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Your team is building an API for a music store application. The application lets users look up songs and albums by many different data fields (artist, publishing year, genre, etc). As you are working on the prototype for the application, you have a library of about 1000 songs and 100 albums. You have decided to store the data about songs and albums in DynamoDB and your approach for searching has been to run a Scan on the table for the different fields that the user has entered. For instance, if the user wants to find information about rock songs written in 1970, you might scan a Songs table with filter conditions on the genre and publishing year. Does this approach seem like it will work as you scale up to (hopefully) millions of songs and albums? Why or why not? What kind of steps could you do to improve scalability?

Your team is building an API for a music store application. The application lets users look up songs and albums by many different data fields (artist, publishing year, genre, etc). As you are working on the prototype for the application, you have a library of about 1000 songs and 100 albums. You have decided to store the data about songs and albums in DynamoDB and your approach for searching has been to run a Scan on the table for the different fields that the user has entered. For instance, if the user wants to find information about rock songs written in 1970, you might scan a Songs table with filter conditions on the genre and publishing year. Does this approach seem like it will work as you scale up to (hopefully) millions of songs and albums? Why or why not? What kind of steps could you do to improve scalability?

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Your team is building an API for a music store application. The application lets users look up songs and albums by many different data fields (artist, publishing year, genre, etc). As you are working on the prototype for the application, you have a library of about 1000 songs and 100 albums. You have decided to store the data about songs and albums in DynamoDB and your approach for searching has been to run a Scan on the table for the different fields that the user has entered. For instance, if the user wants to find information about rock songs written in 1970, you might scan a Songs table with filter conditions on the genre and publishing year. Does this approach seem like it will work as you scale up to (hopefully) millions of songs and albums? Why or why not? What kind of steps could you do to improve scalability? Edit Tble
Transcribed Image Text:Your team is building an API for a music store application. The application lets users look up songs and albums by many different data fields (artist, publishing year, genre, etc). As you are working on the prototype for the application, you have a library of about 1000 songs and 100 albums. You have decided to store the data about songs and albums in DynamoDB and your approach for searching has been to run a Scan on the table for the different fields that the user has entered. For instance, if the user wants to find information about rock songs written in 1970, you might scan a Songs table with filter conditions on the genre and publishing year. Does this approach seem like it will work as you scale up to (hopefully) millions of songs and albums? Why or why not? What kind of steps could you do to improve scalability? Edit Tble
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