NewValidDumpsはClouderaのCCA175試験復習赤本認定試験に対して問題集を提供しておるサイトで、現場のClouderaのCCA175試験復習赤本試験問題と模擬試験問題集を含みます。ほかのホームページに弊社みたいな問題集を見れば、あとでみ続けて、弊社の商品を盗作することとよくわかります。NewValidDumpsが提供した資料は最も全面的で、しかも更新の最も速いです。 あなたを試験に一発合格させる素晴らしいCCA175試験復習赤本試験に関連する参考書が登場しますよ。それはNewValidDumpsのCCA175試験復習赤本問題集です。 最新ClouderaのCCA175試験復習赤本認定試験は真実の試験問題にもっとも近くて比較的に全面的でございます。

Cloudera Certified CCA175 NewValidDumpsは君にとってベストな選択になります。

ClouderaのCCA175 - CCA Spark and Hadoop Developer Exam試験復習赤本認証試験は世界でどの国でも承認されて、すべての国が分け隔てをしないの試験です。 うちのClouderaのCCA175 試験勉強攻略試験トレーニング資料を購入する前に、NewValidDumpsのサイトで、一部分のフリーな試験問題と解答をダンロードでき、試用してみます。君がうち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試験復習赤本「CCA Spark and Hadoop Developer Exam」トレーニング資料を利用したら、初めて試験を受けるあなたでも一回で試験に合格できることを保証します。NewValidDumpsのClouderaのCCA175試験復習赤本トレーニング資料を利用しても合格しないのなら、我々は全額で返金することができます。あなたに他の同じ値段の製品を無料に送って差し上げます。

Cloudera CCA175試験復習赤本 - 心はもはや空しくなく、生活を美しくなります。

ClouderaのCCA175試験復習赤本認定試験はIT職員が欠くことができない認証です。IT職員のキャリアと関連しますから。 ClouderaのCCA175試験復習赤本試験トレーニング資料は受験生の皆さんが必要とした勉強資料です。NewValidDumpsのトレーニング資料は受験生が一番ほしい唯一なトレーニング資料です。NewValidDumpsのClouderaのCCA175試験復習赤本試験トレーニング資料を手に入れたら、試験に合格することができるようになります。

また、CCA175試験復習赤本問題集に疑問があると、メールで問い合わせてください。現在IT技術会社に通勤しているあなたは、ClouderaのCCA175試験復習赤本試験認定を取得しましたか？CCA175試験復習赤本試験認定は給料の増加とジョブのプロモーションに役立ちます。

CCA175 PDF DEMO:

QUESTION NO: 1
. 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: 2
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: 3
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;

QUESTION NO: 4
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: 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.

ClouderaのPegasystems PEGACPCSD23V1認定試験は最近最も人気のある試験ですから、受験したいのですか。 人によって目標が違いますが、あなたにCloudera　Microsoft SC-100J試験に順調に合格できるのは我々の共同の目標です。 PMI PMP - 真実かつ信頼性の高いものだからこそ、NewValidDumpsの試験参考書は長い時間にわたってますます人気があるようになっています。 あなたに高品質で、全面的なMicrosoft MB-230J参考資料を提供することは私たちの責任です。 SAP C-SIGDA-2403 - きっとそれを望んでいるでしょう。

Updated: May 28, 2022