Cloudera Exam CCA175 Topic 4 Question 16 Discussion

Actual exam question for Cloudera's CCA175 exam

Question #: 16
Topic #: 4

[All CCA175 Questions]

Problem Scenario 75 : 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

Please accomplish following activities.

1. Copy "retail_db.order_items" table to hdfs in respective directory p90_order_items .

2. Do the summation of entire revenue in this table using pyspark.

3. Find the maximum and minimum revenue as well.

4. Calculate average revenue

Columns of ordeMtems table : (order_item_id , order_item_order_id , order_item_product_id, order_item_quantity,order_item_subtotal,order_item_subtotal,order_item_product_price)

ASolution :
Step 1 : Import Single table .
sqoop import --connect jdbc:mysql://quickstart:3306/retail_db -username=retail_dba -password=cloudera -table=order_items --target-dir=p90 ordeMtems --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 : Read the data from one of the partition, created using above command. hadoop fs -cat p90_order_items/part-m-00000
Step 3 : In pyspark, get the total revenue across all days and orders. entire TableRDD = sc.textFile('p90_order_items')
#Cast string to float
extractedRevenueColumn = entireTableRDD.map(lambda line: float(line.split(',')[4]))
Step 4 : Verify extracted data
for revenue in extractedRevenueColumn.collect():
print revenue
#use reduce'function to sum a single column vale
totalRevenue = extractedRevenueColumn.reduce(lambda a, b: a + b)
Step 5 : Caclculate average revenue
count=extractedRevenueColumn.count()
averageRev=totalRevenue/count

BSolution :
Step 1 : Import Single table .
sqoop import --connect jdbc:mysql://quickstart:3306/retail_db -username=retail_dba -password=cloudera -table=order_items --target-dir=p90 ordeMtems --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 : Read the data from one of the partition, created using above command. hadoop fs -cat p90_order_items/part-m-00000
Step 3 : In pyspark, get the total revenue across all days and orders. entire TableRDD = sc.textFile('p90_order_items')
#Cast string to float
extractedRevenueColumn = entireTableRDD.map(lambda line: float(line.split(',')[4]))
Step 4 : Verify extracted data
for revenue in extractedRevenueColumn.collect():
print revenue
#use reduce'function to sum a single column vale
totalRevenue = extractedRevenueColumn.reduce(lambda a, b: a + b)
Step 5 : Calculate the maximum revenue
maximumRevenue = extractedRevenueColumn.reduce(lambda a, b: (a if a>=b else b))
Step 6 : Calculate the minimum revenue
minimumRevenue = extractedRevenueColumn.reduce(lambda a, b: (a if a<=b else b))
Step 7 : Caclculate average revenue
count=extractedRevenueColumn.count()
averageRev=totalRevenue/count

Show Suggested Answer

Suggested Answer: B

by Regenia at May 08, 2022, 05:03 AM

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