Cloudera Exam CCA175 Topic 6 Question 65 Discussion

Actual exam question for Cloudera's CCA175 exam

Question #: 65
Topic #: 6

[All CCA175 Questions]

Problem Scenario 80 : You have been given MySQL DB with following details.

user=retail_dba

password=cloudera

database=retail_db

table=retail_db.products

jdbc URL = jdbc:mysql://quickstart:3306/retail_db

Please accomplish following activities.

1. Copy "retaildb.products" table to hdfs in a directory p93_products

2. Now sort the products data sorted by product price per category, use productcategoryid colunm to group by category

ASolution :
Step 1 : Import Single table .
sqoop import --connect jdbc:mysql://quickstart:3306/retail_db -username=retail_dba -password=cloudera -table=products --target-dir=p93
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(Mp93_products')
Step 4 : Filter empty prices, if exists
#filter out empty prices lines
Nonempty_lines = productsRDD.filter(lambda x: len(x.split(',')[4]) > 0)
Step 5 : Create data set like (categroyld, (id,name,price)
mappedRDD = nonempty_lines.map(lambda line: (line.split(',')[1], (line.split(',')[0], line.split(',')[2], float(line.split(',')[4]))))
tor line in mappedRDD.collect(): print(line)
Step 6 : Now groupBy the all records based on categoryld, which a key on mappedRDD it will produce output like (categoryld, iterable of all linesfor a key/categoryld)
groupByCategroyld = mappedRDD.groupByKey() for line in groupByCategroyld.collect(): print(line)
step 7 : Now sort the data in each category based on price in ascending order.
# sorted is a function to sort an iterable, we can also specify, what would be the Key on which we want to sort in this case we have price onwhich it needs to be sorted.
groupByCategroyld.map(lambda tuple: sorted(tuple[1], key=lambda tupleValue: tupleValue[2])).take(5)
Step 8 : Now sort the data in each category based on price in descending order.
# sorted is a function to sort an iterable, we can also specify, what would be the Key on which we want to sort in this case we have price which it needs to be sorted.
on groupByCategroyld.map(lambda tuple: sorted(tuple[1], key=lambda tupleValue: tupleValue[2] , reverse=True)).take(5)

BSolution :
Step 1 : Import Single table .
sqoop import --connect jdbc:mysql://quickstart:3306/retail_db -username=retail_dba -password=cloudera -table=products --target-dir=p93
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(Mp93_products')
Step 4 : Filter empty prices, if exists
#filter out empty prices lines
Nonempty_lines = productsRDD.filter(lambda x: len(x.split(',')[4]) > 0)
Step 5 : Create data set like (categroyld, (id,name,price)
mappedRDD = nonempty_lines.map(lambda line: (line.split(',')[1], (line.split(',')[0], line.split(',')[2], float(line.split(',')[4]))))
tor line in mappedRDD.collect(): print(line)
step 6 : Now sort the data in each category based on price in ascending order.
# sorted is a function to sort an iterable, we can also specify, what would be the Key on which we want to sort in this case we have price onwhich it needs to be sorted.
groupByCategroyld.map(lambda tuple: sorted(tuple[1], key=lambda tupleValue: tupleValue[2])).take(5)
Step 7 : Now sort the data in each category based on price in descending order.
# sorted is a function to sort an iterable, we can also specify, what would be the Key on which we want to sort in this case we have price which it needs to be sorted.
on groupByCategroyld.map(lambda tuple: sorted(tuple[1], key=lambda tupleValue: tupleValue[2] , reverse=True)).take(5)

Show Suggested Answer

Suggested Answer: B

by Lashawnda at Jul 07, 2024, 08:48 AM

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-class com.hadoopexam.MyTask

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9 months ago

The correct answer is B. The --deploy-mode cluster option is necessary to launch the driver on a cluster node.

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Martha

8 months ago

B) --deploy-mode cluster

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Selene

8 months ago

A) -class com.hadoopexam.MyTask

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Pamella

8 months ago

B) Solution

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Erasmo

8 months ago

A) Solution

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