H13-711_V3.5 Valid Exam Pattern | Latest H13-711_V3.5 Braindumps Pdf

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Huawei H13-711_V3.5 Exam Syllabus Topics:

SectionWeightObjectives
Big Data Industry Overview & Basic Concepts8%- Application scenarios and value of big data
- Huawei Kunpeng big data ecosystem
- Development trend and characteristics of big data
MapReduce & YARN12%- YARN architecture, resource scheduling and management
- MapReduce programming model and execution process
HBase & Hive20%- HBase architecture, data model, design and operation
- Hive data warehouse principle, table design, SQL and optimization
Flume & Kafka12%- Kafka message system, storage, transmission and application
- Flume data collection mechanism and configuration
ClickHouse & Elasticsearch8%- ClickHouse architecture, storage and query features
- Elasticsearch search engine, indexing and analysis
Huawei Big Data Platform MRS & DataArts Studio8%- DataArts Studio data development and governance
- MRS platform architecture, components and operation
- Typical industry solutions and cases
Spark & Flink20%- Flink stream processing, architecture, API and application development
- Spark core architecture, RDD, DataFrame, SQL and streaming processing
HDFS & ZooKeeper12%- ZooKeeper core functions and working mechanism
- HDFS architecture, principle and operation

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Huawei HCIA-Big Data V3.5 Sample Questions (Q494-Q499):

NEW QUESTION # 494
Kafka is a distributed message publishing and subscription system. It only forwards messages and does not save messages.

Answer: B


NEW QUESTION # 495
The Streaming of Fusioninsight HD is developed based on the open source Apache Storm, which is a distributed offline computing framework.

Answer: B


NEW QUESTION # 496
How can HBase and Hive be integrated for big data solutions? (Choose two)

Answer: A,D


NEW QUESTION # 497
Among the following options, which one is correct about the meaning of Zookeeper reliability?

Answer: B


NEW QUESTION # 498
Synchronize data between partition replication in Kafka. Copying data from the leader of the partition to the follower requires a thread (replicationFetcherThread), and the follower (a follower is equivalent to a consumer) actively pulls messages from the leader in batches, which greatly improves the throughput.

Answer: B


NEW QUESTION # 499
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