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MongoDB SoCal 2020: Best Practices for Working with IoT and Time-series Data
@
#MDBlocal
Best practices:
Working with IoT and Time-Series
Data
Robert Walters, Director of IoT, MongoDB
@RobsCranium
SOCAL
LinkedIn: https://www.linkedin.com/in/robwaltersprofile/
#MDBLocal
#MDBLocal
Agenda
Define time-series data
Review typical IoT Architecture
Designing time-series schemas
Query and visualize time-series data
#MDBLocal
What is time series data?
Data in an IoT Architecture
#MDBLocal
https://tinyurl.com/Mongodb-Houston-2019
https://www.mongodb.com/white-papers
#MDBLocal
Common IoT Architecture
#MDBLocal
Common IoT Architecture
#MDBLocal
Common IoT Architecture
#MDBLocal
Common IoT Architecture
#MDBLocal
Common IoT Architecture
#MDBLocal
Common IoT Architecture
#MDBLocal
MongoDB IoT Reference Architecture
#MDBLocal
Data at the edge
Designing time-series schemas
#MDBLocal
Breaking the relational mindset….
#MDBLocal
MongoDB Schema Design
for Time Series data
#MDBLocal
Effects on Document count
Per second vs Per Minute
#MDBLocal
Effects on data storage
Per second vs Per Minute
#MDBLocal
Effects on memory
Per second vs Per Minute
#MDBLocal
Sample code to add to the size based bucketMongoDB Schema Design
for Time Series data
#MDBLocal
Case Study:
https://www.ampcontrolgroup.com/
Leaders in industrial electrical and electronic
engineering
Selected MongoDB for Gas-Detection Mining Application
#MDBLocal
Case Study:
#MDBLocal
Case Study:
One Document per Device per Parameter per Hour
Pre-aggregated data updated for every update
After 3 months samples array removed
Data archived for 7 years
#MDBLocal
Keys to successful time series applications
Know your application requirements
Writes Reads Data Retention Security
#MDBLocal
What to do with old data
• Pre-aggregation
• Offline archival
• db.remove
• TTL Indexes
• Dropping the collection
• Online archival
• Queryable backups
• Sharding archival data
• Offload to data warehouse / S3
#MDBLocal
MongoDB Atlas Data Lake
Analyze data in any format on S3 using MongoDB Query Language
Archive IoT and Time-series data for long term storage and analysis
How to query and visualize
time-series data
#MDBLocal
Real-time Analytics
One database for operational and analytical
data
Easy to query unstructured data
MongoDB Query Language (MQL)
Aggregation Framework
#MDBLocal
Real-time Analytics
Easily query unstructured data with Aggregation Framework
#MDBLocal
Using MQL Demo
What is the largest value for a given sensor id?
db.SensorData.aggregate( [
{$match: { "sensorid":3003 }},
{$unwind: { path: '$samples' }},
{$group: { _id: '$day', MaxValue: { $max:
'$samples.val' } }},
{$sort: { "id": 1 }} ])
What is the largest value for a given sensor id?
db.SensorData.aggregate( [
{$match: { "sensorid":3003 }},
{$unwind: { path: '$samples' }},
{$group: { _id: '$day', MaxValue: { $max:
'$samples.val' } }},
{$sort: { "id": 1 }} ])
What is the largest value for a given sensor id?
db.SensorData.aggregate( [
{$match: { "sensorid":3003 }},
{$unwind: { path: '$samples' }},
{$group: { _id: '$day', MaxValue: { $max:
'$samples.val' } }},
{$sort: { "id": 1 }} ])
What is the largest value for a given sensor id?
db.SensorData.aggregate( [
{$match: { "sensorid":3003 }},
{$unwind: { path: '$samples' }},
{$group: { _id: '$day', MaxValue: { $max:
'$samples.val' } }},
{$sort: { "id": 1 }} ])
Cloud – Real-time Analytics
What is the largest value for a given sensor id?
db.SensorData.aggregate( [
{$match: { "sensorid":3003 }},
{$unwind: { path: '$samples' }},
{$group: { id: '$day', MaxValue: { $max:
'$samples.val' } }},
{$sort: { "id": 1 }} ])
{ "_id" : ISODate("2018-12-10T00:00:00Z"), "MaxValue" : 40.4 }
{ "_id" : ISODate("2018-12-11T00:00:00Z"), "MaxValue" : 40.43 }
{ "_id" : ISODate("2018-12-12T00:00:00Z"), "MaxValue" : 40.09 }
{ "_id" : ISODate("2018-12-13T00:00:00Z"), "MaxValue" : 39.7 }
…
#MDBLocal
Cloud – Visualization
MongoDB Charts
#MDBLocal
Cloud – Visualization
MongoDB BI Connector
#MDBLocal
Integration with
Why MongoDB for IoT and Time-
Series Data?
#MDBLocal
Why MongoDB for IoT Data?
#MDBLocal
Best practices summary
Know your requirements
1 sensor reading per document works but not the most efficient
Data retention policy
Data access requirements
For very large data consider multiple collections
Faster to archive/drop collections than db.remove()
Recommended design fixed-based schema
https://www.mongodb.com/collateral/time-series-best-practices
Archive data to S3 / Atlas Data Lake for long term storage and analysis
#MDBLocal
Resources
MongoDB IoT Reference Architecture
Time Series Data and MongoDB: Best Practices Guide
Get Started with your project in MongoDB Atlas.
Use code “IOT200” for $200 in credit!
Questions about your IoT Solution?
Robert.Walters@MongoDB.COM
MongoDB SoCal 2020: Best Practices for Working with IoT and Time-series Data
THANK YOU
MongoDB SoCal 2020: Best Practices for Working with IoT and Time-series Data

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