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Huawei H13-723-ENU Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Big Data Real-time Stream Computing Scenario-based Solution | 30% | - Apache Flink: event time, windowing, state, checkpoint - Spark Structured Streaming - Flink SQL and CEP - Kafka integration and transactions |
| Big Data Application Development Overall Guide | 15% | - HDFS advanced features and YARN scheduling - Big data architecture: Lambda and Kappa - Security framework: Kerberos, Ranger, ZooKeeper - FusionInsight HD architecture and components |
| Big Data Offline Batch Processing Scenario-based Solution | 25% | - Hive development: UDF/UDAF/UDTF, ACID, optimization - Data ingestion and lakehouse formats - Spark development: RDD, DataFrame, Catalyst, AQE |
| Big Data Real-time Retrieval Scenario-based Solution | 30% | - Elasticsearch, SolrCloud, CarbonData usage - Apache Phoenix SQL and indexing - HBase design, coprocessors, optimization - GaussDB(DWS) data warehouse |
Huawei HCIP-Big Data Developer Sample Questions:
Question 1
Which of the following options is the core function of Yarn?
A. Search
B. Storage
C. Resource management
D. Data transfer
Question 2
When indexing in Solr, which of the following code snippets can significantly improve indexing performance? (multiple choice)
A. lbClient.setRequestWriter (new BinaryRequestWriter());
B. SolrlnputDocument doc = new SolrlnputDocument(); doc.addField ("id", i.toString()); doc.addField ("name", "Zhang San" + i); doc.addField ("features", "test" + ); doc.addField ("price", (float) i * 1.01); cloudSolrClient.add (doc); cloudSolrClient.commit();
C. if (updateRequest.getDocuments().size() >= 1000) { cloudSolrClient.request (updateRequest, collName); updateRequest.clear(); }
D. if (updateRequest.getDocumentsMap().size() >= 10000) { cloudSolrClient.request (updateRequest, collName); updateRequest.clear(); }
Question 3
Regarding the flow of data in Flume, which of the following descriptions is correct?
A. (1) Data from sink to channle; (2) Source gets data from channel
B. (1) Data from channle to source; (2) Sink gets data from source
C. (1) Data from source to channel; (2) Sink gets data from channel
D. (1) Data from channle to source; (2) Sink gets data from source
Question 4
Which of the following table types does Hive support? (multiple choice)
A. Partition table
B. Tilt table
C. Bucket table
D. Partition + bucket table
Question 5
In FusionInsight HD, regarding the partition function of Hive, what is wrong in the following description?
A. Using partitions can reduce the data scan range of certain queries, thereby improving query efficiency
B. There can only be one partition field, and multi-level partitions cannot be created
C. The partition field should be defined when the table is created
D. The partition field can be used as the condition of the where clause
Solutions:
| Question 1 Answer: C | Question 2 Answer: A,D | Question 3 Answer: C | Question 4 Answer: A,B,C,D | Question 5 Answer: B |






