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Infosyte | HCIA-Big Data

HCIA-Big Data

RM5,500.00

Course Duration: 5 Days

Description

COURSE OBJECTIVE

After completing the training, you will be able to: 

  • Master 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 capable of using Huawei big data platform MRS
  • Operate and develop services based on Huawei MRS
  • Competent for positions related to big data development engineers
  • Have the knowledge and skills required for big data pre-sales, big data project management, and big data development

PREREQUISITES

  • Has basic knowledge of network technology
  • Be familiar with basic operations on Linux operating systems.

AUDIENCE

  • Those who desire to become big data engineers
  • Those who desire to obtain the HCIA-Big Data certification
  • Junior big data engineers

 

MORE INFO

COURSE OUTLINE

COURSE OUTLINE

1. 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
2. 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
3. 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
4. ClickHouse — Online Analytical Processing Database Management System
  • ClickHouse Overview
  • ClickHouse Architecture and Basic Features
  • Enhanced Features of ClickHouse
5. 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
6. 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
7. 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
8. Elasticsearch — Distributed Search Engine
  • Overview
  • System Architecture
  • Key Features
9. MRS Huawei’s Big Data Platform
  • Overview of MRS
  • MRS Components
  • MRS Cloud-Native Data Lake Baseline Solution
10. Huawei DataArts Studio
  • Data Governance
  • Huawei DataArts Studio

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