changes another must also change in the same table. This is called a Dependency. Note: This is another rule that is sometimes ignored.
------------ Numeric Types ------------
TINYINT: A number with a value no bigger than 127 or smaller than -128
SMALLINT: A number with a value no bigger than 32,768 or smaller than -32,767
MEDIUM INT: A number with a value no bigger than 8,388,608 or smaller than -8,388,608
INT: A number with a value no bigger than 2^31 or smaller than 2^31 1
BIGINT: A number with a value no bigger than 2^63 or smaller than 2^63 1
FLOAT: A number with decimal spaces, with a value no bigger than 1.1E38 or smaller than -1.1E38
DOUBLE: A number with decimal spaces, with a value no bigger than 1.7E308 or smaller than -1.7E308
------------ String Types ------------
CHAR: A character string with a fixed length
VARCHAR: A character string with a length thats variable
BLOB: Can contain 2^16 bytes of data
ENUM: A character string that has a limited number of total values, which you must define.
SET: A list of legal possible character strings. Unlike ENUM, a SET can contain multiple values in comparison to the one legal value with ENUM.
------------ Date & Time Types ------------
DATE: A date value with the format of (YYYY-MM-DD)
TIME: A time value with the format of (HH:MM:SS)
DATETIME: A time value with the format of (YYYY-MM-DD HH:MM:SS)
TIMESTAMP: A time value with the format of (YYYYMMDDHHMMSS)
YEAR: A year value with the format of (YYYY)
9. DESCRIBE student;
a. Show the table set up
10. INSERT INTO student VALUES('Dale', 'Cooper', '[email protected]',
'123 Main St', 'Yakima', 'WA', 98901, '792-223-8901', "1959-2-22",
'M', NOW(), 3.50, NULL);
a. Inserting Data into a Table
b. INSERT INTO student VALUES('Harry', 'Truman', '[email protected]',
'202 South St', 'Vancouver', 'WA', 98660, '792-223-9810', "1946-1-24",
'M', NOW(), 3.50, NULL);
INSERT INTO student VALUES('Shelly', 'Johnson', '[email protected]',
'9 Pond Rd', 'Sparks', 'NV', 89431, '792-223-6734', "1970-12-12",
'F', NOW(), 3.50, NULL);
INSERT INTO student VALUES('Bobby', 'Briggs', '[email protected]',
'14 12th St', 'San Diego', 'CA', 92101, '792-223-6178', "1967-5-24",
'M', NOW(), 3.50, NULL);
INSERT INTO student VALUES('Donna', 'Hayward', '[email protected]',
'120 16th St', 'Davenport', 'IA', 52801, '792-223-2001', "1970-3-24",
'F', NOW(), 3.50, NULL);
INSERT INTO student VALUES('Audrey', 'Horne', '[email protected]',
'342 19th St', 'Detroit', 'MI', 48222, '792-223-2001', "1965-2-1",
'F', NOW(), 3.50, NULL);
INSERT INTO student VALUES('James', 'Hurley', '[email protected]',
'2578 Cliff St', 'Queens', 'NY', 11427, '792-223-1890', "1967-1-2",
'M', NOW(), 3.50, NULL);
INSERT INTO student VALUES('Lucy', 'Moran', '[email protected]',
'178 Dover St', 'Hollywood', 'CA', 90078, '792-223-9678', "1954-11-27",
'F', NOW(), 3.50, NULL);
INSERT INTO student VALUES('Tommy', 'Hill', '[email protected]',
'672 High Plains', 'Tucson', 'AZ', 85701, '792-223-1115', "1951-12-21",
'M', NOW(), 3.50, NULL);
INSERT INTO student VALUES('Andy', 'Brennan', '[email protected]',
'281 4th St', 'Jacksonville', 'NC', 28540, '792-223-8902', "1960-12-27",
'M', NOW(), 3.50, NULL);
11. SELECT * FROM student;
a. Shows all the student data
12. CREATE TABLE class(
name VARCHAR(30) NOT NULL,
class_id INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY);
a. Create a separate table for all classes
13. show tables;
a. Show all the tables
14. INSERT INTO class VALUES
('English', NULL), ('Speech', NULL), ('Literature', NULL),
('Algebra', NULL), ('Geometry', NULL), ('Trigonometry', NULL),
('Calculus', NULL), ('Earth Science', NULL), ('Biology', NULL),
('Chemistry', NULL), ('Physics', NULL), ('History', NULL),
('Art', NULL), ('Gym', NULL);
a. Insert all possible classes
b. select * from class;
15. CREATE TABLE test(
date DATE NOT NULL,
type ENUM('T', 'Q') NOT NULL,
class_id INT UNSIGNED NOT NULL,
test_id INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY);
a. class_id is a foreign key
I. Used to make references to the Primary Key of another table
II. Example: If we have a customer and city table. If the city table had a column which listed the unique primary key of all the customers, that Primary Key listing in the city table would be considered a Foreign Key.
