Huawei HCIA-Big Data V3.0 : H13-711_V3.0-ENU

H13-711_V3.0-ENU real exams

Exam Code: H13-711_V3.0-ENU

Exam Name: HCIA-Big Data V3.0

Updated: Sep 13, 2026

Q & A: 646 Questions and Answers

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Huawei H13-711_V3.0-ENU Exam Syllabus Topics:

SectionWeightObjectives
Huawei Big Data Solution4%- Platform functions and industry cases
- FusionInsight HD/MRS overview
Flume Log Collection7%- Flume architecture and components
- Data collection workflow
Elasticsearch Search Engine5%- Architecture and indexing mechanism
- Full-text search and analysis
Redis In-Memory Database5%- Data types and storage structure
- High availability and application scenarios
Big Data Development Trend & Kunpeng Big Data Solution3%- Huawei Kunpeng big data overview
- Big Data industry development trends
- Characteristics of big data
HBase Distributed Database10%- HBase architecture and data model
- HBase table design and application scenarios
- HBase read/write process
Spark Distributed Computing Framework12%- Spark architecture and RDD concept
- Spark SQL and Spark Streaming
- Spark task scheduling and optimization
Flink Stream Processing Framework8%- Event time and window mechanism
- Flink architecture and data flow model
- Stream processing scenarios
MapReduce & YARN12%- YARN architecture and resource scheduling
- MapReduce programming model and workflow
- Task execution and resource management
Hive Distributed Data Warehouse10%- Hive data model and SQL
- Hive architecture and components
- Hive data storage and query execution
LDAP & Kerberos Security5%- Kerberos authentication process
- Unified authentication principles
Kafka Messaging System9%- Message production and consumption
- Kafka architecture and core concepts
HDFS & ZooKeeper12%- HDFS architecture and principles
- ZooKeeper architecture and coordination mechanism
- HDFS data storage and fault tolerance
Loader Data Conversion5%- Loader functions and use cases
- Data import/export process

Huawei HCIA-Big Data V3.0 Sample Questions:

Question #1

The picture below shows Sparke&MapReduce performance comparison data, it can be concluded that compared with MapReducei computing, Spark uses( )resources, get( )double the performance?

  • A. 1/8, 3
  • B. 1/8, 4
  • C. 1/10, 4
  • D. 1/10, 3
Answer: D
Question #2

The Fusionlnsight HD management node provides a dual-machine HA mechanism. After the primary node fails, the primary and secondary nodes need to manually implement Failover.

  • A. False
  • B. True
Answer: A
Question #3

In order to consider performance optimization. It is recommended to deploy LdapServer and KrbServer on the same node in all clusters

  • A. False
  • B. True
Answer: B
Question #4

There are 230 nodes in the FusionlnsightHD cluster of a university. Which of the following processes should be deployed on the data nodes during cluster planning?

  • A. SolrServer
  • B. RegionServer
  • C. DataNode
  • D. NameNode
  • E. NodeManager
  • F. DBServer
Answer: A,B,C,E
Question #5

Which of the following scenarios is Flumej suitable for data collection?

  • A. Local file data collection
  • B. Collect data on data sources such as Thrift, Avro, Syslog, Kafka, etC.
  • C. Real-time data collection of large amounts of data
  • D. Collection of logs generated by the application system
Answer: A,B,D

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