CCA175 exam material & Free CCA175 AI Tutor

QUESTION: 1

CORRECT TEXT
Problem Scenario 28 : You need to implement near real time solutions for collecting information when submitted in file with below
Data
echo "IBM, 100, 20160104" >> /tmp/spooldir2/.bb.txt
echo "IBM, 103, 20160105" >> /tmp/spooldir2/.bb.txt
mv /tmp/spooldir2/.bb.txt /tmp/spooldir2/bb.txt
After few mins
echo "IBM, 100.2, 20160104" >> /tmp/spooldir2/.dr.txt
echo "IBM, 103.1, 20160105" >> /tmp/spooldir2/.dr.txt
mv /tmp/spooldir2/.dr.txt /tmp/spooldir2/dr.txt
You have been given below directory location (if not available than create it) /tmp/spooldir2 .
As soon as file committed in this directory that needs to be available in hdfs in /tmp/flume/primary as well as /tmp/flume/secondary location.
However, note that/tmp/flume/secondary is optional, if transaction failed which writes in this directory need not to be rollback.
Write a flume configuration file named flumeS.conf and use it to load data in hdfs with following additional properties .

1. Spool /tmp/spooldir2 directory
2. File prefix in hdfs sholuld be events
3. File suffix should be .log
4. If file is not committed and in use than it should have _ as prefix.
5. Data should be written as text to hdfs

See the explanation for Step by Step Solution and configuration.

Answer(s): A

Explanation:

Solution :Step 1: Create directory mkdir /tmp/spooldir2
Step 2: Create flume configuration file, with below configuration for source, sink and channel and save it in flume8.conf.
agent1 .sources = source1
agent1.sinks = sink1a sink1bagent1.channels = channel1a channel1b
agent1.sources.source1.channels = channel1a channel1b agent1.sources.source1.selector.type = replicating
agent1.sources.source1.selector.optional = channel1b agent1.sinks.sink1a.channel = channel1a
agent1 .sinks.sink1b.channel = channel1b
agent1.sources.source1.type = spooldir
agent1 .sources.sourcel.spoolDir = /tmp/spooldir2
agent1.sinks.sink1a.type = hdfs
agent1 .sinks, sink1a.hdfs. path = /tmp/flume/primary agent1 .sinks.sink1a.hdfs.tilePrefix = events
agent1 .sinks.sink1a.hdfs.fileSuffix = .log
agent1 .sinks.sink1a.hdfs.fileType = Data Stream
agent1 .sinks.sink1b.type = hdfs
agent1 .sinks.sink1b.hdfs.path = /tmp/flume/secondary agent1 .sinks.sink1b.hdfs.filePrefix = events
agent1.sinks.sink1b.hdfs.fileSuffix = .log
agent1 .sinks.sink1b.hdfs.fileType = Data Stream
agent1.channels.channel1a.type = file
agent1.channels.channel1b.type = memory
step 4 : Run below command which will use this configuration file and append data in hdfs.
Start flume service:
flume-ng agent -conf /home/cloudera/flumeconf -conf-file /home/cloudera/flumeconf/flume8.conf --name age
Step 5: Open another terminal and create a file in /tmp/spooldir2/
echo "IBM, 100, 20160104" » /tmp/spooldir2/.bb.txt
echo "IBM, 103, 20160105" » /tmp/spooldir2/.bb.txt mv /tmp/spooldir2/.bb.txt /tmp/spooldir2/bb.txt
After few mins
echo "IBM.100.2, 20160104" »/tmp/spooldir2/.dr.txt
echo "IBM, 103.1, 20160105" » /tmp/spooldir2/.dr.txt mv /tmp/spooldir2/.dr.txt /tmp/spooldir2/dr.txt

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QUESTION: 2 CORRECT TEXT

Problem Scenario 83 : In Continuation of previous question, please accomplish following activities.

1. Select all the records with quantity >= 5000 and name starts with 'Pen'
2. Select all the records with quantity >= 5000, price is less than 1.24 and name starts with
'Pen'
3. Select all the records witch does not have quantity >= 5000 and name does not starts
with 'Pen'
4. Select all the products which name is 'Pen Red', 'Pen Black'
5. Select all the products which has price BETWEEN 1.0 AND 2.0 AND quantity
BETWEEN 1000 AND 2000.

See the explanation for Step by Step Solution and configuration.

