Below is a table description and its data. The table is not in Third Normal Form (3NF).Explain why.mysql> DESC movies;| Field I Type| Null I Key I Default | Extra+| int(11)| varchar(25)| stars | varchar(100) | YES| id| PRI I NULL| auto_increment I| NO| YESI nameNULLI NULL+------mysql> SELECT * FROM movies;+----+-| id | name| stars+----1 | Finding Nemo | Nemo, Dory, Marlin2 | Zombies|| Meg Donnelly, Milo Manheim|3 I Finding Dory | Nemo, Dory, Marlin, Jenny+---

A relation is said to be in the third normal form if only if the relation is in both first normal…

Below is a table description and its data. The table is not in Third Normal Form (3NF). Explain why. mysql> DESC movies; +-- I Field I Type | Null | Key | DefaultI Extra +---- I auto_increment I I int(11) I varchar(25) | stars I varchar(100) | YES I id | NO | YES I PRI | NULL I NULL | NULL | name | +----- mysql> SELECT * FROM movies; +----+ | id I name | stars +---- 1 | Finding Nemo | Nemo, Dory, Marlin 2 I Zombies | Meg Donnelly, Milo Manheim 3 I Finding Dory I Nemo, Dory, Marlin, Jenny

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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A database has four transactions. Let min sup = 60% and min conf = 80%.cust ID TID items bought (in the form of brand-item category)01 T100 {King’s-Crab, Sunset-Milk, Dairyland-Cheese, Best-Bread}02 T200 {Best-Cheese, Dairyland-Milk, Goldenfarm-Apple, Tasty-Pie, Wonder-Bread}01 T300 {Westcoast-Apple, Dairyland-Milk, Wonder-Bread, Tasty-Pie}03 T400 {Wonder-Bread, Sunset-Milk, Dairyland-Cheese}(a) At the granularity of item category (e.g., itemi could be “Milk”), for the ruletemplate,∀X ∈ transaction, buys(X,item1) ∧ buys(X,item2) ⇒ buys(X,item3) [s,c],list the frequent k-itemset for the largest k, and all the strong association rules(with their support s and confidence c) containing the frequent k-itemset for thelargest k.(b) At the granularity of brand-item category (e.g., itemi could be “Sunset-Milk”),for the rule template,∀X ∈ customer, buys(X,item1) ∧ buys(X,item2) ⇒ buys(X,item3),list the frequent k-itemset for the largest k (but do not print any rules).
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You have the table T = (name, ssn, phone number) representing a person. Each name is uniquely identified by ssn, but the same name can have multiple phone numbers. Suppose you break the tables into two tables T1=(name, ssn) and T2= (name, phone number) a) What are the candidate keys of T, T1, and T2, respectively?