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Connecting RStudio to superQuery

These instructions explain how to connect your RStudio account to superQuery’s query optimization engine.
When connected, your queries will pass through superQuery — where it will be automatically optimized — before being executed in BigQuery. 

The result: a significant reduction in query costs and execution time.


  1. Click on the Integrations link in the sidebar of superQuery:

  2. Enable your desired connection by clicking “Connect”
  3. After clicking “Connect” you’ll see the username and password screen, like so:



  1.  Whitelist your IP Address if necessary
  2.  Copy the hostname and port from this window into your service of choice.
    • server:
    • port: 3306

6.  Finalize the connection.


  • Download RStudio
  • In RStudio run the following from the console:
    • install.packages(“RMySQL”)
    • install.packages(“jsonlite”)

Connect RStudio to superQuery

  1. Open RStudio and create a new R script:
    mydb = dbConnect(MySQL(), user='xxxx', password='xxxx', dbname='yourproject.yourdataset', host='')
    rs = dbSendQuery(mydb, 'SELECT COUNT(*) FROM `yourproject.yourdataset.yourtable`;')
    data = fetch(rs, n=-1)
    rs_explain = dbSendQuery(mydb, 'explain;')
    data_explain = fetch(rs_explain, n=-1)
    data_explain = fromJSON(data_explain$statistics)
  2. Enter the following details into the script:
    1. Your username and password into the ‘xxxx’ parts
    2. yourproject, yourdataset and yourtable in the relevants parts.
  3. Run the script and you will see two variables were created:
    1. data
    2. data_explain

      The variable called “data” will contain your query results and the variable “data_explain” will contain your query’s execution plan and statistics.  It should look like this:

Boom! You’re all set.

Now you can start building your own beautiful dashboards. 
Query on! 🙂

Here are some ways you can organize boards and queries (okay, maybe not the last one 😉)

User Acquisition Board

  • CAC
  • MRR Churn
  • Gross Margin
  • LTV

Marketing Campaigns Board

  • Facebook
  • Twitter
  • LinkedIn
  • Quora
  • Pinterest
  • Instagram

Pokemon Pokedex

  • Easiest to Capture by Type
  • Strongest by Type
  • Strongest by Generation
  • # Pokemon by Type
…but really, the possibilities are endless! It depends on you, the data you’re examining, and how you mentally organize your data insights.

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