print(sortedPriceProducts)
Step 10 : Now sort data based on product_price as ascending and product_id in ascending order, using takeOrdered{) function.
#Dont forget to cast string
#Tuple as key ((price,id),name) sortedPriceProducts=nonemptyJines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

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print(sortedPriceProducts)
Step 10 : Now sort data based on product_price as ascending and product_id in ascending order, using takeOrdered{) function.
#Dont forget to cast string
#Tuple as key ((price,id),name) sortedPriceProducts=nonemptyJines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

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print(sortedPriceProducts)
Step 10 : Now sort data based on product_price as ascending and product_id in ascending order, using takeOrdered{) function.
#Dont forget to cast string
#Tuple as key ((price,id),name) sortedPriceProducts=nonemptyJines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

Dumps."> print(sortedPriceProducts)
Step 10 : Now sort data based on product_price as ascending and product_id in ascending order, using takeOrdered{) function.
#Dont forget to cast string
#Tuple as key ((price,id),name) sortedPriceProducts=nonemptyJines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

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print(sortedPriceProducts)
Step 10 : Now sort data based on product_price as ascending and product_id in ascending order, using takeOrdered{) function.
#Dont forget to cast string
#Tuple as key ((price,id),name) sortedPriceProducts=nonemptyJines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

dumps,
print(sortedPriceProducts)
Step 10 : Now sort data based on product_price as ascending and product_id in ascending order, using takeOrdered{) function.
#Dont forget to cast string
#Tuple as key ((price,id),name) sortedPriceProducts=nonemptyJines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

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print(sortedPriceProducts)
Step 10 : Now sort data based on product_price as ascending and product_id in ascending order, using takeOrdered{) function.
#Dont forget to cast string
#Tuple as key ((price,id),name) sortedPriceProducts=nonemptyJines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

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Exam Code:
print(sortedPriceProducts)
Step 10 : Now sort data based on product_price as ascending and product_id in ascending order, using takeOrdered{) function.
#Dont forget to cast string
#Tuple as key ((price,id),name) sortedPriceProducts=nonemptyJines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

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    print(sortedPriceProducts)
    Step 10 : Now sort data based on product_price as ascending and product_id in ascending order, using takeOrdered{) function.
    #Dont forget to cast string
    #Tuple as key ((price,id),name) sortedPriceProducts=nonemptyJines.map(lambda line:
    ((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
    (tuple[0][0],tuple[0][1]))
    Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
    # Dont forget to cast string
    # Tuple as key ((price,id},name)
    # Using minus(-) parameter can help you to make descending ordering , only for numeric value.
    sortedPrlceProducts=nonemptylines.map(lambda line:
    ((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
    (-tuple[0][0],tuple[0][1]}}

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print(sortedPriceProducts)
Step 10 : Now sort data based on product_price as ascending and product_id in ascending order, using takeOrdered{) function.
#Dont forget to cast string
#Tuple as key ((price,id),name) sortedPriceProducts=nonemptyJines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

Question Answers


print(sortedPriceProducts)
Step 10 : Now sort data based on product_price as ascending and product_id in ascending order, using takeOrdered{) function.
#Dont forget to cast string
#Tuple as key ((price,id),name) sortedPriceProducts=nonemptyJines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

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print(sortedPriceProducts)
Step 10 : Now sort data based on product_price as ascending and product_id in ascending order, using takeOrdered{) function.
#Dont forget to cast string
#Tuple as key ((price,id),name) sortedPriceProducts=nonemptyJines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

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print(sortedPriceProducts)
Step 10 : Now sort data based on product_price as ascending and product_id in ascending order, using takeOrdered{) function.
#Dont forget to cast string
#Tuple as key ((price,id),name) sortedPriceProducts=nonemptyJines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

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print(sortedPriceProducts)
Step 10 : Now sort data based on product_price as ascending and product_id in ascending order, using takeOrdered{) function.
#Dont forget to cast string
#Tuple as key ((price,id),name) sortedPriceProducts=nonemptyJines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

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(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

exam" width="15" height="15"> Choose Printthiscard
print(sortedPriceProducts)
Step 10 : Now sort data based on product_price as ascending and product_id in ascending order, using takeOrdered{) function.
#Dont forget to cast string
#Tuple as key ((price,id),name) sortedPriceProducts=nonemptyJines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

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(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

exam" width="15" height="15"> Comprehensive questions and answers about
print(sortedPriceProducts)
Step 10 : Now sort data based on product_price as ascending and product_id in ascending order, using takeOrdered{) function.
#Dont forget to cast string
#Tuple as key ((price,id),name) sortedPriceProducts=nonemptyJines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

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(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

exam" width="15" height="15">
print(sortedPriceProducts)
Step 10 : Now sort data based on product_price as ascending and product_id in ascending order, using takeOrdered{) function.
#Dont forget to cast string
#Tuple as key ((price,id),name) sortedPriceProducts=nonemptyJines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

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(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

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(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

exam" width="15" height="15">
print(sortedPriceProducts)
Step 10 : Now sort data based on product_price as ascending and product_id in ascending order, using takeOrdered{) function.
#Dont forget to cast string
#Tuple as key ((price,id),name) sortedPriceProducts=nonemptyJines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

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(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

