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Huawei H13-723-ENU Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Big Data Application Development Overall Guide | 15% | - Big data concepts and architecture - Application development fundamentals - Mainstream big data technologies and ecosystems - Scenario-based big data solutions overview |
| Big Data Real-time Stream Computing Scenario-based Solution | 30% | - Stream solution deployment and tuning - Flume and Kafka data ingestion - Spark Streaming and Structured Streaming - Flink stream processing framework |
| Big Data Real-time Retrieval Scenario-based Solution | 30% | - HBase architecture and development - Real-time retrieval optimization - Elasticsearch and real-time search - GaussDB(DWS) and distributed query |
| Big Data Offline Batch Processing Scenario-based Solution | 25% | - HDFS and Hive principles and usage - Spark SQL and batch processing - Data ingestion tools: Loader, Sqoop, Kettle - Offline solution design and optimization |
Huawei HCIP-Big Data Developer Sample Questions:
1. HBase filters can set column names or column values as filter conditions, and support multiple filters to be used together.
A) True
B) False
2. As the core object of Spark, which of the following characteristics does RDD have? (multiple choice)
A) Efficient
B) Read only
C) Partition
D) Fault tolerance
3. In FusionInsight HD, use the Streaming command line to submit the om.huawei.examole.WordCount task in example.jar. The task name is wcTest. Which of the following commands is correct?
A) storm jar example .jar wcTest WordCount
B) storm jar example.jar WordCount wcTest
C) storm jar example .jar wcTest om.huawei.example.WordCount
D) storm jar example .jar om.huawei.example.WordCount wcTest
4. Which of the following options is the core function of Yarn?
A) Resource management
B) Search
C) Storage
D) Data transfer
5. In Spark application development, which of the following codes can correctly count words?
A) val counts = textFile.map (line => line.split ("')).map (-rd => (word, 1)).reduceByKey(_ +_)
B) val counts = textFile.flatMap (line=>line.split (" ")).map (word => (word, 1)).reduceByKey(_ +_)
C) val counts = textFile.map (line=>line.split (" ")).map (word => (word, 1)).groupByKey ()
D) val counts = textFile.flatMap (line=>line.split (" ")).map (word => (word, 1)).groupByKey ()
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: A,B,C,D | Question # 3 Answer: D | Question # 4 Answer: A | Question # 5 Answer: B |
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