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NEW QUESTION: 1
CORRECT TEXT
Problem Scenario 89 : You have been given below patient data in csv format, patientID,name,dateOfBirth,lastVisitDate
1001,Ah Teck,1991-12-31,2012-01-20
1002,Kumar,2011-10-29,2012-09-20
1003,Ali,2011-01-30,2012-10-21
Accomplish following activities.
1 . Find all the patients whose lastVisitDate between current time and '2012-09-15'
2 . Find all the patients who born in 2011
3 . Find all the patients age
4 . List patients whose last visited more than 60 days ago
5 . Select patients 18 years old or younger
Answer:
Explanation:
See the explanation for Step by Step Solution and configuration.
Explanation:
Solution :
Step 1:
hdfs dfs -mkdir sparksql3
hdfs dfs -put patients.csv sparksql3/
Step 2 : Now in spark shell
// SQLContext entry point for working with structured data
val sqlContext = neworg.apache.spark.sql.SQLContext(sc)
// this is used to implicitly convert an RDD to a DataFrame.
import sqlContext.impIicits._
// Import Spark SQL data types and Row.
import org.apache.spark.sql._
// load the data into a new RDD
val patients = sc.textFilef'sparksqIS/patients.csv")
// Return the first element in this RDD
patients.first()
//define the schema using a case class
case class Patient(patientid: Integer, name: String, dateOfBirth:String , lastVisitDate:
String)
// create an RDD of Product objects
val patRDD = patients.map(_.split(M,M)).map(p => Patient(p(0).tolnt,p(1),p(2),p(3))) patRDD.first() patRDD.count(}
// change RDD of Product objects to a DataFrame val patDF = patRDD.toDF()
// register the DataFrame as a temp table patDF.registerTempTable("patients"}
// Select data from table
val results = sqlContext.sql(......SELECT* FROM patients '.....)
// display dataframe in a tabular format
results.show()
//Find all the patients whose lastVisitDate between current time and '2012-09-15' val results = sqlContext.sql(......SELECT * FROM patients WHERE
TO_DATE(CAST(UNIX_TIMESTAMP(lastVisitDate, 'yyyy-MM-dd') AS TIMESTAMP))
BETWEEN '2012-09-15' AND current_timestamp() ORDER BY lastVisitDate......) results.showQ
/.Find all the patients who born in 2011
val results = sqlContext.sql(......SELECT * FROM patients WHERE
YEAR(TO_DATE(CAST(UNIXJTlMESTAMP(dateOfBirth, 'yyyy-MM-dd') AS
TIMESTAMP))) = 2011 ......)
results. show()
//Find all the patients age
val results = sqlContext.sql(......SELECT name, dateOfBirth, datediff(current_date(),
TO_DATE(CAST(UNIX_TIMESTAMP(dateOfBirth, 'yyyy-MM-dd') AS TlMESTAMP}}}/365
AS age
FROM patients
Mini >
results.show()
//List patients whose last visited more than 60 days ago
-- List patients whose last visited more than 60 days ago
val results = sqlContext.sql(......SELECT name, lastVisitDate FROM patients WHERE datediff(current_date(), TO_DATE(CAST(UNIX_TIMESTAMP[lastVisitDate, 'yyyy-MM-dd')
AS T1MESTAMP))) > 60......);
results. showQ;
-- Select patients 18 years old or younger
SELECT' FROM patients WHERE TO_DATE(CAST(UNIXJTlMESTAMP(dateOfBirth,
'yyyy-MM-dd') AS TIMESTAMP}) > DATE_SUB(current_date(),INTERVAL 18 YEAR); val results = sqlContext.sql(......SELECT' FROM patients WHERE
TO_DATE(CAST(UNIX_TIMESTAMP(dateOfBirth, 'yyyy-MM--dd') AS TIMESTAMP)) >
DATE_SUB(current_date(), T8*365)......);
results. showQ;
val results = sqlContext.sql(......SELECT DATE_SUB(current_date(), 18*365) FROM patients......); results.show();

NEW QUESTION: 2
Welche der folgenden Teamrollen ist am besten geeignet, um das Team zu erweitern, und warum? 2 Credits
A. Ein Qualitätssicherungsbeauftragter
B. Eine Person mit der Fähigkeit, Aufgaben zu erledigen
C. Eine Person mit fundierten technischen Kenntnissen
D. Eine Person, die dem Team neue Ideen bringt
Answer: D
Explanation:
=============================================== =
Thema 10, Szenario 6, V3 "Unabhängiges Testteam"
Für das Projekt wurden drei Ausstiegskriterien definiert:
- A: Testfälle bestanden mehr als 70%
- B: Anzahl offener Mängel, die weniger als 5 betragen
- C: Anzahl der Fehler pro Testfall unter 0,5
In der ersten Testwoche wurden folgende Ergebnisse erzielt:

NEW QUESTION: 3
You have an Azure SQL database that contains a table named Customer. Customer has the columns shown in the following table.

You plan to implement a dynamic data mask for the Customer_Phone column. The mask must meet the following requirements:
The first six numerals of each customer's phone number must be masked.
The last four digits of each customer's phone number must be visible.
Hyphens must be preserved and displayed.
How should you configure the dynamic data mask? To answer, select the appropriate options in the answer area.

Answer:
Explanation:

Explanation:
Box 1: 0
Custom String : Masking method that exposes the first and last letters and adds a custom padding string in the middle. prefix,[padding],suffix Box 2: xxx-xxx Box 3: 5 Reference:
https://docs.microsoft.com/en-us/sql/relational-databases/security/dynamic-data-masking