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che online playground: tice that two duplicate data regard as two data. an example, for location 'Fallowfield', you may count 2 for below tw _id" : 3, "address" : "317 Wilmslow Road", "location" : "Fallowfield", id" : 4, "address" : "317 Wilmslow Road", "location" : "Fallowfield", "nai "nar a. Write a query using a map-reduce pipeline to get the count of re each location. b. Write a query to get the average rating for each location withou

che online playground: tice that two duplicate data regard as two data. an example, for location 'Fallowfield', you may count 2 for below tw _id" : 3, "address" : "317 Wilmslow Road", "location" : "Fallowfield", id" : 4, "address" : "317 Wilmslow Road", "location" : "Fallowfield", "nai "nar a. Write a query using a map-reduce pipeline to get the count of re each location. b. Write a query to get the average rating for each location withou

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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Problem 4. Based on the MongoDB "Restaurants database" (on "restaurant" collection) in the online playground: Notice that two duplicate data regard as two data. As an example, for location 'Fallowfield', you may count 2 for below two identical data. { "_id" : 3, "address" : "317 Wilmslow Road", "location" : "Fallowfield", "name" : "23rd Street { "_id" : 4, "address" : "317 Wilmslow Road", "location" : "Fallowfield", "name" : "23rd Street a. Write a query using a map-reduce pipeline to get the count of restaurants for each location. b. Write a query to get the average rating for each location without using a map- reduce pipeline. c. Write a query to get the type of food with highest average rating without using a map-reduce pipeline.
Transcribed Image Text:Problem 4. Based on the MongoDB "Restaurants database" (on "restaurant" collection) in the online playground: Notice that two duplicate data regard as two data. As an example, for location 'Fallowfield', you may count 2 for below two identical data. { "_id" : 3, "address" : "317 Wilmslow Road", "location" : "Fallowfield", "name" : "23rd Street { "_id" : 4, "address" : "317 Wilmslow Road", "location" : "Fallowfield", "name" : "23rd Street a. Write a query using a map-reduce pipeline to get the count of restaurants for each location. b. Write a query to get the average rating for each location without using a map- reduce pipeline. c. Write a query to get the type of food with highest average rating without using a map-reduce pipeline.
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