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MicrosoftHCIA-Big Data V3.5 H13-711_V3.5 Dumps
by Victoria Meisel - HCIA-Big Data V3.5 Certification (H13-711_V3.5) is the latest exam code introduced by Huawei to replace the retired version 3.0 on June 16, 2023. Passcert has recently released the latest HCIA-Big Data V3.5 H13-711_V3.5 Dumps to help candidates prepare for the exam successfully. These HCIA-Big Data V3.5 H13-711_V3.5 Dumps cover all the topics and concepts that are necessary to pass the exam, and are updated regularly to ensure that they are in line with the latest exam objectives. With the help of these HCIA-Big Data V3.5 H13-711_V3.5 Dumps, candidates can ensure that they are well-prepared for the exam and can confidently answer all the questions that are asked.
HCIA-Big Data Certification
H13-711_V3.5 is the new exam code for HCIA-Big Data Certification. The previous version, 3.0, has been retired as of June 16, 2023. Holding the HCIA-Big Data Certification demonstrates that you have mastered the technical principles and architectures of common and important big data components, including HDFS, HBase, Hive, ClickHouse, MapReduce, YARN, Spark, Flink, Flume, Kafka, ElasticSearch, and ZooKeeper, and are capable of using Huawei's big data platform MRS. You are also able to operate and develop services based on Huawei MRS, and are competent for positions related to big data development engineers.
Target audience for this certification includes those who desire to become big data engineers, those who wish to obtain the HCIA-Big Data certification, and junior big data engineers. Prerequisites for this certification include basic knowledge of network technology and familiarity with basic operations on Linux operating systems.
HCIA-Big Data V3.5 Exam Overview
HCIA-Big Data V3.5 Exam Content
The HCIA-Big Data V3.5 exam covers:
1. Development trend of the big data industry, big data features, and Huawei Kunpeng big data;
2. Basic technical principles of common and important big data components (including HDFS, HBase, Hive, ClickHouse, MapReduce, YARN, Spark, Flink, Flume, Kafka, ElasticSearch, ZooKeeper);
3. MRS Huawei's Big Data Platform, Huawei DataArts Studio, and success stories in the big data industry.
HCIA-Big Data V3.5 Exam Knowledge Point Percentage
Big Data Development Trends and the Kunpeng Big Data Solution
Big Data Era
Big Data Application Fields
Challenges and Opportunities Faced by Enterprises
Huawei Kunpeng Solution
HDFS — Hadoop Distributed File System & ZooKeeper
HDFS
HDFS Overview
HDFS-related Concepts
HDFS Architecture
HDFS Key Features
HDFS Data Read/Write Process
ZooKeeper Distributed Coordination Service
ZooKeeper Overview
ZooKeeper Architecture
HBase — Distributed Database & Hive — Distributed Data Warehouse
HBase — Distributed Database
HBase Overview and Data Models
HBase Architecture
HBase Performance Tuning
Common Shell Commands of HBase
Hive — Distributed Data Warehouse
Hive Overview
Hive Functions and Architecture
Basic Hive Operations
ClickHouse — Online Analytical Processing Database Management System
ClickHouse Overview
ClickHouse Architecture and Basic Features
Enhanced Features of ClickHouse
MapReduce and YARN Technical Principles
MapReduce and YARN Overview
Functions and Architectures of MapReduce and YARN
Resource Management and Task Scheduling in YARN
Enhanced Features of YARN
Spark — In-memory Distributed Computing Engine & Flink — Stream and Batch Processing in a Single Engine
Spark — In-memory Distributed Computing Engine
Spark Overview
Spark Data Structure
Spark Principles and Architecture
Flink — Stream and Batch Processing in a Single Engine
Flink Principles and Architecture
Flink Time and Window
Flink Watermark
Flink Fault Tolerance Mechanism
Flume's Massive Log Aggregation & Kafka's Distributed Messaging System
Flume: Massive Log Aggregation
Overview and Architecture
Key Features
Applications
Kafka: Distributed Messaging System
Overview
Architecture and Functions
Data Management
Elasticsearch — Distributed Search Engine
Overview
System Architecture
Key Features
MRS Huawei's Big Data Platform
Overview of MRS
MRS Components
MRS Cloud-Native Data Lake Baseline Solution
Huawei DataArts Studio
Data Governance
Huawei DataArts Studio
Share HCIA-Big Data V3.5 H13-711_V3.5 Free Dumps
1. Which of the following HDFS commands can be used to check the integrity of data blocks?
A. HDFS fsck /
B. HDFS fsck -delete
C. HDFS dfsadmin -report
D. HDFS balancer -threshold 1
Answer: A
2. Where is the Meta Region routing information of HBase metadata stored in?
A. Root table
B. Zookeeper
C. HMaster
D. Meta table
Answer: B
3. What is the purpose of the HBase cluster to perform compaction regularly? (Multiple choice)
A. Reduce the number of files in the same Region and ColumnFamily
B. Improve data reading performance
C. Reduce the file data of the same ColumnFamily
D. Reduce the number of files in the same Region
Answer: ABD
4. Which of the following descriptions of Hive features are incorrect?
A. Flexible and convenient ETL
B. Only supports MapReduce computing engine
C. Can directly access HDFS files and HBase
D. Easy to use and easy to program
Answer: B
5. Which of the following functions can Spark provide? (Multiple choice)
A. Distributed memory computing engine
B. Distributed File System
C. Unified scheduling of cluster resources
D. Stream processing function
Answer: AD
6. Which of the following descriptions of Flink key features are wrong?
A. Compared with Flink, SparkStreaming has lower latency
B. The Flink streaming engine can provide functions that support stream processing and batch
processing applications at the same time
C. Compared with Streaming in Fusionlnght HD, Flink has higher throughput
D. checkpoint realizes Flink's fault tolerance
Answer: A