一年以内に、あなたが持っている資料を更新したい限り、NewValidDumpsは最新バージョンのCCA175テスト模擬問題集問題集を捧げます。NewValidDumpsはあなたに最大の利便性を与えるために全力を尽くしています。NewValidDumpsのCCA175テスト模擬問題集問題集の超低い価格に反して、 NewValidDumpsに提供される問題集は最高の品質を持っています。 一目でわかる最新の出題傾向でわかりやすい解説と充実の補充問題があります。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テスト模擬問題集認定試験対策模擬テスト問題集が研究しました。 ClouderaのCCA175テスト模擬問題集試験トレーニング資料は現在、市場上で一番質のいい学習教材です。

Cloudera Certified CCA175 近年、IT領域で競争がますます激しくなります。

あなたは高効率の復習とClouderaのCCA175 - CCA Spark and Hadoop Developer Examテスト模擬問題集試験の成功を経験する必要があればいいです。 NewValidDumpsのClouderaのCCA175 ウェブトレーニング試験トレーニング資料は豊富な知識と経験を持っているIT専門家に研究された成果で、正確度がとても高いです。NewValidDumpsに会ったら、最高のトレーニング資料を見つけました。

数年間の発展で我々NewValidDumpsはもっと多くの資源と経験を得ています。改善されているソフトはあなたのClouderaのCCA175テスト模擬問題集試験の復習の効率を高めることができます。IT業界での競争がますます激しくなるうちに、あなたの能力をどのように証明しますか。

Cloudera CCA175テスト模擬問題集 - 弊社の商品が好きなのは弊社のたのしいです。

NewValidDumpsを選択したら、成功が遠くではありません。NewValidDumpsが提供するClouderaのCCA175テスト模擬問題集認証試験問題集が君の試験に合格させます。テストの時に有効なツルが必要でございます。

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。

CCA175 PDF DEMO:

QUESTION NO: 1
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: 2
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: 3
. 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: 4
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: 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;

Huawei H13-629_V3.0 - あなたに予想外の良い効果を見せられますから。 あなたはインターネットでClouderaのWGU Organizational-Behaviors-and-Leadership認証試験の練習問題と解答の試用版を無料でダウンロードしてください。 SAP C-SIGPM-2403 - あなたが首尾よく試験に合格するように、我々は最も有利な価格と最高のクオリティーを提供して差し上げます。 Huawei H13-629_V3.0 - NewValidDumpsはまた一年間に無料なサービスを更新いたします。 そうしたらNewValidDumpsのClouderaのMicrosoft AZ-400J試験に合格することができるようになります。

Updated: May 28, 2022