我々のClouderaのCCA175テストトレーニングソフトはあなたのすべての需要を満たすのを希望します。問題集の全面性と権威性、ClouderaのCCA175テストトレーニングソフトがPDF版、オンライン版とソフト版があるという資料のバーションの多様性、購入の前にデモの無料ダウンロード、購入の後でClouderaのCCA175テストトレーニングソフトの一年間の無料更新、これ全部は我々の誠の心を示しています。 NewValidDumpsの専門家チームが君の需要を満たすために自分の経験と知識を利用してClouderaのCCA175テストトレーニング認定試験対策模擬テスト問題集が研究しました。模擬テスト問題集と真実の試験問題がよく似ています。 IT業界で就職する前に、あなたはClouderaのCCA175テストトレーニング試験に合格したら、あなたに満足させる仕事を探す準備をよくしました。

それはNewValidDumpsのCCA175テストトレーニング問題集です。

もしあなたはまだ合格のためにCloudera CCA175 - CCA Spark and Hadoop Developer Examテストトレーニングに大量の貴重な時間とエネルギーをかかって一生懸命準備し、Cloudera CCA175 - CCA Spark and Hadoop Developer Examテストトレーニング「CCA Spark and Hadoop Developer Exam」認証試験に合格するの近道が分からなくって、今はNewValidDumpsが有効なCloudera CCA175 - CCA Spark and Hadoop Developer Examテストトレーニング認定試験の合格の方法を提供して、君は半分の労力で倍の成果を取るの与えています。 もし不合格になったら、私たちは全額返金することを保証します。一回だけでClouderaのCCA175 トレーニング資料試験に合格したい？NewValidDumpsは君の欲求を満たすために存在するのです。

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Cloudera CCA175テストトレーニング - これは受験生の皆様を助けた結果です。

あなたはCCA175テストトレーニング試験に不安を持っていますか？CCA175テストトレーニング参考資料をご覧下さい。私たちのCCA175テストトレーニング参考資料は十年以上にわたり、専門家が何度も練習して、作られました。あなたに高品質で、全面的なCCA175テストトレーニング参考資料を提供することは私たちの責任です。私たちより、CCA175テストトレーニング試験を知る人はいません。

ClouderaのCCA175テストトレーニング試験に受かるのはあなたが自分をIT業種にアピールする方法の一つです。でも、試験に合格するために大量な時間とエネルギーを費やすことはなく、NewValidDumpsのClouderaのCCA175テストトレーニング試験トレーニング資料を選んだらいいです。

CCA175 PDF DEMO:

QUESTION NO: 1
CORRECT TEXT
Problem Scenario 81 : You have been given MySQL DB with following details. You have been given following product.csv file product.csv productID,productCode,name,quantity,price
1001,PEN,Pen Red,5000,1.23
1002,PEN,Pen Blue,8000,1.25
1003,PEN,Pen Black,2000,1.25
1004,PEC,Pencil 2B,10000,0.48
1005,PEC,Pencil 2H,8000,0.49
1006,PEC,Pencil HB,0,9999.99
Now accomplish following activities.
1 . Create a Hive ORC table using SparkSql
2 . Load this data in Hive table.

QUESTION NO: 2
. Create a Hive parquet table using SparkSQL and load data in it.
Answer:
See the explanation for Step by Step Solution and configuration.
Explanation:
Solution :
Step 1 : Create this tile in HDFS under following directory (Without header}
/user/cloudera/he/exam/task1/productcsv
Step 2 : Now using Spark-shell read the file as RDD
// load the data into a new RDD
val products = sc.textFile("/user/cloudera/he/exam/task1/product.csv")
// Return the first element in this RDD
prod u cts.fi rst()
Step 3 : Now define the schema using a case class
case class Product(productid: Integer, code: String, name: String, quantity:lnteger, price:
Float)
Step 4 : create an RDD of Product objects
val prdRDD = products.map(_.split(",")).map(p =>
Product(p(0).tolnt,p(1),p(2),p(3}.tolnt,p(4}.toFloat))
prdRDD.first()
prdRDD.count()
Step 5 : Now create data frame val prdDF = prdRDD.toDF()
Step 6 : Now store data in hive warehouse directory. (However, table will not be created } import org.apache.spark.sql.SaveMode
prdDF.write.mode(SaveMode.Overwrite).format("orc").saveAsTable("product_orc_table") step 7:
Now create table using data stored in warehouse directory. With the help of hive.
hive
show tables
CREATE EXTERNAL TABLE products (productid int,code string,name string .quantity int, price float}
STORED AS ore
LOCATION 7user/hive/warehouse/product_orc_table';
Step 8 : Now create a parquet table
import org.apache.spark.sql.SaveMode
prdDF.write.mode(SaveMode.Overwrite).format("parquet").saveAsTable("product_parquet_ table")
Step 9 : Now create table using this
CREATE EXTERNAL TABLE products_parquet (productid int,code string,name string
.quantity int, price float}
STORED AS parquet
LOCATION 7user/hive/warehouse/product_parquet_table';
Step 10 : Check data has been loaded or not.
Select * from products;
Select * from products_parquet;
3. CORRECT TEXT
Problem Scenario 84 : In Continuation of previous question, please accomplish following activities.
1. Select all the products which has product code as null
2. Select all the products, whose name starts with Pen and results should be order by Price descending order.
3. Select all the products, whose name starts with Pen and results should be order by
Price descending order and quantity ascending order.

