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Cloudera CCA175 Exam Prep Course (Premium File)
AI-Powered CCA Spark and Hadoop Developer Exam Exam - Pass on Your First Try

Last updated on May 17, 2026

CCA175 Practice Exam
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CCA175 Package
Premium File (PDF): 90 Questions
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Duration & Delievery: Self Paced
Last Updated: 17-May-2026
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All CCA Spark and Hadoop Developer Exam certification learning material, study guide, training courses are created by a team of Cloudera training experts. The Study Guide and .EXM training software files contain relevant CCA Spark and Hadoop Developer Exam content, labs, practice questions and explanation. This CCA175 exam guide and training courses is based on the latest exam outlines available!

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CCA Spark and Hadoop Developer Exam Study package designed to help you confidently pass your exam.

The CCA175 Exam Prep Features:

  • Contains the most relevant and up to date CCA175 study material covering all exam topics on the latest CCA175 certification.
  • A 90+% historical success rate, giving you confidence in your CCA175 exam preparation.
  • Includes a FREE CCA175 Mock exam software for added practice.
  • Free updates for 60 days, ensuring you have the latest CCA175 study content.
  • Instant access to download the study material, no waiting required.
  • Unlimited download access from any device, making studying convenient and easy.
  • Secure and real-time processing of payments through a 256-bit SSL system.
  • A responsive technical support team to provide you support 24/7.

Take the first step towards passing your CCA175 exam with ease by investing in our comprehensive certification exam material.

How to Prepare and Pass the Cloudera CCA175 Exam

Are you aspiring to become a certified Cloudera Data Engineer? The Cloudera CCA175 exam is a significant step towards achieving that goal. This article will guide you through the essential information about the CCA175 exam, including its objectives, preparation tips, and actionable strategies to help you succeed.

Understanding the Cloudera CCA175 Exam

The Cloudera CCA175 exam, officially known as the Cloudera Certified Associate - Spark and Hadoop Developer, validates your skills in data ingestion, transformation, and analysis using Apache Spark and Apache Hadoop. This certification is designed for professionals who work with big data, demonstrating their ability to write, maintain, and optimize Spark applications.

Here are the key details you should know about the CCA175 exam:

  • Exam Format: The exam is a hands-on, practical examination conducted on a Cloudera Enterprise cluster. You will be given a set of tasks to complete within a specific time frame.
  • Duration: The exam lasts for 120 minutes.
  • Passing Score: To pass the exam, you need to score at least 70%.
  • Prerequisites: There are no prerequisites for taking the CCA175 exam. However, Cloudera recommends having knowledge and experience in data processing, SQL, and programming in Scala or Python.

Preparing for the CCA175 Exam

Proper preparation is crucial for success in the CCA175 exam. Here are some actionable tips to help you prepare effectively:

  1. Review the Exam Objectives: Familiarize yourself with the exam objectives provided by Cloudera. Understanding what topics will be covered in the exam will help you structure your preparation plan.
  2. Gain Practical Experience: Hands-on experience with Apache Spark and Hadoop is essential. Set up a local development environment or use Cloudera QuickStart VM to gain practical experience in data ingestion, transformation, and analysis using Spark.
  3. Explore Official Documentation: Cloudera provides comprehensive documentation on Apache Spark and Hadoop. Study the official documentation to deepen your understanding of the tools and their functionalities.
  4. Practice with Sample Exercises: Cloudera offers sample exercises that mimic the exam environment. Practice these exercises to familiarize yourself with the type of tasks you may encounter during the exam.
  5. Join Study Groups or Forums: Engage with the Cloudera community by joining study groups or online forums. Collaborating with peers can enhance your learning experience and provide valuable insights.
  6. Take Mock Exams: Several online platforms offer mock exams for the CCA175 certification. Taking these exams will help you assess your knowledge and identify areas where you need improvement.
  7. Time Management: The CCA175 exam has a time constraint, so practice managing your time effectively during preparation. Allocate time for each task and aim to complete them within the given timeframe.

Exam-Day Tips

On the day of the CCA175 exam, it's essential to be well-prepared and manage your time wisely. Consider the following tips:

  • Read the Instructions: Carefully read the instructions provided at the beginning of the exam. Understand the tasks, requirements, and any constraints mentioned.
  • Plan Your Approach: Before starting the tasks, create a high-level plan of how you will tackle each one. Having a clear strategy will help you stay organized during the exam.
  • Review and Debug: After completing each task, review your work and double-check for any errors or bugs. Time permitting, debug and optimize your code for better performance.
  • Manage Time: Keep an eye on the time remaining and allocate it wisely across the tasks. If you encounter a particularly challenging task, consider flagging it and revisiting it later.
  • Stay Calm and Focused: Remain calm and focused throughout the exam. Avoid getting overwhelmed by challenging tasks and maintain a steady pace.

By following these preparation and exam-day tips, you can enhance your chances of success in the Cloudera CCA175 exam and earn your certification as a Cloudera Data Engineer. Best of luck!

Disclaimer: This article is provided as a general guide for informational purposes only. Please refer to the official Cloudera website for the most accurate and up-to-date information regarding the CCA175 exam.

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VirtuLearn AI

Question 20:

  • Correct answer: D and E.

