MemSQL Training Course

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

MemSQL is an in-memory, distributed, SQL database management system for cloud and on-premises. It's a real-time data warehouse that immediately delivers insights from live and historical data.

In this instructor-led, live training, participants will learn the essentials of MemSQL for development and administration.

By the end of this training, participants will be able to:

  • Understand the key concepts and characteristics of MemSQL
  • Install, design, maintain, and operate MemSQL
  • Optimize schemas in MemSQL
  • Improve queries in MemSQL
  • Benchmark performance in MemSQL
  • Build real-time data applications using MemSQL

Audience

  • Developers
  • Administrators
  • Operation Engineers

Format of the course

  • Part lecture, part discussion, exercises and heavy hands-on practice

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

Testimonials

★★★★★
★★★★★

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