Answer(s): A

Explanation:

Solution :Step 1: Select all the records with quantity >= 5000 and name starts with 'Pen' val results = sqlContext.sql(......SELECT * FROM products WHERE quantity >= 5000 AND name LIKE 'Pen %.......)
results.show()
Step 2: Select all the records with quantity >= 5000 , price is less than 1.24 and name starts with 'Pen'
val results = sqlContext.sql(......SELECT * FROM products WHERE quantity >= 5000 AND price < 1.24 AND name LIKE 'Pen %.......)
results. showQ
Step 3: Select all the records witch does not have quantity >= 5000 and name does not starts with 'Pen'
val results = sqlContext.sql('.....SELECT * FROM products WHERE NOT (quantity >= 5000 AND name LIKE 'Pen %')......)
results. showQ
Step 4: Select all the products wchich name is 'Pen Red', 'Pen Black' val results = sqlContext.sql('.....SELECT' FROM products WHERE name IN ('Pen Red', 'Pen Black')......)
results. showQ
Step 5: Select all the products which has price BETWEEN 1.0 AND 2.0 AND quantity BETWEEN 1000 AND 2000.
val results = sqlContext.sql(......SELECT * FROM products WHERE (price BETWEEN 1.0 AND 2.0) AND (quantity BETWEEN 1000 AND 2000)......) results. show()

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QUESTION: 3 CORRECT TEXT

Problem Scenario 82 : You have been given table in Hive with following structure (Which you have created in previous exercise).
productid int code string name string quantity int price float
Using SparkSQL accomplish following activities.

1. Select all the products name and quantity having quantity <= 2000
2. Select name and price of the product having code as 'PEN'
3. Select all the products, which name starts with PENCIL
4. Select all products which "name" begins with 'P\ followed by any two characters,
followed by space, followed by zero or more characters

See the explanation for Step by Step Solution and configuration.

Answer(s): A

Explanation:

Solution :
Step 1: Copy following tile (Mandatory Step in Cloudera QuickVM) if you have not done it.
sudo su root
cp /usr/lib/hive/conf/hive-site.xml /usr/lib/sparkVconf/
Step 2: Now start spark-shell
Step 3 ; Select all the products name and quantity having quantity <= 2000 val results = sqlContext.sql(......SELECT name, quantity FROM products WHERE quantity <= 2000......)
results.showQ
Step 4: Select name and price of the product having code as 'PEN' val results = sqlContext.sql(......SELECT name, price FROM products WHERE code = 'PEN.......)
results. showQ
Step 5: Select all the products , which name starts with PENCIL val results = sqlContext.sql(......SELECT name, price FROM products WHERE upper(name) LIKE 'PENCIL%.......}
results. showQ
Step 6: select all products which "name" begins with 'P', followed by any two characters, followed by space, followed byzero or more characters -- "name" begins with 'P', followed by any two characters,
- followed by space, followed by zero or more characters val results = sqlContext.sql(......SELECT name, price FROM products WHERE name LIKE 'P_ %.......)
results. show()

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QUESTION: 4 CORRECT TEXT

Problem Scenario 20 : 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.

1. Write a Sqoop Job which will import "retaildb.categories" table to hdfs, in a directory
name "categories_targetJob".

See the explanation for Step by Step Solution and configuration.

Answer(s): A

Explanation:

Solution :Step 1: Connecting to existing MySQL Database mysql -user=retail_dba -- password=cloudera retail_db
Step 2: Show all the available tables show tables;
Step 3: Below is the command to create Sqoop Job (Please note that - import space is mandatory)
sqoop job -create sqoopjob \ -- import \
-connect "jdbc:mysql://quickstart:3306/retail_db" \
-username=retail_dba \
-password=cloudera \
-table categories \
-target-dir categories_targetJob \
-fields-terminated-by '|' \
-lines-terminated-by '\n'
Step 4: List all the Sqoop Jobs sqoop job --list
Step 5: Show details of the Sqoop Job sqoop job --show sqoopjob
Step 6: Execute the sqoopjob sqoopjob --exec sqoopjob
Step 7: Check the output of import job
hdfs dfs -Is categories_target_job
hdfs dfs -cat categories_target_job/part*

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QUESTION: 5 CORRECT TEXT

Problem Scenario 59 : You have been given below code snippet.
val x = sc.parallelize(1 to 20)
val y = sc.parallelize(10 to 30) operationl
z.collect
Write a correct code snippet for operationl which will produce desired output, shown below. Array[lnt] = Array(16, 12, 20, 13, 17, 14, 18, 10, 19, 15, 11)

See the explanation for Step by Step Solution and configuration.

