Updated: Aug 13, 2026
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| Certification Vendor: | Huawei |
| Exam Name: | Huawei Certified ICT Associate - Big Data V3.5 |
| Exam Number: | H13-711_V3.5 |
| Available Languages: | English, Chinese, Spanish |
| Certificate Validity Period: | 3 years |
| Real Exam Qty: | 60 |
| Exam Duration: | 90 minutes |
| Passing Score: | 600/1000 |
| Exam Price: | USD 200 |
| Related Certifications: | HCIP-Big Data HCIE-Big Data |
| Exam Format: | Single-choice, Multiple-choice, True/False, Short answer, Drag and drop |
| Recommended Training: | HCIA-Big Data V3.5 Official Training Course |
| Exam Registration: | Pearson VUE Registration Huawei Talent Online |
| Sample Questions: | Huawei H13-711_V3.5 Sample Questions |
| Exam Way: | Online proctored or onsite at Pearson VUE test centers |
| Pre Condition: | Basic knowledge of Linux operation and Hadoop principles is recommended; no mandatory prerequisites |
| Official Syllabus URL: | https://e.huawei.com/en/talent/certification/exam/h13-711_v3.5 |
| Section | Weight | Objectives |
|---|---|---|
| Big Data Industry Overview & Basic Concepts | 8% | - Huawei Kunpeng big data ecosystem - Development trend and characteristics of big data - Application scenarios and value of big data |
| Spark & Flink | 20% | - Flink stream processing, architecture, API and application development - Spark core architecture, RDD, DataFrame, SQL and streaming processing |
| ClickHouse & Elasticsearch | 8% | - Elasticsearch search engine, indexing and analysis - ClickHouse architecture, storage and query features |
| MapReduce & YARN | 12% | - MapReduce programming model and execution process - YARN architecture, resource scheduling and management |
| HDFS & ZooKeeper | 12% | - HDFS architecture, principle and operation - ZooKeeper core functions and working mechanism |
| Huawei Big Data Platform MRS & DataArts Studio | 8% | - MRS platform architecture, components and operation - DataArts Studio data development and governance - Typical industry solutions and cases |
| HBase & Hive | 20% | - HBase architecture, data model, design and operation - Hive data warehouse principle, table design, SQL and optimization |
| Flume & Kafka | 12% | - Flume data collection mechanism and configuration - Kafka message system, storage, transmission and application |
1. Regarding the warning of insufficient Kafka disk capacity, which of the following analysis is wrong for the possible reasons?
A) The disk configuration used to store Kafka data (such as the number and size of disks, etc.) cannot meet the current business data flow declaration, causing the disk usage to reach the upper limit
B) The data storage time is configured too long, and the data accumulation reaches the upper limit of disk usage
C) Unreasonable business planning, resulting in uneven data distribution, causing some disks to reach the upper limit of usage
D) Broker node failure causes
2. Hive is a data warehouse processing tool that uses the SQL-like HiveQL language to implement data query functions. All Hive data are stored in HDFS.
A) False
B) True
3. The Fusionlnsight HD cluster contains many kinds of services, and each service is composed of several roles. Which of the following are the roles of the service? (Multiple choice)
A) NameNode
B) DataNodes
C) HDFS
D) HBase
4. In Hadoop, if yarn.scheduler.capacity.root.QueueA.minimum-user-limit-percent is set to 50, which of the following statements is wrong?
A) If there are already 2 user tasks running in QueueA, the task submitted by the third user needs to wait for the release of resources
B) A user submitting a task can use 100% of QueueA's resources
C) QueueA must guarantee that each user gets at least 50% of the resources
D) Each user in QueueA can only get up to 50% of the resources
5. Spark and Hadoop are equally unsuitable for generational computing.
A) False
B) True
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: B | Question # 3 Answer: A,B | Question # 4 Answer: D | Question # 5 Answer: A |
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