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Answers to Quizzes and Final Exam
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77. a, d 78. b, c, d 79. a, e 80. a, b, c, e 81. a, d, e 82. a, b, c, d 83. a, d 84.
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SELECT MOVIE_ID, MOVIE_TITLE FROM MOVIE WHERE MPAA_RATING_CODE IN ('G','PG','PG-13');
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SELECT FROM WHERE OR OR COUNT(*) MOVIE LOWER(MOVIE_TITLE) LIKE 'of %' LOWER(MOVIE_TITLE) LIKE '% of' LOWER(MOVIE_TITLE) LIKE '% of %';
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SELECT COUNT(*) FROM CUSTOMER_ACCOUNT WHERE DATE_TERMINATED IS NOT NULL;
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SELECT MIN(RETAIL_PRICE_VHS) AS MIN_PRICE, MAX(RETAIL_PRICE_VHS) AS MAX_PRICE FROM MOVIE;
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SELECT MOVIE_GENRE_CODE, ROUND(AVG(RETAIL_PRICE_DVD),2) AS AVG_PRICE FROM MOVIE GROUP BY MOVIE_GENRE_CODE;
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SELECT SUM(CUSTOMER_DEPOSIT_AMOUNT) AS TOTAL FROM CUSTOMER_ACCOUNT;
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SELECT MOVIE_ID, MOVIE_TITLE FROM MOVIE A
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WHERE EXISTS (SELECT MOVIE_ID FROM MOVIE_RENTAL B WHERE A.MOVIE_ID = B.MOVIE_ID);
SQL Demysti ed
SELECT FROM WHERE GROUP A.MOVIE_ID, A.MOVIE_TITLE MOVIE A, MOVIE_RENTAL B A.MOVIE_ID = B.MOVIE_ID BY A.MOVIE_ID, A.MOVIE_TITLE;
The DISTINCT keyword may be used in place of the GROUP BY clause but is usually less ef cient. 92.
SELECT MOVIE_TITLE, COUNT(*) AS DVD_COPIES FROM MOVIE JOIN MOVIE_COPY ON MOVIE.MOVIE_ID = MOVIE_COPY.MOVIE_ID WHERE MEDIA_FORMAT = 'D' GROUP BY MOVIE_TITLE;
SELECT CUSTOMER_ACCOUNT_ID, COUNT(*) AS NUM_RENTALS FROM CUSTOMER_TRANSACTION A JOIN MOVIE_RENTAL B ON A.TRANSACTION_ID = B.TRANSACTION_ID GROUP BY CUSTOMER_ACCOUNT_ID;
SELECT FLOOR(AVG(RETAIL_PRICE_DVD)) AS AVERAGE_DVD_PRICE FROM MOVIE;
SELECT ASCII(';');
For Oracle, the clause FROM DUAL must be added. 96.
SELECT REPLACE(EMPLOYEE_TAX_ID,'-',' ') AS EMPLOYEE_TAX_ID FROM EMPLOYEE;
SELECT MOVIE_TITLE, CASE WHEN RETAIL_PRICE_DVD IS NULL THEN 'None' WHEN RETAIL_PRICE_DVD = 0 THEN 'None' WHEN RETAIL_PRICE_DVD < 20 THEN 'Bargain'
Answers to Quizzes and Final Exam
WHEN RETAIL_PRICE_DVD < 30 THEN 'Moderate' WHEN RETAIL_PRICE_DVD >= 30 THEN 'Premium' END AS PRICE_CATEGORY FROM MOVIE ORDER BY MOVIE_TITLE;
INSERT INTO MOVIE (MOVIE_ID, MOVIE_GENRE_CODE, MPAA_RATING_CODE, MOVIE_TITLE) VALUES (999, 'Drama', 'NR', 'How the Database Was Won');
UPDATE MOVIE SET RETAIL_PRICE_DVD = RETAIL_PRICE_DVD + 1 WHERE RETAIL_PRICE_DVD IS NOT NULL;
DELETE FROM MOVIE_GENRE WHERE MOVIE_GENRE_CODE NOT IN (SELECT DISTINCT MOVIE_GENRE_CODE FROM MOVIE);
The DISTINCT is not absolutely necessary, but it makes the list of values in the subselect much shorter, which makes the statement far more ef cient.
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INDEX
References to gures and illustrations are in italics. % (percent), 103 _ (underscore), 103 <> (not equal operator), 140 , (commas), 46 - (hyphens), 46 ; (semicolons), 45 (single quotes), 46 autocommit mode, 207, 208, 209, 210 AutoNumber data type, 61
BETWEEN operator, 101 103 BFILE data type, 64 big integer data types, 58 BIGINT data type, 61, 66, 68 BIGSERIAL data type, 68 BINARY data type, 62 binary large object types, 60 BIT data type, 62, 67, 69 BIT VARYING data type, 69 bit-map indexes, 248 249 BLOB data type, 63, 64, 67 BOOLEAN data type, 60, 66, 68 Boyce-Codd normal form, 21 buffers, 223 224, 240 241 BYTEA data type, 68
aggregate functions, 117 118 ALTER TABLE statement, 78 80 American National Standards Institute. See ANSI AND operator, 97 ANSI, 43, 44 answers to quizzes and nal exam, 281 301 APIs, 226 application programming interfaces. See APIs applications, 221 approximate numeric data types, 57 arithmetic operators, 108 109 arrays, 69 ASC keyword, 77 ASCII function, 153 asynchronous I/O, 241 attributes, multivalued, 13 16
Call Level Interface (CLI), 226 Cartesian product, 128 129 CASE expression, 166 searched, 168 169 simple form, 166 168 case sensitivity, 45, 104
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CAST function, 117 CEILING (CEIL) function, 155 CHAR BINARY data type, 67 CHAR (CHR) function, 153 154 CHAR data type, 63, 64, 66 vs. VARCHAR data type, 241 242 CHARACTER (CHAR) data type, 61, 68 character data types, 55 56 character functions, 110 115, 150 154 character large object types, 60 CHARACTER VARYING data type, 68 CHECK constraints, 9, 73, 75, 175 clauses, 45 clients, 39 CLOB data type, 63, 65 CLOSE statement, 225 226 clustered indexes, 252 Codd, E.F., 3, 10, 21 collection types, 55 column functions, 110 column-level security, 200 columns de ned, 54 unnecessary, 245 command-line interfaces, 40 commas, 46 comments, multiline, 46 Common Language Runtime (CLR), 228 229 comparison operators, 94 97 composite data types, 69 compound query operators, 120 121 computationally complete SQL, 229 230 concurrent update problems, 211 212 conjunctive operators, 97 100 connecting to the database, client/server arrangement, 39 40 constraints, 7 9 constructed data types, 55
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