Prepare and pass exam with our Cloudera CCA175 training material, here you will achieve your dream easily With TrainingQuiz!
Updated: Oct 17, 2026
No. of Questions: 96 Questions & Answers with Testing Engine
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| Certification Vendor: | Cloudera |
|---|---|
| Exam Name: | CCA Spark and Hadoop Developer Exam |
| Exam Number: | CCA175 |
| Related Certifications: | CCP Data Engineer CCA Data Analyst |
| Exam Format: | Live cluster environment, Performance-based, Hands-on tasks |
| Available Languages: | English |
| Exam Price: | USD 295 |
| Real Exam Qty: | 8-12 |
| Certificate Validity Period: | 2 years |
| Exam Duration: | 120 minutes |
| Passing Score: | 70% |
| Recommended Training: | Cloudera Developer Training for Spark and Hadoop |
| Exam Registration: | Cloudera Certification Portal |
| Sample Questions: | Cloudera CCA175 Sample Questions |
| Exam Way: | Online proctored, delivered remotely via secure browser |
| Pre Condition: | No formal prerequisites; recommended experience with Scala/Python, HDFS, Hive, Sqoop, Flume, and Spark |
| Official Syllabus URL: | https://www.cloudera.com/about/training/certification/cdhhdp-certification/cca-spark.html |
Incorrect answers are being ignored to get success in the exam. Correct answers are being used to get success in the exam. CCA175 Exam is based on Cloudera technologies. Questions of CCA175 exam are analyzed in a perfect manner. Scenarios of CCA175 exam are analyzed in the most appropriate manner. Cloudera CCA175 exam dumps are of great use to get success in the exam. Solved CCA175 exam questions are sufficient to get success in the exam. Streaming data is being used to get success in the exam. Free CCA175 exam questions are being provided for the candidates. Syllabus of CCA175 exam is sufficient to get success in the exam. Code of CCA175 exam questions is enough to get success in the exam. Querying abilities are being used to get success in the exam. Associate the exam questions with the real exam. Sqoop is being used to solve the CCA175 exam questions. Configuration of CCA175 exam questions is sufficient to get success in the exam. Interview of Cloudera Certified Advanced Architect- Data Engineer exam is sufficient to get success in the exam.
CCA Spark and Hadoop Developer (CCA175) is an exam intended for certification of professionals who are experienced in applying Cloudera technologies to develop applications. Executed by Cloudera, the CCA Spark and Hadoop Developer (CCA175) exam tests candidates' knowledge in Spark, the Java programming language, Hadoop MapReduce (MR), and other related skills. Exponentially growing IT market has made it necessary for your success in Cloudera Certified Advanced Architect- Data Engineer. Covered in the Cloudera Certified Advanced Architect- Data Engineer exam questions are the aspects of the software, Cloudera management, live data, Hadoop Distributed File Systems, and other technologies. Package Cloudera technical interview questions are used for this exam. The candidates have to provide the right answers according to the scenario and if they failed to produce any answer, then they may get the question repeated again. Cloudera CCA175 exam dumps can be helpful in your success because you will get a well-formatted question from which you can predict the answer to the upcoming question.
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Reference: https://www.cloudera.com/about/training/certification/cdhhdp-certification/cca-spark.html
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Ingestion | 20% | - Import/export data between relational databases and HDFS - Ingest data into HDFS using Flume - Ingest data into HDFS using Sqoop |
| Topic 2: Application Configuration and Execution | 10% | - Submit Spark applications via spark-submit - Set memory, cores, and execution parameters - Use Spark Shell (Scala/PySpark) for interactive analysis |
| Topic 3: Transform, Stage, and Store Data | 35% | - Load data from HDFS into Spark - Read/write various file formats (CSV, JSON, Avro, Parquet, etc.) - Write transformed results back to HDFS - Perform ETL operations using Spark API |
| Topic 4: Data Analysis | 35% | - Use Spark SQL and interact with Hive metastore - Join multiple datasets - Create and query temporary views and tables - Perform aggregations and calculations - Filter and sort datasets |
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