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Cloudera CCA175 Exam Overview:
| Certification Vendor: | Cloudera |
|---|---|
| Exam Name: | CCA Spark and Hadoop Developer Exam |
| Exam Number: | CCA175 |
| Available Languages: | English |
| Exam Price: | USD 295 |
| Certificate Validity Period: | 2 years |
| Passing Score: | 70% |
| Exam Format: | Live cluster environment, Performance-based, Hands-on tasks |
| Related Certifications: | CCP Data Engineer CCA Data Analyst |
| Exam Duration: | 120 minutes |
| Real Exam Qty: | 8-12 |
| 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 |
Difficulty in Writing CCA Spark and Hadoop Developer (CCA175) Exam
The difficulty in writing CCA Spark and Hadoop Developer (CCA175) Exam is not too difficult. The CCA Spark and Hadoop Developer (CCA175) Exam is a performance-based hands-on test that will assess your skills of Cloudera Enterprise Cluster. It has been designed to provide a challenging but fair exam for you to sharpen your skills. There are questions related to the Cloudera Enterprise Cluster environment that will test your skill on how well you know the subject of this certification exam. It is also an opportunity for you to prove yourself as a professional with an expertise in Cloudera Certified Advanced Architect- Data Engineer continuing education by passing this certification exam with good score. Processing in Cloudera Certified Advanced Architect- Data Engineer certification exam is in the format of performance-based hands-on test. This means that you will get the Cloudera Enterprise Cluster environment to practice, configure, monitor and apply your Cloudera knowledge.
Processing in Cloudera Certified Advanced Architect- Data Engineer exam is also in the format of performance-based hands-on test. This means that you will get the Cloudera Enterprise Cluster environment to practice, configure, monitor and apply your Cloudera knowledge. Cloudera CCA175 exam dumps questions will help you to prepare for the performance-based hands-on test in CCA Spark and Hadoop Developer (CCA175) exam. Genuine practice test is very close to the real performance-based hands-on test in Cloudera Certified Advanced Architect- Data Engineer certification exam.
Reference: https://www.cloudera.com/about/training/certification/cdhhdp-certification/cca-spark.html
CCA Spark and Hadoop Developer (CCA175) Exam Prep Materials
There are various materials to help you in prep for CCA Spark and Hadoop Developer (CCA175) Exam. These materials have been specifically designed to help you prepare for this exam. These materials will give you good understanding of the CCA Spark and Hadoop Developer (CCA175) Exam and how it is going to be given. Regular studying of these materials will be helpful for you to achieve success in the exam. Experience has shown that students who do well in the exam have been regular in reviewing these materials. Proves that the CCA Spark and Hadoop Developer (CCA175) Exam Prep Materials work for you. Cloudera CCA175 exam dumps questions can also help you. Proves that the CCA Spark and Hadoop Developer (CCA175) Exam Prep Materials work while taking the exam. Testimonials from candidates who have passed the examination will help you to judge how good these materials are.
Template of questions in CCA Spark and Hadoop Developer (CCA175) Exam Prep Materials are made to give you the same level of difficulty of the Cloudera Certified Advanced Architect- Data Engineer certification exam. Variety of tests is available in these materials. Standard tests are included for CCA Spark and Hadoop Developer (CCA175) Certification Exam Prep Materials to give you the same level of environment as the real exam. Extract from these materials can be directly used in the exam without any alteration. Processes in Cloudera Certified Advanced Architect- Data Engineer prep materials are explained well so that you can understand what you will have to do in the exam.
Objective of CCA Spark and Hadoop Developer (CCA175) Exam
Cloudera Certified Advanced Architect- Data Engineer (CCA175) is Cloudera's first certification to apply Spark and Hadoop to Java development. After the application of the certification, the technology will be applied to other Cloudera products besides big data. Content of Cloudera Certified Advanced Architect- Data Engineer (CCA175) certification is high level of expertise in Apache Spark and data processing. Change in IT requirements has made it necessary for your success in Cloudera Certified Advanced Architect- Data Engineer. We have designed the CCA Spark and Hadoop Developer (CCA175) questions with your success in mind. The certification exam is based on Cloudera technologies. Updates in the technology and trends and high level of expertise in the industry make it necessary for your success in Cloudera Certified Advanced Architect- Data Engineer exam. We have designed CCA Spark and Hadoop Developer (CCA175) questions with your success in mind.
Certificate for CCA Spark and Hadoop Developer (CCA175) will be awarded for the proven skills in Spark, Java, and Java MapReduce. Scored by Cloudera, the exam will be based on Apache Spark with programming in Java. Preparing for CCA175 exam will take you one step closer to achieving your goals. The CCA175 exam is based on experience in Apache Spark. Specialized skills in the AWS infrastructure will be tested by CCA175 exam questions. Tables and columns data structures, JavaScript, and functional programming will be tested by CCA175 exam questions.
Cloudera CCA175 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Transform, Stage, and Store Data | 35% | - Write transformed results back to HDFS - Load data from HDFS into Spark - Perform ETL operations using Spark API - Read/write various file formats (CSV, JSON, Avro, Parquet, etc.) |
| Data Analysis | 35% | - Join multiple datasets - Perform aggregations and calculations - Filter and sort datasets - Use Spark SQL and interact with Hive metastore - Create and query temporary views and tables |
| Data Ingestion | 20% | - Ingest data into HDFS using Flume - Ingest data into HDFS using Sqoop - Import/export data between relational databases and HDFS |
| Application Configuration and Execution | 10% | - Set memory, cores, and execution parameters - Use Spark Shell (Scala/PySpark) for interactive analysis - Submit Spark applications via spark-submit |
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