MemSQL 교육 과정

  1. 빅 데이터 Training
  2. Data warehouse Training
  3. MemSQL 교육 과정

Course Code

memsql

Duration

28 hours (usually 4 days including breaks)

Requirements

  • Experience with Linux, relational database systems, and SQL platforms
  • Experience with Scala, Java, or Python programming

Overview

Mem SQL 은 클라우드 및 온 - 프레미스 (in-premises)를위한 메모리 내 분산 SQL 데이터베이스 관리 시스템입니다. 라이브 및 히스토리 데이터로부터 즉시 통찰력을 제공하는 실시간 데이터웨어 하우스입니다.

이 강사가 진행하는 실제 교육에서 참가자는 개발 및 관리를 위해 Mem SQL 의 핵심 사항을 학습합니다.

이 훈련이 끝나면 참가자는 다음을 할 수 있습니다.

  • Mem SQL 의 주요 개념 및 특징 이해
  • Mem SQL 설치, 설계, 유지 보수 및 작동
  • Mem SQL 에서 스키마 최적화
  • Mem SQL 에서 쿼리 개선
  • Mem SQL 벤치 마크 성능
  • Mem SQL 사용하여 실시간 데이터 애플리케이션 구축

청중

  • 개발자
  • 관리자
  • 운영 엔지니어

과정 형식

  • 파트 강의, 파트 토론, 연습 및 무거운 실무 연습

Machine Translated

Course Outline

Introduction

Overview of MemSQL

Understanding the MemSQL Architecture

Quick Start with MemSQL Using MemSQL Ops

Understanding Essential MemSQL Concepts

  • Overview of MemSQL Commands
  • Working with Rowstore and Columnstore
  • Implementing Data Distribution
  • Using Shard Keys
  • Implementing Distributed Joins
  • Using Reference Tables
  • Understanding Application Cluster Topologies

Installing and Upgrading MemSQL

  • Designing a Cluster
  • Doing Manual Installation
  • Expanding a Cluster
  • Implementing an Upgrade
  • Securing MemSQL

Working with Schema Design and Query Optimization

  • Working with Transactions
  • Working with Geospatial Data
  • Understanding Index Types
  • Using Sparsity and Normalized Forms
  • Hands-on: Using a Reference Table to Query JSON with Variant Array Lengths
  • Working with Shard Key Strategies
  • Identifying a Sharding Strategy
  • Understanding Analyze, Explain, and Profile
  • Implementing Schema Optimization for Query Performance
  • Using Query Hints

Diving Deep into Administering MemSQL Operations

  • Using the MemSQL Ops Command Line Interface
  • Administering a Cluster
  • Understanding Administrator Key Concepts
  • Backing Up and Restoring Data
  • Scaling Cluster Size
  • Dealing with Cluster Failures
  • Managing High Availability
  • Monitoring MemSQL
  • Working with the Trace Log
  • Using Durability and Recovery
  • Running Diagnostics

Working with MemSQL Procedural SQL (MPSQL)

  • Using Table-Valued Functions
  • Using User-Defined Functions
  • Using User-Defined Aggregate Functions
  • Using Stored Procedures

Implementing Performance Benchmarking and Fine-Tuning

  • Using Experimental Metrics
  • Performance Testing with dbbench
  • Hands-on: Working with a Database Workload Generator
  • Using Management Views
  • Implementing Workload Profiling
  • Hands-on: MemSQL Top

Working with MemSQL Pipelines and Real-Time Data Ingestion

  • Using the MemSQL Connector for Apache Spark
  • Using MemSQL Pipelines with Apache Kafka and AWS S3

Creating Real-Time Applications

  • Working with Business Intelligence Dashboards
  • Using MemSQL Pipelines for Machine Learning
  • Implementing a Real-Time Dashboard
  • Implementing Predictive Analytics

Troubleshooting MemSQL

Summary and Conclusion

회원 평가

★★★★★
★★★★★

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