III. The Foreign Key can have a different name from the Primary Key name.
IV. The value of a Foreign Key can have the value of NULL.
V. A Foreign Key doesnt have to be unique
16. CREATE TABLE score(
student_id INT UNSIGNED NOT NULL,
event_id INT UNSIGNED NOT NULL,
score INT NOT NULL,
PRIMARY KEY(event_id, student_id));
a. We combined the event and student id to make sure we don't have
duplicate scores and it makes it easier to change scores
b. Since neither the event or the student ids are unique on their
own we are able to make them unique by combining them
17. CREATE TABLE absence(
student_id INT UNSIGNED NOT NULL,
date DATE NOT NULL,
PRIMARY KEY(student_id, date));
a. Again we combine 2 items that aren't unique to generate a
unique key
18. Add a max score column to test
a. ALTER TABLE test ADD maxscore INT NOT NULL AFTER type;
b. DESCRIBE test;
19. Insert Tests
a. INSERT INTO test VALUES
('2014-8-25', 'Q', 15, 1, NULL),
('2014-8-27', 'Q', 15, 1, NULL),
('2014-8-29', 'T', 30, 1, NULL),
('2014-8-29', 'T', 30, 2, NULL),
('2014-8-27', 'Q', 15, 4, NULL),
('2014-8-29', 'T', 30, 4, NULL);
b. select * FROM test;
20. ALTER TABLE score CHANGE event_id test_id
INT UNSIGNED NOT NULL;
a. Change the name of event_id in score to test_id
b. DESCRIBE score;
21. Enter student scores
a. INSERT INTO score VALUES
(1, 1, 15),
(1, 2, 14),
(1, 3, 28),
(1, 4, 29),
(1, 5, 15),
(1, 6, 27),
(2, 1, 15),
(2, 2, 14),
(2, 3, 26),
(2, 4, 28),
(2, 5, 14),
(2, 6, 26),
(3, 1, 14),
(3, 2, 14),
(3, 3, 26),
(3, 4, 26),
(3, 5, 13),
(3, 6, 26),
(4, 1, 15),
(4, 2, 14),
(4, 3, 27),
(4, 4, 27),
(4, 5, 15),
(4, 6, 27),
(5, 1, 14),
(5, 2, 13),
(5, 3, 26),
(5, 4, 27),
(5, 5, 13),
(5, 6, 27),
(6, 1, 13),
(6, 2, 13),
# Missed this day (6, 3, 24),
(6, 4, 26),
(6, 5, 13),
(6, 6, 26),
(7, 1, 13),
(7, 2, 13),
(7, 3, 25),
(7, 4, 27),
(7, 5, 13),
# Missed this day (7, 6, 27),
(8, 1, 14),
# Missed this day (8, 2, 13),
(8, 3, 26),
(8, 4, 23),
(8, 5, 12),
(8, 6, 24),
(9, 1, 15),
(9, 2, 13),
(9, 3, 28),
(9, 4, 27),
(9, 5, 14),
(9, 6, 27),
(10, 1, 15),
(10, 2, 13),
(10, 3, 26),
(10, 4, 27),
(10, 5, 12),
(10, 6, 22);
22. Fill in the absences
a. INSERT INTO absence VALUES
(6, '2014-08-29'),
(7, '2014-08-29'),
(8, '2014-08-27');
23. SELECT * FROM student;
a. Shows everything in the student table
24. SELECT FIRST_NAME, last_name
FROM student;
a. Show just selected data from the table (Not Case Sensitive)
25. RENAME TABLE
absence to absences,
class to classes,
score to scores,
student to students,
test to tests;
a. Change all the table names SHOW TABLES;
26. SELECT first_name, last_name, state
FROM students
WHERE state="WA";
a. Show every student born in the state of Washington
27. SELECT first_name, last_name, birth_date
FROM students
WHERE YEAR(birth_date) >= 1965;
a. You can compare values with =, >, <, >=, <=, !=
b. To get the month, day or year of a date use MONTH(), DAY(), or YEAR()
27. SELECT first_name, last_name, birth_date
FROM students
WHERE MONTH(birth_date) = 2 OR state="CA";
a. AND, && : Returns a true value if both conditions are true
b. OR, || : Returns a true value if either condition is true
c. NOT, ! : Returns a true value if the operand is false
28. SELECT last_name, state, birth_date
FROM students
WHERE DAY(birth_date) >= 12 && (state="CA" || state="NV");
a. You can use compound logical operators
29. SELECT last_name
FROM students
WHERE last_name IS NULL;
SELECT last_name
FROM students
WHERE last_name IS NOT NULL;
a. If you want to check for NULL you must use IS NULL or IS NOT NULL
30. SELECT first_name, last_name
FROM students
ORDER BY last_name;
a. ORDER BY allows you to order results. To change the order use
ORDER BY col_name DESC;
31. SELECT first_name, last_name, state
FROM students
ORDER BY state DESC, last_name ASC;
a. If you use 2 ORDER BYs it will order one and then the other
32. SELECT first_name, last_name
FROM students
LIMIT 5;
a. Use LIMIT to limit the number of results
33. SELECT first_name, last_name
FROM students
LIMIT 5, 10;
a. You can also get results 5 through 10
34. SELECT CONCAT(first_name, " ", last_name) AS 'Name',
CONCAT(city, ", ", state) AS 'Hometown'
FROM students;
a. CONCAT is used to combine results
b. AS provides for a way to define the column name
35. SELECT last_name, first_name
FROM students
WHERE first_name LIKE 'D%' OR last_name LIKE '%n';
a. Matchs any first name that starts with a D, or ends with a n
b. % matchs any sequence of characters
