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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 - Hive development, optimization and ACID transactions - Data ingestion tools: Loader, Sqoop, Flume - Spark Core, Spark SQL and Catalyst optimization |
| Topic 2: Big Data Real-time Stream Computing Scenario-based Solution | 30% | - Kafka architecture, transactions and configuration - Flink SQL and complex event processing - Spark Structured Streaming fundamentals - Apache Flink: event time, watermark, windowing and state management |
| Topic 3: Big Data Real-time Retrieval Scenario-based Solution | 30% | - Elasticsearch indexing, query and cluster management - CarbonData and GaussDB(DWS) basics - Apache Phoenix and secondary indexes - HBase architecture, row-key design and optimization |
| Topic 4: Big Data Application Development Overall Guide | 15% | - Scenario-based solution design overview - Mainstream big data technologies and ecosystem - FusionInsight HD architecture and components - Application development process and specifications |
Huawei HCIP-Big Data Developer V2.0 Sample Questions:
Question 1
Rcboft0system, abouteWhich of the provided file formats is not in column format?
A. RCFileRow-column storage
B. ORC(High-performance column store)
C. TextFile
D. Parquetcolumn store
Question 2
Hadoopenabled in the platformYARNWhich parameter needs to be configured for the log aggregation function of the component?
A. yarn.nodemanager.log-dirs
B. yarn.acl.enable
C. yarn.log-aggregation-enable
D. yarn.nodemanager.local-dirs
Question 3
existSpark, which of the following statements about broadcast variables is correct?
A. Broadcast variables are read-only
B. broadcast variable in eachExecutorsave a copy
C. broadcast variable in everyTasksave a copy
D. broadcast variable viaSparkContext.broadcast() method to generate
Question 4
FusionInsight HDmiddle,HiveWhich of the following parameters of the client is used to controlreduceConcurrency? (multiple choice)
A. hive.exec-ducers.max
B. hive.exec.max.dynamic.partitions
C. hive.exec.max.dynamic.partitions.pernode
D. hive.exec.reducers.bytes.per.reducer
Question 5
Fusionlnsigt HDofHiveWhat distributed computing frameworks can components run on? (multiple choice)
A. Spark
B. HDFS
C. Streaming
D. MapReduce
Solutions:
| Question 1 Answer: C | Question 2 Answer: C | Question 3 Answer: A,B,D | Question 4 Answer: A,D | Question 5 Answer: A,D |
