H13-711_V3.5 is the new exam code of HCIA-Big Data Certification, the previous version 3.0 has been retired on June 16, 2023. To aid aspiring candidates in their preparation, PassQuestion team has recently cracked the latest HCIA-Big Data V3.5 H13-711_V3.5 Questions and Answers, providing invaluable study materials that guarantee a smooth pathway to success in the certification exam. The HCIA-Big Data V3.5 H13-711_V3.5 Questions and Answers compiled by PassQuestion offer comprehensive coverage of the exam syllabus, equipping candidates with the confidence and understanding needed to pass the certification with ease.

Holding the HCIA-Big Data Certification prove you can (1) Master the technical principles and architectures of common and important big data components, including HDFS, HBase, Hive, ClickHouse, MapReduce, YARN, Spark, Flink, Flume, Kafka, ElasticSearch and ZooKeeper, and capable of using Huawei big data platform MRS; (2) Able to operate and develop services based on Huawei MRS; (3) Competent for positions related to big data development engineers.

Target Audience:

The HCIA-Big Data Certification is intended for three primary target audiences:
Aspiring Big Data Engineers: Individuals who aspire to pursue a career in the field of big data engineering can use this certification as a stepping stone to enhance their technical expertise and gain industry-recognized validation.

HCIA-Big Data Certification Seekers: Professionals who seek to obtain the HCIA-Big Data certification can do so to bolster their resumes and stand out in a competitive job market. This certification serves as a strong testament to their capabilities in the realm of big data.

Junior Big Data Engineers: Junior-level big data engineers who wish to take their careers to the next level can leverage this certification to validate their existing skills and expand their knowledge base, opening up new opportunities for growth and advancement.

Prerequisites:

To enroll in the HCIA-Big Data Certification program, candidates should meet the following prerequisites:
Basic Knowledge of Network Technology: A fundamental understanding of network technology is essential as big data systems often rely on distributed architectures and network communication.

Familiarity with Linux Operating Systems: Candidates should be well-versed in basic operations on Linux operating systems, as this is a common environment for many big data applications.

Exam Information

Exam Code: H13-711
Exam Name: HCIA-Big Data V3.5
Exam Type: Written examination
Exam Format: Single-answer Question,Multiple-answer Question,True or false,Short Response Item,Drag and Drop Item
Time: 90min
Passing Score/Total Score: 600/1000
Exam Cost: 200USD
Language: Chinese,English

HCIA-Big Data V3.5 Exam Knowledge

Big Data Development Trends and the Kunpeng Big Data Solution   3%
HDFS — Hadoop Distributed File System & ZooKeeper   12%
HBase — Distributed Database & Hive — Distributed Data Warehouse   20%
ClickHouse — Online Analytical Processing Database Management System   8%
MapReduce and YARN Technical Principles   12%
Spark — In-memory Distributed Computing Engine & Flink — Stream and Batch Processing in a Single Engine   20%
Flume's Massive Log Aggregation & Kafka's Distributed Messaging System   12%
Elasticsearch — Distributed Search Engine  5%
MRS Huawei's Big Data Platform   4%
Huawei DataArts Studio   4%

View Online HCIA-Big Data V3.5 H13-711_V3.5 Free Questions

1. Which of the following HDFS commands can be used to check the integrity of data blocks?
A. HDFS fsck /
B. HDFS fsck -delete
C. HDFS dfsadmin -report
D. HDFS balancer -threshold 1
Answer: A

2. Where is the Meta Region routing information of HBase metadata stored in?
A. Root table
B. Zookeeper
C. HMaster
D. Meta table
Answer: B 

3. What is the purpose of the HBase cluster to perform compaction regularly? (Multiple choice)
A. Reduce the number of files in the same Region and ColumnFamily
B. Improve data reading performance
C. Reduce the file data of the same ColumnFamily
D. Reduce the number of files in the same Region
Answer: ABD 

4. Which of the following descriptions of Hive features are incorrect?
A. Flexible and convenient ETL
B. Only supports MapReduce computing engine
C. Can directly access HDFS files and HBase
D. Easy to use and easy to program
Answer: B 

5. Which of the following functions can Spark provide? (Multiple choice)
A. Distributed memory computing engine
B. Distributed File System
C. Unified scheduling of cluster resources
D. Stream processing function
Answer: AD 

6. Which of the following descriptions of Flink key features are wrong?
A. Compared with Flink, SparkStreaming has lower latency
B. The Flink streaming engine can provide functions that support stream processing and batch
processing applications at the same time
C. Compared with Streaming in Fusionlnght HD, Flink has higher throughput
D. checkpoint realizes Flink's fault tolerance
Answer: A