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Huawei H13-723 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Big Data Application Development Overall Guide | 15% | - Big data scenario-based solutions - Application development fundamentals - Big data concepts and architecture |
| Topic 2: Big Data Real-time Stream Computing Scenario-based Solution | 30% | - Real-time stream processing frameworks (Flume, Kafka, Spark Streaming, Flink) - Stream data ingestion and processing - Streaming use cases and configuration |
| Topic 3: Big Data Offline Batch Processing Scenario-based Solution | 25% | - Spark SQL and data ingestion tools (Loader, Sqoop, Kettle) - Offline batch processing solutions - HDFS and Hive fundamentals |
| Topic 4: Big Data Real-time Retrieval Scenario-based Solution | 30% | - Real-time query optimization - Real-time retrieval solution components - Distributed database concepts (HBase, Elasticsearch, GES) |
Huawei HCIP-Big Data Developer V1.0 Sample Questions:
The calculation logic of the Spark application will be parsed into DNG. Which of the following functional modules will complete this parsing operation?
- A. Application Master
- B. Driver
- C. Executor
- D. Client
For HBase column family, which of the following attributes can be set? (multiple choice)
- A. Compression
- B. Versions
- C. TTL
- D. Coprocessor
Suppose there is an application that needs to frequently access the user table in the Oracle database. In order to improve performance, Redis is introduced to cache user information.
For this scenario, which of the following is the best data structure choice for Redis?
- A. list
- B. set
- C. hash
- D. sorted set
Which distributed computing frameworks can the Hive component of FusionInsigt HD run on? (multiple choice)
- A. Spark
- B. Streaming
- C. MapReduoe
- D. HDFS
In HBase application development, when the Rowkey range and distribution of a table are known, it is recommended to pre-divide regions. After calling the following code (fragment) to pre-divide a table into regions, this table will create several regions.
//Create a table of pre-partitioned regions
byte[][] splits=new byte[4][];
splits[0] = Bytes.toBytes("A");
splits[1] = Bytes.toBytes("H");
splits[2] = Bytes.toBytes("O");
splits[3] = Bytes.toBytes("U");
admin.createTable (htd, splits);
- A. 5
- B. 3
- C. 6
- D. 4
Quincy 
Elma 
Ira 
Moses 
Jenny 
Willie 
Murray 
Daniel 
Dick 
Pandora 
Pamela 
Simon 
Dean 
Kent 
Gladys 
Nicholas 
Wanda 
Lester 
