Question # 1 Problem Scenario 65 : You have been given below code snippet. val a = sc.parallelize(List("dog", "cat", "owl", "gnu", "ant"), 2) val b = sc.parallelize(1 to a.count.tolnt, 2) val c = a.zip(b) operation1 Write a correct code snippet for operationl which will produce desired output, shown below. Array[(String, Int)] = Array((owl,3), (gnu,4), (dog,1), (cat,2>, (ant,5))
Answer Description Answer: See the explanation for Step by Step Solution and configuration. Explanation: Solution : c.sortByKey(false).collect sortByKey [Ordered] : This function sorts the input RDD's data and stores it in a new RDD. "The output RDD is a shuffled RDD because it stores data that is output by a reducer which has been shuffled. The implementation of this function is actually very clever. First, it uses a range partitioner to partition the data in ranges within the shuffled RDD. Then it sorts these ranges individually with mapPartitions using standard sort mechanisms.
Question # 2 Problem Scenario 72 : You have been given a table named "employee2" with following detail. first_name string last_name string Write a spark script in python which read this table and print all the rows and individual column values.
Answer Description Answer: See the explanation for Step by Step Solution and configuration. Explanation: Solution : Step 1 : Import statements for HiveContext from pyspark.sql import HiveContext Step 2 : Create sqIContext sqIContext = HiveContext(sc) Step 3 : Query hive employee2 = sqlContext.sql("select' from employee2") Step 4 : Now prints the data for row in employee2.collect(): print(row) Step 5 : Print specific column for row in employee2.collect(): print( row.fi rst_name)
Question # 3 Problem Scenario 67 : You have been given below code snippet. lines = sc.parallelize(['lts fun to have fun,','but you have to know how.'])M = lines.map( lambda x: x.replace(',7 ').replace('.',' 'J.replaceC-V ').lower()) r2 = r1.flatMap(lambda x: x.split()) r3 = r2.map(lambda x: (x, 1)) operation1 r5 = r4.map(lambda x:(x[1],x[0])) r6 = r5.sortByKey(ascending=False) r6.take(20) Write a correct code snippet for operationl which will produce desired output, shown below. [(2, 'fun'), (2, 'to'), (2, 'have'), (1, its'), (1, 'know1), (1, 'how1), (1, 'you'), (1, 'but')]
Answer Description Answer: See the explanation for Step by Step Solution and configuration. Explanation: Solution : r4 = r3.reduceByKey(lambda x,y:x+y)
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