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print(sortedPriceProducts)
Step 10 : Now sort data based on product_price as ascending and product_id in ascending order, using takeOrdered{) function.
#Dont forget to cast string
#Tuple as key ((price,id),name) sortedPriceProducts=nonemptyJines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

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(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

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(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

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print(sortedPriceProducts)
Step 10 : Now sort data based on product_price as ascending and product_id in ascending order, using takeOrdered{) function.
#Dont forget to cast string
#Tuple as key ((price,id),name) sortedPriceProducts=nonemptyJines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(tuple[0][0],tuple[0][1]))
Step 11 : Now sort data based on product_price as descending and product_id in ascending order, using takeOrdered() function.
# Dont forget to cast string
# Tuple as key ((price,id},name)
# Using minus(-) parameter can help you to make descending ordering , only for numeric value.
sortedPrlceProducts=nonemptylines.map(lambda line:
((float(line.split(","}[4]},int(line.split(","}[0]}},line.split(","}[2]}}.takeOrdered(10, lambda tuple :
(-tuple[0][0],tuple[0][1]}}

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NEW QUESTION: 1

A. Option B
B. Option C
C. Option A
D. Option D
Answer: D
Explanation:
Reference:
https://www.cisco.com/c/en/us/td/docs/security/asa/asa95/configuration/general/asa-95-generalconfig/ ha-failover.pdf

NEW QUESTION: 2
An administrator is concerned that a company's web server has not been patched. Which of the following would be the BEST assessment for the administrator to perform?
A. Virus scan
B. Vulnerability scan
C. Network sniffer
D. Risk assessment
Answer: B
Explanation:
A vulnerability scan is the process of scanning the network and/or I.T. infrastructure for threats and vulnerabilities. Vulnerabilities include computer systems that do not have the latest security patches installed. The threats and vulnerabilities are then evaluated in a risk assessment and the necessary actions taken to resolve and vulnerabilities. A vulnerability scan is the automated process of proactively identifying security vulnerabilities of computing systems in a network in order to determine if and where a system can be exploited and/or threatened. While public servers are important for communication and data transfer over the Internet, they open the door to potential security breaches by threat agents, such as malicious hackers. Vulnerability scanning employs software that seeks out security flaws based on a database of known flaws, testing systems for the occurrence of these flaws and generating a report of the findings that an individual or an enterprise can use to tighten the network's security. Vulnerability scanning typically refers to the scanning of systems that are connected to the Internet but can also refer to system audits on internal networks that are not connected to the Internet in order to assess the threat of rogue software or malicious employees in an enterprise.

NEW QUESTION: 3
CORRECT TEXT
Problem Scenario 79 : You have been given MySQL DB with following details.
user=retail_dba
password=cloudera
database=retail_db
table=retail_db.orders
table=retail_db.order_items
jdbc URL = jdbc:mysql://quickstart:3306/retail_db
Columns of products table : (product_id | product categoryid | product_name | product_description | product_prtce | product_image )
Please accomplish following activities.
1 . Copy "retaildb.products" table to hdfs in a directory p93_products
2 . Filter out all the empty prices
3 . Sort all the products based on price in both ascending as well as descending order.
4 . Sort all the products based on price as well as product_id in descending order.
5 . Use the below functions to do data ordering or ranking and fetch top 10 elements top() takeOrdered() sortByKey()
Answer:
Explanation:
See the explanation for Step by Step Solution and configuration.
Explanation:
Solution :
Step 1 : Import Single table .
sqoop import --connect jdbc:mysql://quickstart:3306/retail_db -username=retail_dba - password=cloudera -table=products -target-dir=p93_products -m 1
Note : Please check you dont have space between before or after '=' sign. Sqoop uses the
MapReduce framework to copy data from RDBMS to hdfs
Step 2 : Step 2 : Read the data from one of the partition, created using above command, hadoop fs -cat p93_products/part-m-00000
Step 3 : Load this directory as RDD using Spark and Python (Open pyspark terminal and do following). productsRDD = sc.textFile("p93_products")
Step 4 : Filter empty prices, if exists
#filter out empty prices lines
nonemptyjines = productsRDD.filter(lambda x: len(x.split(",")[4]) > 0)
Step 5 : Now sort data based on product_price in order.
sortedPriceProducts=nonempty_lines.map(lambdaline:(float(line.split(",")[4]),line.split(",")[2]
)).sortByKey()
for line in sortedPriceProducts.collect(): print(line)
Step 6 : Now sort data based on product_price in descending order.
sortedPriceProducts=nonempty_lines.map(lambda line:
(float(line.split(",")[4]),line.split(",")[2])).sortByKey(False)
for line in sortedPriceProducts.collect(): print(line)
Step 7 : Get highest price products name.
sortedPriceProducts=nonemptyJines.map(lambda line : (float(line.split(",")[4]),line- split(,,,,,)[2]))-sortByKey(False).take(1) print(sortedPriceProducts)
Step 8 : Now sort data based on product_price as well as product_id in descending order.
#Dont forget to cast string #Tuple as key ((price,id),name)
sortedPriceProducts=nonemptyJines.map(lambda line : ((float(line
print(sortedPriceProducts)
Step 9 : Now sort data based on product_price as well as product_id in descending order, using top() function.
#Dont forget to cast string
#Tuple as key ((price,id),name)
sortedPriceProducts=nonemptyJines.map(lambda line: ((float(line.s

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