Hi all,
We are encountering a persistent 422 Unprocessable Entity error when attempting to query aggregated data via the Data Warehouse API (/api/v2/analytics/data-warehouse/query) within our multi-tenant AppFoundry application. Specifically, the issue arises when we attempt to aggregate custom segment data using a ‘daily’ time granularity alongside specific interaction attributes that are not natively supported at that aggregation level.
The request payload includes a standard query structure with a time range spanning the last 30 days. However, when we include a custom segment ID in the groupBy clause while maintaining the ‘daily’ time unit, the API rejects the request. The error response indicates that the selected time granularity is incompatible with the requested metric aggregation for the specified segment.
We have verified that the segment ID is valid and active within the target organization. Furthermore, querying the same segment with an ‘hourly’ time granularity returns data successfully, albeit with significantly higher payload sizes and increased latency, which is not sustainable for our dashboard rendering requirements. We are trying to optimize our data retrieval strategy to support real-time reporting for our clients without overwhelming the API rate limits or our frontend processing capabilities.
Has anyone experienced similar constraints with custom segments in the Data Warehouse API? Is there a documented limitation regarding which metrics can be aggregated at the ‘daily’ level when custom segments are involved, or is this a known issue with the current API version? We are currently using the latest stable version of the Genesys Cloud Platform API as documented in the developer portal.
Any insights or workarounds would be appreciated. We are looking to ensure our integration remains robust and efficient for our enterprise clients.
This 422 Unprocessable Entity error is a classic constraint of the Genesys Cloud Data Warehouse API, specifically regarding the alignment between timeGranularity and the selected metrics or dimensions. When you select a daily granularity, the API enforces a strict schema that only allows metrics and dimensions that can be meaningfully aggregated over a 24-hour period.
Custom segment data, particularly when tied to specific interaction attributes (like interaction.id or real-time queue states), often requires a minute or second granularity to resolve correctly. If you attempt to pull these high-cardinality fields into a daily bucket, the API rejects the payload because it cannot deterministically map the atomic interaction data to the aggregated time window without losing fidelity or violating the schema definition.
To resolve this, you have two primary options. First, adjust your query payload to use a minute granularity if you need those specific interaction attributes. This will increase the row count but provide the necessary detail. Second, and more likely what you need for a multi-tenant AppFoundry app, is to strip out the unsupported interaction attributes from the daily query and instead use a pre-aggregated view or a separate, lower-frequency query for the custom segment metrics that do support daily aggregation.
Here is a corrected payload structure for a daily query that avoids the 422:
{
"query": {
"timeGroup": {
"granularity": "daily",
"startTime": "2023-10-01T00:00:00.000Z",
"endTime": "2023-10-02T00:00:00.000Z"
},
"metrics": [
{ "id": "queueHandleTime", "type": "avg" },
{ "id": "conversationCount", "type": "count" }
],
"dimensions": [
{ "id": "segmentName", "type": "string" }
]
}
}
Ensure you are not mixing interaction dimensions with daily metrics. Cross-reference the Data Warehouse API documentation under “Supported Metrics and Dimensions” to verify which fields are compatible with your chosen time granularity. This alignment is critical for avoiding 422 errors in high-volume analytics queries.