Answer(s): A

Explanation:

Solution :
val z = x.intersection(y)
intersection : Returns the elements in the two RDDs which are the same.

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DAX Transaction Category = CALCULATE( MAX('Transaction Size'[Size]), FILTER( 'Transaction Size', AND( Sales[Sales Amount] >= 'Transaction Size'[Minimum], Sales[Sales Amount] <= 'Transaction Size'[Maximum] ) ) )

Cloudera CCA175: Skills Tested, Job Roles, and Study Tips

The CCA Spark and Hadoop Developer Exam is designed for professionals who need to demonstrate their ability to develop, maintain, and optimize Apache Spark and Hadoop applications. This certification is primarily targeted at data engineers, software developers, and data scientists who work within the Cloudera ecosystem to process large-scale datasets. Employers in the big data and analytics sectors value this certification because it validates a candidate's hands-on proficiency in writing code that interacts with distributed systems. By earning this Cloudera certification, professionals prove they possess the technical competence required to handle complex data transformation, ingestion, and analysis tasks in production environments. It serves as a benchmark for technical skill, ensuring that developers can effectively navigate the challenges of distributed computing and data processing.

The role of a Spark and Hadoop developer is critical in organizations that rely on data-driven decision-making, as these individuals are responsible for the underlying infrastructure that powers analytics. Companies hiring for these positions look for candidates who can not only write functional code but also optimize it for performance and scalability within a cluster. Because the CCA175 exam focuses on practical application, it ensures that certified individuals are ready to contribute to development teams immediately upon hiring. This certification is often a prerequisite for roles involving data pipeline architecture, ETL process development, and real-time data streaming. Ultimately, the exam validates that a developer understands the nuances of the Hadoop ecosystem and can apply that knowledge to solve real-world business problems.

What the CCA175 Exam Covers

The CCA175 exam evaluates a candidate's ability to perform specific technical tasks using Apache Spark and Hadoop, focusing heavily on data ingestion, transformation, and analysis. Candidates are expected to demonstrate proficiency in reading and writing data in various formats, such as Parquet, Avro, and JSON, while managing data schemas effectively. The exam also tests the ability to manipulate data using Spark SQL and the Spark API, requiring developers to perform complex joins, aggregations, and filtering operations. Our practice questions are designed to mirror these core competencies, allowing you to test your knowledge across the entire spectrum of the exam objectives. By working through these practice questions, you gain exposure to the types of coding scenarios you will encounter, ensuring you are comfortable with the syntax and logic required for successful data processing.

One of the most technically demanding areas of the exam involves performance tuning and troubleshooting within a Spark environment. Candidates must demonstrate a deep understanding of how to optimize Spark jobs, including managing memory allocation, understanding shuffle operations, and effectively using caching strategies. This requires more than just basic coding skills; it demands an analytical mindset to identify bottlenecks and implement efficient solutions that minimize resource consumption. Because these tasks are complex, they often form the core of the most challenging practice questions, requiring you to think critically about how your code will execute on a distributed cluster. Mastering these concepts is essential for passing the certification exam, as it separates those who can write code from those who can write performant, production-ready applications.

Are These Real CCA175 Exam Questions?

Our platform provides access to practice questions that are sourced and verified by the community, including IT professionals and recent test-takers who have successfully passed the actual exam. These questions reflect what appears on the real exam because they are sourced from the community, ensuring that the material remains relevant to the current exam objectives. If you've been searching for CCA175 exam dumps or braindump files, our community-verified practice questions offer something more valuable, each question is verified and explained by IT professionals who recently passed the exam. We prioritize accuracy and pedagogical value over simple memorization, ensuring that you are learning the underlying concepts rather than just the answers. This community-verified approach provides a reliable way to gauge your readiness for the certification exam without relying on unauthorized or leaked content.

The community verification process is a cornerstone of our platform, where users actively discuss answer choices, flag potentially incorrect information, and share context from their own recent exam experiences. When a question is flagged, it is reviewed by other members of the community who have hands-on experience with the CCA175, ensuring that the explanations are technically sound and aligned with Cloudera's standards. This collaborative environment allows you to see different perspectives on how to solve a specific problem, which is invaluable for understanding the nuances of Spark and Hadoop development. By engaging with these discussions, you gain insights that go beyond what is found in standard textbooks, making your exam preparation much more effective. This transparency and collective effort are what make our practice questions a trusted resource for candidates aiming to pass the exam.

