それは正確性が高くて、カバー率も広いです。あなたはNewValidDumpsの学習教材を購入した後、私たちは一年間で無料更新サービスを提供することができます。NewValidDumpsのClouderaのCCA175試験過去問試験トレーニング資料はClouderaのCCA175試験過去問認定試験を準備するのリーダーです。 短時間でCCA175試験過去問試験に一発合格したいなら、我々社のClouderaのCCA175試験過去問資料を参考しましょう。また、CCA175試験過去問問題集に疑問があると、メールで問い合わせてください。 もちろん、我々はあなたに一番安心させるのは我々の開発する多くの受験生に合格させるClouderaのCCA175試験過去問試験のソフトウェアです。

CCA175試験過去問試験備考資料の整理を悩んでいますか。

ClouderaのCCA175 - CCA Spark and Hadoop Developer Exam試験過去問の購入の前にあなたの無料の試しから、購入の後での一年間の無料更新まで我々はあなたのClouderaのCCA175 - CCA Spark and Hadoop Developer Exam試験過去問試験に一番信頼できるヘルプを提供します。 NewValidDumpsは数年にわたりCloudera　CCA175 問題例資格認定試験の研究に取り組んで、量豊かな問題庫があるし、豊富な経験を持ってあなたが認定試験に効率的に合格するのを助けます。CCA175 問題例資格認定試験に合格できるかどうかには、重要なのは正確の方法で、復習教材の量ではありません。

社会と経済の発展につれて、多くの人はIT技術を勉強します。なぜならば、IT職員にとって、ClouderaのCCA175試験過去問資格証明書があるのは肝心な指標であると言えます。自分の能力を証明するために、CCA175試験過去問試験に合格するのは不可欠なことです。

Cloudera CCA175試験過去問 - 迷ってないください。

今の社会の中で、ネット上で訓練は普及して、弊社は試験問題集を提供する多くのネットの一つでございます。NewValidDumpsが提供したのオンライン商品がIT業界では品質の高い学習資料、受験生の必要が満足できるサイトでございます。

それに、ClouderaのCCA175試験過去問の試験の実践経験やテストダンプにも含まれています。NewValidDumpsは受験生たちを助けて試験の準備をして、試験に合格するサイトですから、受験生のトレーニングにいろいろな便利を差し上げます。

CCA175 PDF DEMO:

QUESTION NO: 1
CORRECT TEXT
Problem Scenario 40 : You have been given sample data as below in a file called spark15/file1.txt
3070811,1963,1096,,"US","CA",,1,
3022811,1963,1096,,"US","CA",,1,56
3033811,1963,1096,,"US","CA",,1,23
Below is the code snippet to process this tile.
val field= sc.textFile("spark15/f ilel.txt")
val mapper = field.map(x=> A)
mapper.map(x => x.map(x=> {B})).collect
Please fill in A and B so it can generate below final output
Array(Array(3070811,1963,109G, 0, "US", "CA", 0,1, 0)
,Array(3022811,1963,1096, 0, "US", "CA", 0,1, 56)
,Array(3033811,1963,1096, 0, "US", "CA", 0,1, 23)
)
Answer:
See the explanation for Step by Step Solution and configuration.
Explanation:
Solution :
A. x.split(","-1)
B. if (x. isEmpty) 0 else x

QUESTION NO: 2
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:
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();

QUESTION NO: 3
CORRECT TEXT
Problem Scenario 35 : You have been given a file named spark7/EmployeeName.csv
(id,name).
EmployeeName.csv
E01,Lokesh
E02,Bhupesh
E03,Amit
E04,Ratan
E05,Dinesh
E06,Pavan
E07,Tejas
E08,Sheela
E09,Kumar
E10,Venkat
1. Load this file from hdfs and sort it by name and save it back as (id,name) in results directory.
However, make sure while saving it should be able to write In a single file.
Answer:
See the explanation for Step by Step Solution and configuration.
Explanation:
Solution:
Step 1 : Create file in hdfs (We will do using Hue). However, you can first create in local filesystem and then upload it to hdfs.
Step 2 : Load EmployeeName.csv file from hdfs and create PairRDDs
val name = sc.textFile("spark7/EmployeeName.csv")
val namePairRDD = name.map(x=> (x.split(",")(0),x.split(",")(1)))
Step 3 : Now swap namePairRDD RDD.
val swapped = namePairRDD.map(item => item.swap)
step 4: Now sort the rdd by key.
val sortedOutput = swapped.sortByKey()
Step 5 : Now swap the result back
val swappedBack = sortedOutput.map(item => item.swap}
Step 6 : Save the output as a Text file and output must be written in a single file.
swappedBack. repartition(1).saveAsTextFile("spark7/result.txt")

QUESTION NO: 4
CORRECT TEXT
Problem Scenario 46 : You have been given belwo list in scala (name,sex,cost) for each work done.
List( ("Deeapak" , "male", 4000), ("Deepak" , "male", 2000), ("Deepika" , "female",
2000),("Deepak" , "female", 2000), ("Deepak" , "male", 1000) , ("Neeta" , "female", 2000))
Now write a Spark program to load this list as an RDD and do the sum of cost for combination of name and sex (as key)
Answer:
See the explanation for Step by Step Solution and configuration.
Explanation:
Solution :
Step 1 : Create an RDD out of this list
val rdd = sc.parallelize(List( ("Deeapak" , "male", 4000}, ("Deepak" , "male", 2000),
("Deepika" , "female", 2000),("Deepak" , "female", 2000), ("Deepak" , "male", 1000} ,
("Neeta" , "female", 2000}}}
Step 2 : Convert this RDD in pair RDD
val byKey = rdd.map({case (name,sex,cost) => (name,sex)->cost})
Step 3 : Now group by Key
val byKeyGrouped = byKey.groupByKey
Step 4 : Nowsum the cost for each group
val result = byKeyGrouped.map{case ((id1,id2),values) => (id1,id2,values.sum)}
Step 5 : Save the results result.repartition(1).saveAsTextFile("spark12/result.txt")

QUESTION NO: 5
CORRECT TEXT
Problem Scenario 96 : Your spark application required extra Java options as below. -
XX:+PrintGCDetails-XX:+PrintGCTimeStamps
Please replace the XXX values correctly
./bin/spark-submit --name "My app" --master local[4] --conf spark.eventLog.enabled=talse -
-conf XXX hadoopexam.jar
Answer:
See the explanation for Step by Step Solution and configuration.
Explanation:
Solution
XXX: Mspark.executoi\extraJavaOptions=-XX:+PrintGCDetails -XX:+PrintGCTimeStamps"
Notes: ./bin/spark-submit \
--class <maln-class>
--master <master-url> \
--deploy-mode <deploy-mode> \
-conf <key>=<value> \
# other options
< application-jar> \
[application-arguments]
Here, conf is used to pass the Spark related contigs which are required for the application to run like any specific property(executor memory) or if you want to override the default property which is set in Spark-default.conf.

ECCouncil 312-96 - 試験問題と解答に関する質問があるなら、当社は直後に解決方法を差し上げます。 NewValidDumpsのClouderaのSAP C-S43-2022問題集を買う前に、一部の問題と解答を無料に試用することができます。 NewValidDumpsのClouderaのCWNP CWSP-207試験問題資料は質が良くて値段が安い製品です。 NewValidDumps ClouderaのHP HP2-I63試験トレーニング資料というのは一体なんでしょうか。 ClouderaのCheckPoint 156-315.81.20認定試験は実は技術専門家を認証する試験です。

Updated: May 28, 2022