QUESTION NO: 3
Select top 2 products by price
Answer:
See the explanation for Step by Step Solution and configuration.
Explanation:
Solution :
Step 1 : Select all the products which has product code as null
val results = sqlContext.sql(......SELECT' FROM products WHERE code IS NULL......) results. showQ val results = sqlContext.sql(......SELECT * FROM products WHERE code = NULL ",,M ) results.showQ
Step 2 : Select all the products , whose name starts with Pen and results should be order by Price descending order. val results = sqlContext.sql(......SELECT * FROM products
WHERE name LIKE 'Pen %' ORDER BY price DESC......)
results. showQ
Step 3 : Select all the products , whose name starts with Pen and results should be order by Price descending order and quantity ascending order. val results = sqlContext.sql('.....SELECT * FROM products WHERE name LIKE 'Pen %' ORDER BY price DESC, quantity......) results. showQ
Step 4 : Select top 2 products by price
val results = sqlContext.sql(......SELECT' FROM products ORDER BY price desc
LIMIT2......}
results. show()
4. CORRECT TEXT
Problem Scenario 4: You have been given MySQL DB with following details.
user=retail_dba
password=cloudera
database=retail_db
table=retail_db.categories
jdbc URL = jdbc:mysql://quickstart:3306/retail_db
Please accomplish following activities.
Import Single table categories (Subset data} to hive managed table , where category_id between 1 and 22
Answer:
See the explanation for Step by Step Solution and configuration.
Explanation:
Solution :
Step 1 : Import Single table (Subset data)
sqoop import --connect jdbc:mysql://quickstart:3306/retail_db -username=retail_dba - password=cloudera -table=categories -where "\'category_id\' between 1 and 22" --hive- import --m 1
Note: Here the ' is the same you find on ~ key
This command will create a managed table and content will be created in the following directory.
/user/hive/warehouse/categories
Step 2 : Check whether table is created or not (In Hive)
show tables;
select * from categories;

QUESTION NO: 4
CORRECT TEXT
Problem Scenario 49 : You have been given below code snippet (do a sum of values by key}, with intermediate output.
val keysWithValuesList = Array("foo=A", "foo=A", "foo=A", "foo=A", "foo=B", "bar=C",
"bar=D", "bar=D")
val data = sc.parallelize(keysWithValuesl_ist}
//Create key value pairs
val kv = data.map(_.split("=")).map(v => (v(0), v(l))).cache()
val initialCount = 0;
val countByKey = kv.aggregateByKey(initialCount)(addToCounts, sumPartitionCounts)
Now define two functions (addToCounts, sumPartitionCounts) such, which will produce following results.
Output 1
countByKey.collect
res3: Array[(String, Int)] = Array((foo,5), (bar,3))
import scala.collection._
val initialSet = scala.collection.mutable.HashSet.empty[String]
val uniqueByKey = kv.aggregateByKey(initialSet)(addToSet, mergePartitionSets)
Now define two functions (addToSet, mergePartitionSets) such, which will produce following results.
Output 2:
uniqueByKey.collect
res4: Array[(String, scala.collection.mutable.HashSet[String])] = Array((foo,Set(B, A}},
(bar,Set(C, D}}}
Answer:
See the explanation for Step by Step Solution and configuration.
Explanation:
Solution :
val addToCounts = (n: Int, v: String) => n + 1
val sumPartitionCounts = (p1: Int, p2: Int} => p1 + p2
val addToSet = (s: mutable.HashSet[String], v: String) => s += v
val mergePartitionSets = (p1: mutable.HashSet[String], p2: mutable.HashSet[String]) => p1
+ += p2

QUESTION NO: 5
CORRECT TEXT
Problem Scenario 13 : You have been given following mysql database details as well as other info.
user=retail_dba
password=cloudera
database=retail_db
jdbc URL = jdbc:mysql://quickstart:3306/retail_db
Please accomplish following.
1. Create a table in retailedb with following definition.
CREATE table departments_export (department_id int(11), department_name varchar(45), created_date T1MESTAMP DEFAULT NOWQ);
2. Now import the data from following directory into departments_export table,
/user/cloudera/departments new
Answer:
See the explanation for Step by Step Solution and configuration.
Explanation:
Solution :
Step 1 : Login to musql db
mysql --user=retail_dba -password=cloudera
show databases; use retail_db; show tables;
step 2 : Create a table as given in problem statement.
CREATE table departments_export (departmentjd int(11), department_name varchar(45), created_date T1MESTAMP DEFAULT NOW()); show tables;
Step 3 : Export data from /user/cloudera/departmentsnew to new table departments_export sqoop export -connect jdbc:mysql://quickstart:3306/retail_db \
-username retaildba \
--password cloudera \
--table departments_export \
-export-dir /user/cloudera/departments_new \
-batch
Step 4 : Now check the export is correctly done or not. mysql -user*retail_dba - password=cloudera show databases; use retail _db;
show tables;
select' from departments_export;

CompTIA SY0-601 - NewValidDumpsはきみの貴重な時間を節約するだけでなく、 安心で順調に試験に合格するのを保証します。 SAP C_THR81_2311 - そうだったら、NewValidDumpsを利用したください。 SAP C_SAC_2402 - NewValidDumps を選択して１００％の合格率を確保することができて、もし試験に失敗したら、NewValidDumpsが全額で返金いたします。 NewValidDumpsのClouderaのEMC D-VXR-OE-23試験トレーニング資料はあなたの成功への第一歩です。 Salesforce CRT-403 - そうしたらあなたはNewValidDumpsが用意した問題集にもっと自信があります。

Updated: May 28, 2022