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]}}

Braindumps,
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]}}

brain dump,
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]}}

brain 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]}}

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]}}

braindump questions, download
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, latest
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, best
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">
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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]}}

    with flying colors. After purchase you will have the access to all latest and valid
    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]}}

    Formal AD0-E903 Test & AD0-E903 New Learning Materials - AD0-E903 PDF Cram Exam - Chinaprint

    This Exam Has Been Retired
    •  
       

      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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      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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    NEW QUESTION: 1
    Wählen Sie für jede der folgenden Aussagen Ja aus, wenn die Aussage wahr ist. Andernfalls wählen Sie Nein. HINWEIS: Jede richtige Auswahl ist einen Punkt wert.

    Answer:
    Explanation:


    NEW QUESTION: 2
    Which of the following would BEST detect malicious damage arising from an internal threat?
    A. Job rotation
    B. Access control list
    C. Encryption
    D. Fraud awareness training
    Answer: A

    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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