Huawei H13-723_V2.0 : HCIP-Big Data Developer V2.0

Exam Code: H13-723_V2.0

Exam Name: HCIP-Big Data Developer V2.0

Updated: Sep 05, 2026

Q & A: 370 Questions and Answers

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Huawei H13-723_V2.0 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Big Data Offline Batch Processing Scenario-based Solution	25%	- HDFS and YARN principles and configuration - Spark Core, Spark SQL and Catalyst optimization - Hive development, optimization and ACID transactions - Data ingestion tools: Loader, Sqoop, Flume
Topic 2: Big Data Application Development Overall Guide	15%	- Mainstream big data technologies and ecosystem - Application development process and specifications - Scenario-based solution design overview - FusionInsight HD architecture and components
Topic 3: Big Data Real-time Retrieval Scenario-based Solution	30%	- CarbonData and GaussDB(DWS) basics - Elasticsearch indexing, query and cluster management - HBase architecture, row-key design and optimization - Apache Phoenix and secondary indexes
Topic 4: Big Data Real-time Stream Computing Scenario-based Solution	30%	- Kafka architecture, transactions and configuration - Apache Flink: event time, watermark, windowing and state management - Flink SQL and complex event processing - Spark Structured Streaming fundamentals

Huawei HCIP-Big Data Developer V2.0 Sample Questions:

Question #1

existKafkain, aboutConsumerWhich statement is correct? (multiple choice)

A. multiple mouthsConsumerconfigure the samegroup.idwhen theseConsumerConsumed data will not be duplicated
B. Kou XinConsumerAPIConsumption data does not need to be specifiedZooKeeperaddress
C. mouthConsumerMainly for data consumption
D. mouthConsumerNeed to specify when consuming dataTopic

Answer: A,C,D

Question #2

existSpark, assuminglinesIs anDStreamobject, which of the following statements can periodically count this number of words on a stream?

A. lines.flatMap(_.split(" ")).map(word =>(word,word.length())).reduceByKey (_+_).print( )
B. lines.flatMap(_.split(" ")).map(word =>(word,1)).reduceByKey(_+_).print ( )
C. lines.flatMap(_.split(" ")).flatmap(word =>(word,1)).groupByKey(_+_).print ( )
D. lines.flatMap(_.split(" ")).map(word =>(word,1)).reduce(_+_).print( )

Answer: B

Question #3

SparkWhat kind of parameter setting methods does the application have? (multiple choice)

A. When submitting your application, by-confmake settings
B. In the application code, passSparkContextofsetPropertymethod to set
C. in the application configuration filespark-defaults.confconfigure in
D. In the application code, passSparkConfobject to set

Answer: A,C,D

Question #4

the following aboutHDFSIs the description correct?
(multiple choice)

A. HDFSDepend onNameNode,DataNode,Clientcomposition.
B. HDFSIt is suitable for the scenario of writing once and reading many times.
C. HDFSThe first copy of the data can be stored by using the rack node close to the client.
D. HDFSprepareNameNodeThe metadata on theNameNodeSync the past directly.

Answer: A,B,C

Question #5

existKafkamiddle,ProducerThis can be done by configuring the synchronization parameters (producer.type), to ensure that the data press

A. sent in order.
B. True
C. False

Answer: A

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