How to Prepare for the CCA175 Exam

Effective exam preparation for the CCA175 requires a combination of theoretical study and hands-on practice in a real or sandbox environment. You should focus on building a consistent study schedule that allows you to experiment with Spark code, test different configurations, and observe how your changes impact job performance. Relying solely on documentation is rarely enough; you must actively write and debug code to internalize the syntax and logic required for the exam. Every practice question includes a free AI Tutor explanation that breaks down the reasoning behind the correct answer, so you understand the concept, not just the answer. This AI Tutor serves as an on-demand resource to clarify complex topics, helping you bridge the gap between reading about a concept and applying it in a coding scenario.

A common mistake candidates make is attempting to memorize the answers to practice questions rather than understanding the underlying logic of the Spark and Hadoop ecosystem. The CCA175 is a scenario-based exam, meaning it tests your ability to apply knowledge to new, unfamiliar problems rather than recalling static facts. To avoid this pitfall, you should treat every practice question as a mini-project where you analyze the requirements, draft a solution, and then compare your approach with the provided explanation. Additionally, time management is a critical skill to develop during your exam prep; practice solving problems under time constraints to ensure you can complete the tasks within the allotted exam duration. By focusing on deep understanding and practical application, you will be much better prepared to handle the challenges of the actual certification exam.

What to Expect on Exam Day

On the day of your CCA175 exam, you should be prepared for a performance-based assessment that requires you to solve real-world coding problems within a live environment. Unlike traditional multiple-choice exams, this Cloudera certification exam typically involves hands-on tasks where you must write, test, and execute code to achieve specific data processing outcomes. You will be provided with a cluster environment, and your success depends on your ability to navigate this environment, use the provided tools, and produce the correct output. The exam is administered through a secure testing platform, often via remote proctoring or at a designated testing center, ensuring the integrity of the assessment process. Being familiar with the interface and the typical workflow of these tasks is essential for maintaining your composure and focus throughout the duration of the exam.

Because the exam is performance-based, you should expect to spend a significant amount of time writing and debugging code, which makes familiarity with the Spark API and Hadoop ecosystem absolutely vital. You will need to be comfortable working in a command-line interface and using standard development tools to manipulate data efficiently. The exam is designed to test your practical skills, so there is no substitute for the experience gained through hands-on practice. Ensure that you have reviewed the official exam objectives provided by Cloudera to understand the specific scope of the tasks you will be asked to perform. By arriving prepared with both technical knowledge and experience in the testing environment, you can approach the exam with confidence.

Who Should Use These CCA175 Practice Questions

These practice questions are intended for data engineers, developers, and data scientists who have some experience working with big data technologies and are looking to validate their skills through the CCA175 certification exam. Typically, candidates should have a foundational understanding of Java or Scala, as well as experience with the Hadoop ecosystem, before beginning their exam preparation. Whether you are looking to advance your career, prove your expertise to potential employers, or simply sharpen your technical skills, this certification is a recognized standard in the industry. Our platform is designed to support professionals who are serious about their career growth and want to ensure they are fully prepared for the rigors of the certification exam. By using these resources, you are taking a proactive step toward mastering the tools and techniques required for success in the big data field.

To get the most out of these practice questions, do not simply read the answer; instead, engage with the AI Tutor explanation to understand the "why" behind each solution. Read the community discussions to see how others have approached the same problems, and make sure to flag any questions you get wrong so you can revisit them later. This iterative process of testing, reviewing, and refining your knowledge is the most effective way to build the confidence needed for the actual exam. Browse the questions above and use the community discussions and AI Tutor to build real exam confidence.

Cloudera CCA175 Exam Prep CCA Spark and Hadoop Developer Exam (Page 2 )

QUESTION: 1

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QUESTION: 2 CORRECT TEXT

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QUESTION: 3 CORRECT TEXT

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QUESTION: 4 CORRECT TEXT

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QUESTION: 5 CORRECT TEXT

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Cloudera CCA175: Skills Tested, Job Roles, and Study Tips

What the CCA175 Exam Covers

Are These Real CCA175 Exam Questions?

How to Prepare for the CCA175 Exam

What to Expect on Exam Day

Who Should Use These CCA175 Practice Questions

Cloudera CCA175 Exam Prep
CCA Spark and Hadoop Developer Exam (Page 2 )