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  • Exam Code: H13-723-ENU
  • Exam Name: HCIP-Big Data Developer
  • No. of Questions: 155 Questions and Answers
  • Updated: Jul 27, 2026

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Huawei H13-723-ENU Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Big Data Application Development Overall Guide15%- Big Data Application Development Fundamentals
  • 1. Big Data Architecture and Ecosystem
    • 2. Huawei MRS Platform Overview
      • 3. Development Environment and Tools
        Topic 2: Big Data Real-time Stream Computing Scenario-based Solution30%- Streaming Data Processing
        • 1. Real-time Data Analysis
          • 2. Stream Processing Application Development
            • 3. Spark Streaming
              • 4. Kafka Messaging
                Topic 3: Big Data Real-time Retrieval Scenario-based Solution30%- Real-time Query and Search
                • 1. Index Management and Search Optimization
                  • 2. Elasticsearch Fundamentals
                    • 3. Data Ingestion and Retrieval
                      Topic 4: Big Data Offline Batch Processing Scenario-based Solution25%- Offline Data Processing
                      • 1. HDFS and Data Storage
                        • 2. Spark Batch Computing
                          • 3. MapReduce Development
                            • 4. Hive Data Warehouse Development

                              Huawei HCIP-Big Data Developer Sample Questions:

                              1. A large manufacturing company plans to transform its internal logistics data and sales data into big data. The design department has given an analysis of the data storage plan. Which of the following descriptions is correct?

                              A) HBase can be built on ordinary commercial servers, and the construction cost is relatively low.
                              B) Logistics data is very sparse, and HBase can efficiently process sparse data.
                              C) HBase stores massive data and supports dynamic expansion, which can fulfill the storage requirements of logistics and sales data.
                              D) Hbase supports efficient random reading, and can complete real-time analysis and command of the logistics situation after a reasonable design.


                              2. In FusionInsight HD's Hive, the user-defined UDF can have the same name as the Hive built-in UDF. In this case, the user-defined UDF will be used.

                              A) True
                              B) False


                              3. In Spark, assuming that lines is a DStream object, the filter statement can filter out 80% of the data. Which statement is correct for the following two statements:
                              X: lines.filter(...).groupByKey(...)
                              Y: lines.groupByKey(...).filter(...)

                              A) X has higher performance than Y
                              B) X has lower performance than Y
                              C) It is impossible to determine the performance difference between X and Y
                              D) X and Y have the same performance


                              4. There are the following business scenarios: the user's online log files have been stored on HDFS, and the log file content format is: each online record has three fields, namely name, gender, and online time, separated by "," between the fields; All female netizens who spend more than two hours online are required to print out.
                              Which of the following code fragments can achieve the above business scenarios? (multiple choice)

                              A) sc.textFile( " /data/file/path " .map(_.split( " , " ).map(p => Femalelnfo(p(0), p(1), p (2) .trim.tolnt)).toDF.registerTempTable("FemalelnfoTable") sqlContext.sql("select name,sum(stayTime) as stayTime from FemalelnfoTable where gender = ' Female '" ).filter( " stayTime >= 120 " ).collect().foreach(println)
                              B) val text = sc.textFile("/data/file/path") val data = text.filter(_.contains("female")) val femaleData:RDD[(String,Int)] = data.map{Iine => val t = line.split( ' , ' ) (t(0),t(2).tolnt) }.reduceByKey(_ + _) val result = femaleData.filter(line => line._2> 120) result.collect().map(x => x._1 + ' , ' + x._2).foreach(println)
                              C) sc.textFile( " /data/file/path " .map(_.split( " , " ).map(p => Femalelnfo(p(0), p(1), p (2) .trim.tolnt)).toDF.registerTempTable("FemalelnfoTable") sqlContext.sql("select name,sum(stayTime) as stayTime from FemalelnfoTable where gender = ' Female ' group by name " ).filter( " stayTime >= 120 " ).collect().foreach(println)
                              D) val text = sc.textFile("/data/file/path") val data = text.filter(_.contains("female")) val femaleData:RDD[(String,Int)] = data.map{Iine => val t = line.split( ' , ' ) (t(0),t(2).tolnt) }. val result = femaleData.filter(line => line._2> 120) result.collect().map(x => x._1 + ' , ' + x._2).foreach(println)


                              5. In FusionInsight HD, regarding Oozie's job operation commands, which of the following descriptions are correct? (multiple choice)

                              A) The submit command can change the status of the job to PREP
                              B) The kill command can be used on jobs in PREP/SUSPEND/RUNNING status
                              C) The run command can make the job status RUNNING
                              D) The start command can make the job in the PREP state become RUNNING


                              Solutions:

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

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