In house datasets

Getting Started

To interact with these cubes, ensure you have the following setup:

1. Cube.js Client Setup: Ensure that your frontend application is correctly set up with Cube.js and has access to the Cube.js API endpoint.

2. Data Sources: The cubes are connected to different data sources (bitcoin, stacks, stellar, dapps, pricing). Ensure that these data sources are correctly configured in your Cube.js backend.

3. Permissions: Get a JWT token from the Ortege team.

Querying the Cubes

Developers can use Cube.js's query language to fetch data from these cubes. Below are some general guidelines and best practices:

• Selecting Measures and Dimensions: Choose relevant measures and dimensions based on the insights you aim to derive.

• Filtering Data: Utilize filters to narrow down the data to specific criteria, such as date ranges, specific accounts, or asset types.

• Time Dimensions: Leverage time dimensions to analyze trends over time, such as hourly, daily, or monthly aggregations.

• Combining Cubes: Use joins and other advanced Cube.js features to combine data from multiple cubes if necessary.

Example Queries

Here are some example queries for different use cases:

1. Total Supplied STX in a Specific Cycle

   jsonCopy code{
     "measures": ["stacks_lending_zest.total_supplied"],
     "dimensions": ["stacks_lending_zest.sender_address"],
     "filters": [
       {
         "dimension": "stacks_lending_zest.cycle",
         "operator": "equals",
         "values": [10]
       }
     ],
     "timeDimensions": []
   }

2. Average Price of Assets Over the Last Week

   jsonCopy code{
     "measures": ["prices.avg_price"],
     "dimensions": ["prices.symbol"],
     "filters": [],
     "timeDimensions": [
       {
         "dimension": "prices.timedate",
         "granularity": "day",
         "dateRange": "Last 7 days"
       }
     ]
   }

3. Stellar Transactions with Average Fee

   jsonCopy code{
     "measures": ["stellar_tx.avg_fee"],
     "dimensions": ["stellar_tx.account", "stellar_tx.block_height"],
     "filters": [],
     "timeDimensions": [
       {
         "dimension": "stellar_tx.timestamp",
         "granularity": "day",
         "dateRange": "Last 30 days"
       }
     ]
   }

Best Practices

• Optimize Queries: Only request necessary measures and dimensions to optimize performance and reduce payload sizes.

• Use Aggregations Wisely: Leverage Cube.js's powerful aggregation capabilities to perform complex calculations server-side.

• Handle Time Zones: Ensure that time dimensions account for time zone differences if your data spans multiple regions.

• Monitor Performance: Regularly monitor query performance and adjust cube configurations as needed to maintain responsiveness.

Troubleshooting

If you encounter issues while querying the cubes:

• Check Cube Definitions: Ensure that the cube definitions are correctly configured and match the underlying database schemas.

• Verify Data Sources: Confirm that all data sources are operational and correctly connected to Cube.js.

• Review Filters and Parameters: Double-check the filters and parameters used in your queries to ensure they align with the cube's dimensions and measures.

• Consult Logs: Check Cube.js and backend logs for any error messages or warnings that can provide insights into the issue.

Contributing

If you plan to add new cubes or modify existing ones:

1. Update Schema Files: Ensure that any new cube definitions are added to the ConfigMap as shown in the provided configurations.

2. Test Queries: Validate new or modified cubes by running test queries to ensure they return the expected data.

3. Document Changes: Update this documentation accordingly to reflect any additions or modifications to the cubes.

Contact

For further assistance or to report issues, please contact the development team at [e-mail].