This talk introduces the SQL data source for Flux. It will start with examples of using data from MySQL or Postgres with time series data from InfluxDB. It will then go over the details of how the SQL data source was created.
3. Why?
• Connect your time series data
with other types of data for
enrichment (and for fun)
• Single responsibility databases
Why?
• Connect your time series data
with other types of data for
enrichment (and for fun)
• Single responsibility databases
6. Example:
Robots
(Industrial IoT)
Each robot has:
❏ ID
❏ name
❏ model
❏ created_at (timestamp)
Example:
Robots
(Industrial IoT)
Each robot has:
❏ ID
❏ name
❏ model
❏ created_at (timestamp)
Example:
Robots
(Industrial IoT)
Each robot has:
❏ ID
❏ name
❏ model
❏ created_at (timestamp)
Example:
Robots
(Industrial IoT)
Each robot has:
❏ ID
❏ name
❏ model
❏ created_at (timestamp)
7. Example:
Robots
(Industrial IoT)
Robot jobs vary. Some measure parts, some
place parts on belts, and others rotate the
parts for inspection. But not all robots
perform the same. Some of them crash.
What is the average CPU usage of each
robot?
Example:
Robots
(Industrial IoT)
Robot jobs vary. Some measure parts, some
place parts on belts, and others rotate the
parts for inspection. But not all robots
perform the same. Some of them crash.
What is the average CPU usage of each
robot?
Example:
Robots
(Industrial IoT)
Robot jobs vary. Some measure parts, some
place parts on belts, and others rotate the
parts for inspection. But not all robots
perform the same. Some of them crash.
What is the average CPU usage of each
robot?