Cube Playground

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Accessing Cube Playground

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Prerequisites

1. Select a project - Choose an active Cube project
2. Select a branch - Choose a branch to work with

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Cube Playground interface

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Main components

• Visual drag-and-drop interface for building queries
• Select measures and dimensions from available cubes
• Apply filters and configure aggregations
• Preview query results

• Direct SQL query execution
• Syntax highlighting and autocomplete
• Query history and saved queries
• Execute and test queries

• Browse available cubes, measures, and dimensions
• View cube definitions and metadata
• Understand data structure and relationships
• Navigate hierarchical cube organization

• Display query results in tables or charts
• Export results to various formats
• Analyze data patterns and insights

• Edit cube definitions using YAML or JavaScript
• Version-controlled schema files
• Deploy and test schema changes

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Building queries

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Visual query builder

1. Select cube
   • Choose a cube from the sidebar
   • View available measures and dimensions
2. Choose measures
   • Select quantitative metrics to calculate
   • Examples: revenue, orders, users, conversions
   • Can select multiple measures
3. Add dimensions
   • Select attributes for grouping and analysis
   • Examples: date, region, product category
   • Can add multiple dimensions
4. Apply filters
   • Filter data by specific values or ranges
   • Date range filters
   • Categorical filters
   • Numeric filters
5. Configure aggregations
   • Set time granularity (day, week, month, etc.)
   • Configure sorting and ordering
   • Set result limits
6. Execute query
   • Click “Run” to execute the query
   • View results in the results panel
   • Export or save query if needed

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SQL editor

1. Open SQL editor
   • Switch to SQL editor tab
   • Write SQL queries using Cube.js SQL syntax
2. Query syntax
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   Ask AI

   SELECT 
     orders.status,
     orders.total_revenue
   FROM orders
   WHERE orders.created_at >= '2024-01-01'
   GROUP BY orders.status
   ORDER BY orders.total_revenue DESC
   

3. Execute and test
   • Click “Run” to execute
   • Review results and query performance
   • Iterate and refine queries
4. Save queries
   • Save frequently used queries
   • Share queries with team members
   • Build query library

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Defining cubes

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Cube schema structure

cubes:
  - name: orders
    sql_table: orders
    measures:
      - name: count
        type: count
      - name: total_revenue
        sql: sum(amount)
        type: sum
      - name: average_order_value
        sql: sum(amount) / count(*)
        type: number
    dimensions:
      - name: status
        sql: status
        type: string
      - name: created_at
        sql: created_at
        type: time
      - name: customer_id
        sql: customer_id
        type: string
        primary_key: true

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Schema components

• Quantitative metrics and calculations
• Types: count, sum, avg, min, max, number
• Custom SQL expressions
• Aggregation functions

• Attributes for analysis and grouping
• Types: string, number, time, boolean
• Primary keys for joins
• Hierarchical relationships

• Special dimensions for time-based analysis
• Support for time grains (day, week, month, etc.)
• Built-in time intelligence functions
• Period-over-period comparisons

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Editing schemas

1. Access schema files
   • Navigate to schema files in Cube Playground
   • Edit YAML or JavaScript files directly
2. Make changes
   • Add new cubes, measures, or dimensions
   • Modify existing definitions
   • Update SQL expressions
3. Save and deploy
   • Save schema changes
   • Deploy to make changes available
   • Changes take effect immediately
4. Test changes
   • Test queries in Playground
   • Verify results are correct
   • Iterate and refine

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Exploring data

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Schema explorer

1. View cubes
   • See all available cubes in sidebar
   • Navigate cube hierarchy
   • Understand cube relationships
2. Explore measures
   • View available measures per cube
   • Understand measure definitions
   • See measure types and calculations
3. Explore dimensions
   • View available dimensions per cube
   • Understand dimension types
   • See dimension relationships

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Data preview

1. Sample data
   • View sample data from cubes
   • Understand data structure
   • Verify data quality
2. Query results
   • Execute queries and view results
   • Analyze data patterns
   • Export results for further analysis

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Best practices

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Query building

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Schema development

• Version control - Commit schema changes regularly with descriptive messages
• Incremental changes - Make small, testable changes rather than large refactors
• Documentation - Add descriptions and examples to cube definitions
• Testing - Test schema changes thoroughly before deploying
• Review - Use pull requests for schema changes in protected branches

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Performance optimization

• Efficient measures - Use appropriate aggregation types
• Indexed dimensions - Ensure frequently used dimensions are indexed
• Query optimization - Review query performance and optimize slow queries
• Data filtering - Apply filters to reduce data volume
• Caching - Leverage Cube.js caching for frequently accessed data

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Troubleshooting

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Common issues