# Problems 15 and 16 are based on the following query: SELECT P_CODE, P_QOH*P_PRICE FROM PRODUCT WHERE P_QOH*P_PRICE &gt; (SELECT AVG(P_QOH*P_PRICE) FROM PRODUCT); What is the likely data sparsity of the P_QOH and P_PRICE columns?

### Database Systems: Design, Implemen...

12th Edition
Carlos Coronel + 1 other
Publisher: Cengage Learning
ISBN: 9781305627482

Chapter
Section

### Database Systems: Design, Implemen...

12th Edition
Carlos Coronel + 1 other
Publisher: Cengage Learning
ISBN: 9781305627482
Chapter 11, Problem 15P
Textbook Problem
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## Problems 15 and 16 are based on the following query: SELECT P_CODE, P_QOH*P_PRICE FROM PRODUCT WHERE P_QOH*P_PRICE > (SELECT AVG(P_QOH*P_PRICE) FROM PRODUCT); What is the likely data sparsity of the P_QOH and P_PRICE columns?

Program Plan Intro

Data sparsity:

The number of unique values a column could contain is referred as data sparsity; the data sparsity can be classified into two types and they are as follows:

• Low sparsity.
• When a column contains minimum number of unique values is called as low sparsity.
• Consider the column named gender; gender can contain only two different values namely ‘male’ and ‘female’ and this is considered to be a low sparsity.
• High sparsity.
• When a column contains maximum number of unique values is called as low sparsity.
• Consider the column named Birthdate; Birthdate can contain multiple different values and this is considered to be a high sparsity.

The appropriate use of index can be determined by knowing the sparsity.

### Explanation of Solution

Data sparsity of the “P_QOH” and “P_PRICE”:

• The data sparsity for the attributes “P_QOH” and “P_PRICE” is, it could contain high sparsity because the column in the PROD...

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