36. SELECT last_name, first_name
FROM students
WHERE first_name LIKE '___y';
a. _ matchs any single character
37. SELECT DISTINCT state
FROM students
ORDER BY state;
a. Returns the states from which students are born because DISTINCT
eliminates duplicates in results
38. SELECT COUNT(DISTINCT state)
FROM students;
a. COUNT returns the number of matchs, so we can get the number
of DISTINCT states from which students were born
39. SELECT COUNT(*)
FROM students;
SELECT COUNT(*)
FROM students
WHERE sex='M';
a. COUNT returns the total number of records as well as the total
number of boys
40. SELECT sex, COUNT(*)
FROM students
GROUP BY sex;
a. GROUP BY defines how the results will be grouped
41. SELECT MONTH(birth_date) AS 'Month', COUNT(*)
FROM students
GROUP BY Month
ORDER BY Month;
a. We can get each month in which we have a birthday and the total
number for each month
42. SELECT state, COUNT(state) AS 'Amount'
FROM students
GROUP BY state
HAVING Amount > 1;
a. HAVING allows you to narrow the results after the query is executed
43. SELECT
test_id AS 'Test',
MIN(score) AS min,
MAX(score) AS max,
MAX(score)-MIN(score) AS 'range',
SUM(score) AS total,
AVG(score) AS average
FROM scores
GROUP BY test_id;
a. There are many math functions built into MySQL. Range had to be quoted because it is a reserved word.
b. You can find all reserved words here http://dev.mysql.com/doc/mysqld-version-reference/en/mysqld-version-reference-reservedwords-5-5.html
44. The Built in Numeric Functions (SLIDE)
ABS(x) : Absolute Number: Returns the absolute value of the variable x.
ACOS(x), ASIN(x), ATAN(x), ATAN2(x,y), COS(x), COT(x), SIN(x), TAN(x) :Trigonometric Functions : They are used to relate the angles of a triangle to the lengths of the sides of a triangle.
AVG(column_name) : Average of Column : Returns the average of all values in a column. SELECT AVG(column_name) FROM table_name;
CEILING(x) : Returns the smallest number not less than x.
COUNT(column_name) : Count : Returns the number of non null values in the column. SELECT COUNT(column_name) FROM table_name;
DEGREES(x) : Returns the value of x, converted from radians to degrees.
EXP(x) : Returns e^x
FLOOR(x) : Returns the largest number not grater than x
LOG(x) : Returns the natural logarithm of x
LOG10(x) : Returns the logarithm of x to the base 10
MAX(column_name) : Maximum Value : Returns the maximum value in the column. SELECT MAX(column_name) FROM table_name;
MIN(column_name) : Minimum : Returns the minimum value in the column. SELECT MIN(column_name) FROM table_name;
MOD(x, y) : Modulus : Returns the remainder of a division between x and y
PI() : Returns the value of PI
POWER(x, y) : Returns x ^ Y
RADIANS(x) : Returns the value of x, converted from degrees to radians
RAND() : Random Number : Returns a random number between the values of 0.0 and 1.0
ROUND(x, d) : Returns the value of x, rounded to d decimal places
SQRT(x) : Square Root : Returns the square root of x
STD(column_name) : Standard Deviation : Returns the Standard Deviation of values in the column. SELECT STD(column_name) FROM table_name;
SUM(column_name) : Summation : Returns the sum of values in the column. SELECT SUM(column_name) FROM table_name;
TRUNCATE(x) : Returns the value of x, truncated to d decimal places
45. SELECT * FROM absences;
DESCRIBE scores;
SELECT student_id, test_id
FROM scores
WHERE student_id = 6;
INSERT INTO scores VALUES
(6, 3, 24);
DELETE FROM absences
WHERE student_id = 6;
a. Look up students that missed a test
b. Look up the specific test missed by student 6
c. Insert the make up test result
d. Delete the record in absences
46. ALTER TABLE absences
ADD COLUMN test_taken CHAR(1) NOT NULL DEFAULT 'F'
AFTER student_id;
a. Use ALTER to add a column to a table. You can use AFTER
or BEFORE to define the placement
47. ALTER TABLE absences
MODIFY COLUMN test_taken ENUM('T','F') NOT NULL DEFAULT 'F';
a. You can change the data type with ALTER and MODIFY COLUMN
48. ALTER TABLE absences
DROP COLUMN test_taken;
a. ALTER and DROP COLUMN can delete a column
49. ALTER TABLE absences
CHANGE student_id student_id INT UNSIGNED NOT NULL;
a. You can change the data type with ALTER and CHANGE
50. SELECT *
FROM scores
WHERE student_id = 4;
UPDATE scores SET score=25
WHERE student_id=4 AND test_id=3;
a. Use UPDATE to change a value in a row
51. SELECT first_name, last_name, birth_date
FROM students
WHERE birth_date
