Free H13-711_V3.5 Exam, H13-711_V3.5 Valid Dump

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Huawei H13-711_V3.5 Exam Syllabus Topics:

Section	Objectives
Topic 1: Big Data Development Practice	- Typical big data application cases - Data visualization and analysis - Data loading and ETL processing - Real-time and batch data processing
Topic 2: Big Data Platform Components	- GES (Graph Engine Service) concepts and application scenarios - Spark memory computing framework - Sqoop data import/export - Flink stream computing framework - MapReduce computing framework - HBase distributed database - Kafka distributed message queue - ClickHouse columnar database - DataArt Studio data development platform - GES graph engine service - Hive data warehouse - YARN resource scheduling - Elasticsearch search engine - Hadoop ecosystem overview - HDFS distributed file system - Flume log collection
Topic 3: FusionInsight HD Overview	- Cluster management and O&M basics - MRS service component introduction - Huawei FusionInsight HD architecture and features
Topic 4: Big Data Platform Security	- Data encryption and desensitization - Platform security design - Security authentication and permission management (Kerberos, Ranger, LDAP)
Topic 5: Big Data Application Scenarios	- Industry pain points and application scenarios of big data - Big data strategy and data governance overview

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Huawei HCIA-Big Data V3.5 Sample Questions (Q66-Q71):

NEW QUESTION # 66
From the point of view of the life cycle, what are the main stages of data? (Multiple choice)

A. Data collection
B. Data Analysis
C. Data Presentation
D. Data Storage
E. Data management

Answer: A,B,D,E

NEW QUESTION # 67
When a MapReduce task fails, the task can be recalculated through the retry mechanism.

A. False
B. True

Answer: B

NEW QUESTION # 68
Which statement about HIVE is wrong?

A. Hive is built on Hadoop based on static batch processing. Hadoop usually has high latency and requires a lot of overhead when submitting and scheduling
B. Hive can realize low-latency and fast query on large-scale data sets
C. The best usage scenario of Hive is the batch processing job of large data sets
D. The Hive query operation process strictly follows the Hadoop MapReduce role execution model.Hive converts the user's HiveQL statement to the MapReduce Hadoop cluster through the interpreter.

Answer: B

NEW QUESTION # 69
Regarding the comparison between Hive and traditional data warehouses, which of the following descriptions is wrong?

A. Since Hive data is stored in HDFS, it can guarantee high fault tolerance and high reliability of data
B. Hive metadata storage is independent of data storage, thereby decoupling metadata and data, with high flexibility, while traditional data warehouses have single data applications and low flexibility
C. Since Hive is based on a big data platform, the query efficiency is faster than traditional data warehouses
D. Hive is based on HDFS storage, theoretically, the storage capacity can be expanded infinitely, while the storage capacity of traditional data warehouses will have an upper limit

Answer: C

NEW QUESTION # 70
Spark's intermediate data is placed in memory, which is more efficient and has higher latency for iterative operations and batch calculations.

A. False
B. True

Answer: A

NEW QUESTION # 71
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