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NEW QUESTION: 1
Different organisms thrive on different nutrients including inorganic substances (Sulfur, H(2)S), and organic substances (Hydrocarbons, Organic acids). In addition, all organisms require a source of carbon, nitrogen and _______ for growth.
A. Water
B. Oxygen
C. Manganese
D. Phosphorous
Answer: D

NEW QUESTION: 2
A company has an application that uses Amazon Elastic File System (Amazon EFS) to store data. The files are
1 GB in size or larger and are accessed often only tor the first few days after creation The application data is shared across a cluster of Linux servers. The company wants to reduce storage costs tor the application What should a solutions architect do to meet these requirements?
A. Configure a Lifecycle policy to move the files to the EFS Infrequent Access (IA) swage class after 7 days,
B. Move the fees from Amazon EFS and store them locally on each Amazon EC2 instance.
C. Implement Amazon FSx and mount the network drive on each server.
D. Move the files to Amazon S3 with S3 lifecycle policies enabled. Rewrite the application to support mounting the S3 bucket.
Answer: A

NEW QUESTION: 3
CORRECT TEXT
Problem Scenario 90 : You have been given below two files
course.txt
id,course
1 ,Hadoop
2 ,Spark
3 ,HBase
fee.txt
id,fee
2,3900
3,4200
4,2900
Accomplish the following activities.
1. Select all the courses and their fees , whether fee is listed or not.
2. Select all the available fees and respective course. If course does not exists still list the fee
3. Select all the courses and their fees , whether fee is listed or not. However, ignore records having fee as null.
Answer:
Explanation:
See the explanation for Step by Step Solution and configuration.
Explanation:
Solution :
Step 1:
hdfs dfs -mkdir sparksql4
hdfs dfs -put course.txt sparksql4/
hdfs dfs -put fee.txt sparksql4/
Step 2 : Now in spark shell
// load the data into a new RDD
val course = sc.textFile("sparksql4/course.txt")
val fee = sc.textFile("sparksql4/fee.txt")
// Return the first element in this RDD
course.fi rst()
fee.fi rst()
//define the schema using a case class case class Course(id: Integer, name: String) case class Fee(id: Integer, fee: Integer)
// create an RDD of Product objects
val courseRDD = course.map(_.split(",")).map(c => Course(c(0).tolnt,c(1))) val feeRDD =fee.map(_.split(",")).map(c => Fee(c(0}.tolnt,c(1}.tolnt)) courseRDD.first() courseRDD.count(}
feeRDD.first()
feeRDD.countQ
// change RDD of Product objects to a DataFrame val courseDF = courseRDD.toDF(} val feeDF = feeRDD.toDF{)
// register the DataFrame as a temp table courseDF. registerTempTable("course") feeDF.
registerTempTablef'fee")
// Select data from table
val results = sqlContext.sql(......SELECT' FROM course """ )
results. showQ
val results = sqlContext.sql(......SELECT' FROM fee......)
results. showQ
val results = sqlContext.sql(......SELECT * FROM course LEFT JOIN fee ON course.id = fee.id......) results-showQ val results ="sqlContext.sql(......SELECT * FROM course RIGHT JOIN fee ON course.id = fee.id "MM ) results. showQ val results = sqlContext.sql(......SELECT' FROM course LEFT JOIN fee ON course.id = fee.id where fee.id IS NULL" results. show()