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Huawei H13-711-ENU Exam Syllabus Topics:

SectionObjectives
Big Data Storage and Processing- Distributed Computing
  • 1. Spark basic architecture and usage
    - Data Warehousing and Query
    • 1. Hive fundamentals and SQL-based processing
      Data Ingestion and Integration- Data Collection Technologies
      • 1. Basic concepts of Kafka and message queues
        Big Data Operation and Security- Cluster Management
        • 1. Basic cluster monitoring and maintenance
          - Data Security
          • 1. Access control and data protection basics
            Big Data Fundamentals- Introduction to Big Data
            • 1. Big data application scenarios
              • 2. Big data concepts and characteristics
                Hadoop Ecosystem- YARN
                • 1. Resource management principles
                  - MapReduce
                  • 1. Job execution flow
                    • 2. MapReduce processing model
                      - HDFS
                      • 1. Data storage and replication mechanism
                        • 2. HDFS architecture and components

                          Huawei HCIA-Big Data(Huawei Certified ICT Associate-Big Data) Sample Questions:

                          1. Spark, like Hadoop, is not suitable for iterative computing.

                          A) True
                          B) False


                          2. Huawei Cloud MapReduce service provides a one-stop enterprise-level big data cluster cloud service that is fully controllable by tenants. The flexible and easy-to-use full-stack big data platform can easily run Hadoop, Spark, HBase, Kafka, Storm and other big data components, realize real-time and offline analysis and mining, and discover new business opportunities.

                          A) True
                          B) False


                          3. Which of the following is the correct step for row data conversion in Fusioninsight HD?

                          A) Load, Transform, Extract
                          B) Load, Transform, Export
                          C) Input Setup, Conversion, Output
                          D) Extraction, transformation, output


                          4. Spark divides the stages according to the dependencies of RDDs. The scheduler starts from the end of the DAG graph and traverses the entire dependency chain in reverse. When it encounters narrow dependencies, it disconnects, and when it encounters wide dependencies, it adds them to the current stage.

                          A) True
                          B) False


                          5. What are the main characteristics of technologies related to big data analysis? (Multiple choice)

                          A) Event correlation analysis behind the data
                          B) Machine learning, full features
                          C) Based on massive data
                          D) Based on exact samples


                          Solutions:

                          Question # 1
                          Answer: B
                          Question # 2
                          Answer: A
                          Question # 3
                          Answer: C
                          Question # 4
                          Answer: B
                          Question # 5
                          Answer: A,B,C

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