A Tableau Web Data Connector (WDC) to pull data from InfluxDB
Github Repository: https://github.com/tagyoureit/InfluxDB_WDC
- 1.4 - Added protocol
https+influxdb:\per Issue #4. - 1.3 - Additional error logging.
- 1.2 - Added support for special characters -
(space),,,\ and /,' and ",-and other special characters. - 1.1 - When editing a connection, the previous values will be restored (except for the password). Increased, and dismissible, alert information. Formatting of # of rows returned with ",".
- 1.0 - Initial version
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npm install influxdb_wdc OR
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Download the files and put them in a local web server.
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Open in Tableau 10.2+ and point to your URL.
This is hosted by Github Pages. To use it, open Tableau (10.2+), select "Web Data Connector" and point to this URL: https://tagyoureit.github.io/InfluxDB_WDC/InfluxDB.html
If you use authorization on your InfluxDB, you can click the link to reload the page with the username/password fields. Alternatively, add ?auth=true or ?auth=false to the end of the URL to access these directly.
- Basic Auth or no Auth
- Full or Incremental refresh
- Row count for extract creation progress
Tableau works great with time data, but time series metrics can be a challenge. The most metrics you can have on a single graph is 2 (with Dual Axis). If you want to show many metrics you'll want to create a dashboard with individual measurements.
Aggregation is a great way to be able to do a row-level join on time series data that would otherwise not be joinable. When you aggregate to any interval, Influx will "fill in" the missing values with nulls. This should enable an inner join where you can use all of your data from a single Tableau Data Source. In Tableau, use your table with earliest/latest dates and then connect to it with a left-outer join.
Aggregation can significantly decrease (or increase) the number of data points that are returned. If your DB stores 1000 measurements per second, and aggregate up to the minute you'll reduce the data by 59,999 points per minute. On the other hand, if you store 1 measurement per hour and aggregate by the milli-second you'll pull an extra 59,999 data points per minute.
If you don't aggregate the measurements, then you will likely want to create a separate Tableau Data Source for each measurement.
By default, Tableau will try to SUM all of your measurements. If you bring data back and try to display it in Tableau at a higher level aggregation (eg you collect temperature readings every 20 minutes) and graph this at an hourly measurement, you may see you steady 80 degrees appear as 240 degrees!
Currently, the admin user is needed to populate the list of databases. Once the extract is created if you want to refresh it you can enter a read (or write) only user account in Tableau.