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Huawei H13-711_V3.0 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Big Data Operations and Management | - Monitoring and maintenance concepts - Cluster deployment basics |
| Big Data Processing Frameworks | - HBase distributed database - Hive data warehouse - Spark fundamentals |
| Big Data Fundamentals | - Big data architecture overview - Concepts of Big Data and data lifecycle |
| Hadoop Ecosystem | - MapReduce and YARN basics - HDFS architecture and principles |
| Data Analysis and Applications | - Data ingestion and processing workflows - Basic analytics and querying methods |
Huawei HCIA-Big Data V3.0 Sample Questions:
1. Which of the following options are correctHBasoProcess description of reading and datastatedcorrect?
A) The client can maintain the visited regionLocation information to speed up the query
B) Clientcannot maintain visitedregionLocation information to speed up the query
C) The client needs to read the datato HMastor Involvement
D) customersNo need to read data on the sideHMaster participation
2. About HDFSThe function of the NameNode, which one of the following descriptions is wrong?
A) Store file content
B) Save the mapping relationship between file blocks and DataNodes
C) MaintenanceThe mapping relationship between Block ID and DataNode local file
D) for storing metadata
3. FlinkThe time window can be divided into the following three types of windows according to the different implementation principles?
A) Session windowwindow)
B) Tumblingwindow)
C) Counting window (Courtwindow)
D) Sliding window (Slidingwindow)
4. A user needs to build a FusionInsightHD cluster with 350 nodes. Which planning solution is the best?
A) The management node and data node are deployed together, the control node is independently deployed, and the two-layer networking
B) Management nodes, control nodes, and data nodes are independently deployed, with three-layer networking
C) Management node, control node, and data node are deployed in one, layer-2 networking
D) Integrated deployment of management nodes and control nodes, independent deployment of data nodes, and Layer 2 networking
5. In many small file scenarios, Spark will start many tasks. When there is a Shuffle operation in the SQL logic, the number of hash buckets will be greatly increased, which will seriously affect the performance. In Fusioninsight, scenarios for small files usually use the( )Operator to merge partitioni generated by small files in Tabler, reduce the number of partitions, avoid generating too many hash buckets during shuffle, and improve performance?
A) coalosce
B) onnect
C) group by
D) join
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: A,C | Question # 3 Answer: A,B,D | Question # 4 Answer: B | Question # 5 Answer: D |


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