  • Why: Provisioning a QnA Maker service creates:
- Azure App Service to host the QnA Maker web API (your App Service Plan AP1 will host the App Service resource). - Azure Cognitive Search to enable fast search over the knowledge base.
  • Why not the others:
- Language Understanding, Azure SQL Database, and Azure Storage are not automatically created by QnA Maker provisioning.
  • Quick note: After provisioning, check RG1 to verify the new App Service and Cognitive Search resources.

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what if different between speech recognizer and speach synthesizer

  • Speech Recognizer (Speech-to-Text): Converts audio input (live mic or audio file) into text. Output is transcripts with timestamps, confidence scores, and optional punctuation. Use cases: meeting transcripts, voice commands, real-time captions.

  • Speech Synthesizer (Text-to-Speech): Converts text (or SSML) into audio output. Output is audio data (wav/mp3 or streaming). Use cases: voice prompts, IVR responses, accessibility narrations. You can choose voices, languages, and adjust prosody (rate, pitch, volume).

  • Key differences:
- Input: Recognizer takes audio; Synthesizer takes text/SSML. - Output: Recognizer ? text; Synthesizer ? audio. - Features: Recognizer provides transcripts and timing; Synthesizer provides customizable voices (neural, SSML), multiple languages. - Typical scenarios: Transcription vs. generating spoken content.
  • Quick example: Use Speech Recognizer to transcribe a meeting; use Speech Synthesizer to read a script aloud in a chosen voice.

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Question 17:

  • Correct answer: A Anomaly Detector.

  • Why: Anomaly Detector is designed to identify unusual values in time-series data. Your scenario has 100 machines × 50 sensors, generating minute-by-minute data, totaling 5,000 time-series. Anomaly Detector can process each time-series (or batches of series) to flag deviations that may indicate potential failures, which is exactly what you need for predictive maintenance.

  • Why not the others:
- Cognitive Search is for indexing and querying content, not for detecting anomalies in time-series data. - Form Recognizer extracts data from forms, not time-series sensor data. - Custom Vision analyzes images, not numeric sensor streams.
  • Practical note: with 5,000 time series, you’d typically run anomaly detection per series (potentially in parallel) and aggregate results to identify which machines/sensors warrant attention.

Singapore, Singapore

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Question 12:

  • Correct answers: A, B, F.

  • Why:
- A. The index size will increase. Enabling CMK encryption adds encryption metadata and key management data, which increases index size. - B. Query times will increase. Encryption/decryption overhead and key retrieval can slow queries. - F. Azure Key Vault is required. CMK means you store/manage keys in Key Vault; it’s a billable, required service for CMK.
  • Why the other options are incorrect:
- C (self-signed X.509 certificate required) is not a requirement for CMK. - D (index size will decrease) and E (query times will decrease) contradict the expected impact of CMK.

Singapore, Singapore

VirtuLearn AI

GIF also we are using ?

  • No, GIF is not supported for Form Recognizer input. The allowed formats are JPG, PNG, PDF (text or scanned), or TIFF.
  • If you have GIFs, convert them to one of the supported formats (e.g., convert to JPG/PNG or PDF) before training or uploading.
  • Also ensure each file is under 50 MB and, when possible, use text-embedded PDFs to reduce errors.

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Question 11:

  • Correct answers: A, C, F.

  • Why:
- Form Recognizer accepts documents in these formats: JPG, PNG, PDF (text or scanned), or TIFF. (TIFF is sometimes used in archival/scanned docs.) - Text-embedded PDFs are preferred because they minimize character extraction and location errors. - Training data must be under 50 MB per file.
  • So A, C, and F are the three files that meet these input requirements; the other options (B, D, E) likely fail one of the criteria (wrong format or too large). If you want, describe the formats of A, C, and F to confirm they meet all three criteria.

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Question 10:
The correct answer is B: A new query key was generated.
Explanation:

  • The REST call to:
POST .../regenerateKey?api-version=2017-04-18 with body {"keyName": "Key2"} regenerates the specified account key.
  • Since you specified Key2, only the secondary key is regenerated; the primary key (Key1) remains unchanged.
  • This operation updates the Cognitive Services account keys within Azure, not anything in Azure Key Vault.
  • “Query key” refers to the key used to authorize API requests to the service (subscription key), so regenerating Key2 yields a new value for that key.

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Why pull first, its create is first is it
Yes. The sequence is correct because you need a base image first.

  • Step 1: Pull the base container image (Anomaly Detector) to have a starting point.
  • Step 2: Create a Dockerfile to capture the exact changes you want (reproducible build).
  • Step 3: Build and push the customized image to Azure Container Registry (ACR).
  • Step 4: Distribute a docker run script to deploy the container on devices.

Why not start with the Dockerfile? You need the base image to reference in the FROM line, and you can only push a built image to ACR, not an unbuilt modification.

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Question 5:

  • In Azure Resource Manager (ARM) REST APIs, creating or updating a resource is done with a PUT request to the resource’s exact URL (idempotent operation). This means you can repeatedly call the same PUT and it will create the resource if it doesn’t exist or update it if it does.
  • POST is used to create resources under a collection (without a predefined name), which would generate a new resource id each time and is not suitable when you need a single, known resource name and a single endpoint/key to consolidate billing and access.
  • For Question 5, you’re creating a new resource at a specific path (with a known resource name) to provide a single key/endpoint for multiple services. Therefore, PUT is the correct method.

If you’d like, I can outline the exact REST call structure (URL, headers, and body) for creating the Cognitive Services/related resource using PUT.

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Smila Vincent

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