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Huawei H13-723-ENU Exam Syllabus Topics:

SectionWeightObjectives
Big Data Real-time Retrieval Scenario-based Solution30%- Apache Phoenix SQL and indexing
- GaussDB(DWS) data warehouse
- HBase design, coprocessors, optimization
- Elasticsearch, SolrCloud, CarbonData usage
Big Data Offline Batch Processing Scenario-based Solution25%- Hive development: UDF/UDAF/UDTF, ACID, optimization
- Spark development: RDD, DataFrame, Catalyst, AQE
- Data ingestion and lakehouse formats
Big Data Application Development Overall Guide15%- Security framework: Kerberos, Ranger, ZooKeeper
- HDFS advanced features and YARN scheduling
- FusionInsight HD architecture and components
- Big data architecture: Lambda and Kappa
Big Data Real-time Stream Computing Scenario-based Solution30%- Kafka integration and transactions
- Apache Flink: event time, windowing, state, checkpoint
- Flink SQL and CEP
- Spark Structured Streaming

Huawei HCIP-Big Data Developer Sample Questions:

Question #1

In FusionInsight HD, in which ways can I view the debugging results of Oozie jobs? (multiple choice)

  • A. Oozie's own web interface can also view job execution results
  • B. Use Hue's file browser to check whether the desired file is generated in the HDFS specified directory
  • C. Check whether the returned result of Oozie's JAVA API meets expectations
  • D. View program running results through Hue's workflow dashboard
Answer: A,B,C,D
Question #2

In Spark, which of the following is the operator that takes the intersection of the DataFrame?

  • A. filter (condifionExpr: String): DataFrame
  • B. dropDuplicates():DataFrame
  • C. intersect (other: Data Fra me): Data Fra me
  • D. join (right: DataFrame, join Exprs: Column): DataFrame
Answer: C
Question #3

In which of the following is the MapReduce task finally executed?

  • A. NodeManager
  • B. ResourceManager
  • C. container
  • D. AppMaster
Answer: C
Question #4

Which of the following business applications is not suitable for Hive?

  • A. Non-real-time analysis (log analysis, statistical analysis)
  • B. Real-time online data analysis
  • C. Data mining (user behavior analysis, interest division, regional display)
  • D. Data summary (number of user clicks per day/week, click ranking)
Answer: B
Question #5

In Spark, assuming that lines is a DStream object, which of the following statements can periodically count the number of words on this stream?

  • A. Iines.flatMap(_.split (" " )).map(word => (word,word.Iength())).reduceByKey (_ +_).print()
  • B. Iines.flatMap(_.split (" " )).map(word => (word, 1)).reduce(_ +_).print()
  • C. Iines.flatMap(_.split (" " )).flatMap(word => (word, 1)).groupByKey(_ +_).print()
  • D. Iines.fIatMap(_.spIit (" " )).map(word => (word, 1)).reduceByKey(_ +_).print()
Answer: D

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