**Understanding Table Relationships and Query Granularity**In a database, different tables often represent distinct entities and their relationships. Here’s an exploration of such a relationship and how it impacts the granularity of query results:- **PAT_ENC Table**: Each row represents a single patient encounter.- **ORDER_MED Table**: Each row represents a single medication order.### Relationship- Each patient encounter can have multiple medication orders. However, each medication order pertains to only one patient encounter.- This relationship is characterized as **one-to-many** from PAT_ENC to ORDER_MED.### Query Scenario- A query is initiated with the `ORDER_MED` table.- When you add the `PAT_ENC` table using an inner join, the granularity of the result set needs to be examined.### Granularity OptionsWhen considering the impact on granularity:- **A**: The granularity remains at one row per patient encounter.- **B**: The granularity remains at one row per medication order.- **C**: The granularity shifts from one row per medication order to one row per patient encounter.- **D**: The granularity shifts from one row per patient encounter to one row per medication order on an encounter.**Correct Answer**: **B** - The granularity stays at one row per medication order.This implies that joining the `PAT_ENC` table does not change the granularity from the perspective of the `ORDER_MED` table. Each row in the result set will still represent a medication order.

A tablе in a databasе is a collеction of rеlatеd data. It is thе basic building block of a…

One row in the PAT_ENC table represents one patient encounter. One row in the ORDER_MED table represents one medication order. One patient encounter can have many medication orders but one medication order can only have one patient encounter. In other words, the cardinality of this PAT_ENC to ORDER_MED relationship is one-to- many. You start a query with ORDER_MED. You then add PAT_ENC using an inner join. What is true about the granularity of the result set before and after adding the PAT_ENC table? A. The granularity stays at one row per patient encounter B. The granularity stays at one row per medication order C. The granularity changes from one row per medication order to one row per patient encounter D. The granularity changes from one row per patient encounter to one row per medication order on an encounter

One row in the PAT_ENC table represents one patient encounter. One row in the ORDER_MED table represents one medication order. One patient encounter can have many medication orders but one medication order can only have one patient encounter. In other words, the cardinality of this PAT_ENC to ORDER_MED relationship is one-to- many. You start a query with ORDER_MED. You then add PAT_ENC using an inner join. What is true about the granularity of the result set before and after adding the PAT_ENC table? A. The granularity stays at one row per patient encounter B. The granularity stays at one row per medication order C. The granularity changes from one row per medication order to one row per patient encounter D. The granularity changes from one row per patient encounter to one row per medication order on an encounter

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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Concept explainers

Intermediate SQL Concepts

A query is a request for data or information from one or more database tables. This information could be presented in the form of pictorials, graphs, or complicated findings which helps in easy interpretation. Structured Query Language (SQL) is the most widely used programming language for retrieving and organizing data from relational databases. Collection of tables with rows and columns is referred to as a database. SQL is the language of databases. It makes it easier to extract specific data from databases, which can then be used for analysis.

Question

**Understanding Table Relationships and Query Granularity**

In a database, different tables often represent distinct entities and their relationships. Here’s an exploration of such a relationship and how it impacts the granularity of query results:

- **PAT_ENC Table**: Each row represents a single patient encounter.
- **ORDER_MED Table**: Each row represents a single medication order.

### Relationship
- Each patient encounter can have multiple medication orders. However, each medication order pertains to only one patient encounter.
- This relationship is characterized as **one-to-many** from PAT_ENC to ORDER_MED.

### Query Scenario
- A query is initiated with the `ORDER_MED` table.
- When you add the `PAT_ENC` table using an inner join, the granularity of the result set needs to be examined.

### Granularity Options
When considering the impact on granularity:

- **A**: The granularity remains at one row per patient encounter.
- **B**: The granularity remains at one row per medication order.
- **C**: The granularity shifts from one row per medication order to one row per patient encounter.
- **D**: The granularity shifts from one row per patient encounter to one row per medication order on an encounter.

**Correct Answer**: **B** - The granularity stays at one row per medication order.

This implies that joining the `PAT_ENC` table does not change the granularity from the perspective of the `ORDER_MED` table. Each row in the result set will still represent a medication order.

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