BETWEEN '1960-1-1' AND '1970-1-1';
a. Use BETWEEN to find matches between a minimum and maximum
52. SELECT first_name, last_name
FROM students
WHERE first_name IN ('Bobby', 'Lucy', 'Andy');
a. Use IN to narrow results based on a predefined list of options
53. SELECT student_id, date, score, maxscore
FROM tests, scores
WHERE date = '2014-08-25'
AND tests.test_id = scores.test_id;
a. To combine data from multiple tables you can perform a JOIN
by matching up common data like we did here with the test ids
b. You have to define the 2 tables to join after FROM
c. You have to define the common data between the tables after WHERE
54. SELECT scores.student_id, tests.date, scores.score, tests.maxscore
FROM tests, scores
WHERE date = '2014-08-25'
AND tests.test_id = scores.test_id;
a. It is good to qualify the specific data needed by proceeding
it with the tables name and a period
b. The test_id that is in scores is an example of a foreign key, which
is a reference to a primary key in the tests table
55. SELECT CONCAT(students.first_name, " ", students.last_name) AS Name,
tests.date, scores.score, tests.maxscore
FROM tests, scores, students
WHERE date = '2014-08-25'
AND tests.test_id = scores.test_id
AND scores.student_id = students.student_id;
a. You can JOIN more then 2 tables as long as you define the like
data between those tables
56. SELECT students.student_id,
CONCAT(students.first_name, " ", students.last_name) AS Name,
COUNT(absences.date) AS Absences
FROM students, absences
WHERE students.student_id = absences.student_id
GROUP BY students.student_id;
a. If we wanted a list of the number of absences per student we
have to group by student_id or we would get just one result
57. SELECT students.student_id,
CONCAT(students.first_name, " ", students.last_name) AS Name,
COUNT(absences.date) AS Absences
FROM students LEFT JOIN absences
ON students.student_id = absences.student_id
GROUP BY students.student_id;
a. If we need to include all information from the table listed
first "FROM students", even if it doesn't exist in the table on
the right "LEFT JOIN absences", we can use a LEFT JOIN.
58. SELECT students.first_name,
students.last_name,
scores.test_id,
scores.score
FROM students
INNER JOIN scores
ON students.student_id=scores.student_id
WHERE scores.score <= 15
ORDER BY scores.test_id;
a. An INNER JOIN gets all rows of data from both tables if there
is a match between columns in both tables
b. Here I'm getting all the data for all quizzes and matching that
data up based on student ids
59. One-to-One Relationship (SLIDE)
a. In this One-to-One relationship there can only be one social security number per person. Hence, each social security number can be associated with one person. As well, one person in the other table only matches up with one social security number.
b. One-to-One relationships can be identified also in that the foreign keys never duplicate across all rows.
c. If you are confused by the One-to-One relationship it is understandable, because they are not often used. Most of the time if a value never repeats it should remain in the parent table being customer in this case. Just understand that in a One-to-One relationship, exactly one row in a parent table is related to exactly one row of a child table.
60. One-to-Many Relationship
a. When we are talking about One-to-Many relationships think about the table diagram here. If you had a list of customers chances are some of them would live in the same state. Hence, in the state column in the parent table, it would be common to see a duplication of states. In this example, each customer can only live in one state so their would only be one id used for each customer.
b. Just remember that, a One-to-Many relationship is one in which a record in the parent table can have many matching records in the child table, but a record in the child can only match one record in the parent. A customer can choose to live in any state, but they can only live in one at a time.
61. Many-to-Many Relationship
a. Many people can own many different products. In this example, you can see an example of a Many-to-Many relationship. This is a sign of a non-normalized database, by the way. How could you ever access this information:
b. If a customer buys more than one product, you will have multiple product ids associated with each customer. As well, you would have multiple customer ids associated with each product.