The Visual Query Profilerand

MongoDB Compass

Ronán BohanSolutions Architect at MongoDB

ronan@mongodb.com

April 2016

Agenda

• Introduction

• Live Demo

• Q&A

Introduction – Part 1

What’s in our Database?

Documents are Rich Data Structures{ first_name: ‘Paul’, surname: ‘Miller’, age: 35, city: ‘London’, location: [45.123, 47.232],

profession: [‘banking’, ‘finance’, ‘trader’], cars: [ { model: ‘Bentley’, year: 1973, value: 100000, … }, { model: ‘Rolls Royce’, year: 1965, value: 330000, … } ]}

Fields can contain an array of sub-documents

Fields

Typed field values

Fields can contain arrays

String

Number

Geo-Coordinates

MongoDB

• Documents are stored in Collections

• Collections are grouped into Databases

• MongoDB has a Flexible Schema,i.e. document structure is not enforced

MongoDB

• So how do we know what we have in our database?

Mongo Shell

Mongo Shell

MongoDB Compass

Introduction – Part 2

So now we know what’s in our Database,how can we measure performance

and visualize the results?

Performance

• Performance is measured by using a Database Profiler

• MongoDB contains a built in profiler

Profiler

• Stores information about operations

• Information is stored in the system.profile collection (in the local database)

• Three options:off, log slow operations, log all operations

What’s stored?

• Each profile document contains–The operation type–The operation parameters–The namespace–The execution time–The client address–Various other details and metrics

Profiler

• So how do we see this profile data?

Mongo Shell

What about…

• Using Compass?

Visual Query Profiler

Demo time!

Where do I get these tools?

• Compass is available for evaluation purposes: https://www.mongodb.com/products/compass

• Visual Query Profiler is available via Cloud Manager Premium

• Both products are included with MongoDB Professional or MongoDB Enterprise Advanced

Q & A

Thank You!

Ronán BohanSolutions Architect at MongoDB

ronan@mongodb.com