Debefy/data-dancer-samples

Data Dancer - Samples

Data Dancer - Big Query in Visual Studio Code

Execute, analyze and model Big Query SQL within Visual Studio Code.

Features

Environment aware

• Switch effortlessly between your datasets or environments
• Colorize your environments

Variables

• Simple and powerful variable handling
• Substitute datasets, variables or settings depending on environment
• Variable highlighting

Execute Sql

• Run selected text or the full .sql file.
• Output to Data Dancer result window inside Visual Studio Code
• Investigate results without leaving Visual Studio Code
• Shows actual billed cost

Analyze Sql

• Dry-run: Get cost estimation from Big Query before running it

Copy Sql

• Copies the selected sql into clipboard. Substituting variables on the fly

Data Analysis

• Quick data type insights
• Investigate returning schema
• Investigate returning raw json

Other features

Type formatting

Clipboard Integration

• Copy data from Data Dancer's result window on mouse click
• Quickly paste your tabular result to excel

Requirements

You need a Google Cloud Big Query Account

Getting started

Create environment file

Create your environment json file. Create variables for your environment. Usually one for each dataset.

Sample dev.json

{
	"settings":
	{
		"project-id":"your-gcp-project",
		"location":"europe-north1",
		"color":"rgba(102, 153, 53, 0.5)" 
	},
	"variables":
	{
		"@@bronze":"dev_bronze",
		"@@silver":"dev_silver",
		"@@gold": "dev_gold",
        "var-raw-data-import-cutoff-months": "24"
	}
}

Sample dev_john.json Notice the inheritance. Where John changed gui color and dataset names.

{
    "inherits" : "dev.json",
	"settings":
	{
		"color":"rgba(100, 100, 100, 0.5)" 
	},
	"variables":
	{
		"@@bronze":"john_dev_bronze",
		"@@silver":"john_dev_silver",
		"@@gold":"jon_dev_gold"
	}
}

Switch between environments

Right click your .json file and choose "Use as Environment file" or click Data Dancer heart icon at bottom right of Visual Studio Code

Known Issues

• No hard-coded limit for returning result. May cause issues if you select large amounts of rows