The following code in Spark Streaming takes an input stream of tweets (with each element containing only the message) and transforms it using a window. def is_rt(s): if s.startswith("RT "): return ("RT", 1) else: return ("No-RT", 1) #We split different fields by the break character ;; messages stream.map (lambda 1: 1[1].split(';;')[0]) matches messages.map(is_rt) counts matches. reduceByKeyAndWindow (operator.sub, operator.add, 30, 6) What will counts contain? Select one: O a. Every 30 seconds, the top 10 retweeted messages Ob. O c. The global maximum mention that received the most retweets Every 6 seconds, the sum of mentions from all the tweets O d. Every 6 seconds, the amount of retweet messages compared to non-retweet messages.
The following code in Spark Streaming takes an input stream of tweets (with each element containing only the message) and transforms it using a window. def is_rt(s): if s.startswith("RT "): return ("RT", 1) else: return ("No-RT", 1) #We split different fields by the break character ;; messages stream.map (lambda 1: 1[1].split(';;')[0]) matches messages.map(is_rt) counts matches. reduceByKeyAndWindow (operator.sub, operator.add, 30, 6) What will counts contain? Select one: O a. Every 30 seconds, the top 10 retweeted messages Ob. O c. The global maximum mention that received the most retweets Every 6 seconds, the sum of mentions from all the tweets O d. Every 6 seconds, the amount of retweet messages compared to non-retweet messages.
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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![The following code in Spark Streaming takes an input stream of tweets (with each element containing only the message) and transforms it
using a window.
def is_rt(s):
if s.startswith("RT "):
return ("RT", 1)
else:
return ("No-RT", 1)
#We split different fields by the break character ;;
messages stream.map (lambda 1: 1[1].split(';;')[0])
matches messages.map(is_rt)
counts = matches. reduceByKeyAndWindow(operator.sub, operator.add, 30, 6)
What will counts contain?
Select one:
a. Every 30 seconds, the top 10 retweeted messages
O b.
The global maximum mention that received the most retweets
Every 6 seconds, the sum of mentions from all the tweets
O d. Every 6 seconds, the amount of retweet messages compared to non-retweet messages.
O c.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F0b231203-0fff-46ac-9473-b5b26ff95a69%2F50612e2a-5666-466e-9949-49ba087aa755%2Feug64lf_processed.png&w=3840&q=75)
Transcribed Image Text:The following code in Spark Streaming takes an input stream of tweets (with each element containing only the message) and transforms it
using a window.
def is_rt(s):
if s.startswith("RT "):
return ("RT", 1)
else:
return ("No-RT", 1)
#We split different fields by the break character ;;
messages stream.map (lambda 1: 1[1].split(';;')[0])
matches messages.map(is_rt)
counts = matches. reduceByKeyAndWindow(operator.sub, operator.add, 30, 6)
What will counts contain?
Select one:
a. Every 30 seconds, the top 10 retweeted messages
O b.
The global maximum mention that received the most retweets
Every 6 seconds, the sum of mentions from all the tweets
O d. Every 6 seconds, the amount of retweet messages compared to non-retweet messages.
O c.
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