Hi all,
i have problem with /api/v2/analytics/knowledge/aggregates/query for my dashboard. When i run query for knowledge articles, the total view count is not match with what i see in admin ui. It’s very strange because i use same interval. For small data it’s ok, but for big date range it’s missing some counts.
i try to use async job /api/v2/analytics/knowledge/aggregates/jobs to avoid timeout but result is still same. i think maybe is edge case when article is deleted? i use this body:
{
"interval": "2023-10-01T00:00:00Z/2023-10-31T23:59:59Z",
"groupBy": ["articleId"],
"metrics": ["nViews"]
}
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This sounds like a pagination issue. When we moved our knowledge base over from Zendesk, we noticed that the standard query endpoint often times out or drops data if the volume is too high. In Zendesk, the API usually just handles the heavy lifting in the background, but in Genesys Cloud, you’ve got to be more explicit. If the synchronous /api/v2/analytics/knowledge/aggregates/query isn’t returning everything, it’s likely because the result set is too large for a single response.
The workaround is to switch entirely to the async flow. You’ll want to POST to /api/v2/analytics/knowledge/aggregates/jobs first, then poll /api/v2/analytics/knowledge/aggregates/jobs/{jobId} until the status is completed. Once it’s done, use the /api/v2/analytics/knowledge/aggregates/jobs/{jobId}/results endpoint. You’ve got to loop through the cursor to get every single page of data, otherwise you’ll keep seeing those missing counts. There’s an older community post about similar gaps in conversation aggregates that confirms this pattern is the way to go.
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POST /api/v2/analytics/knowledge/aggregates/jobs
{
"interval": "2023-10-01T00:00:00Z/2023-10-31T23:59:59Z",
"metrics": ["vViewCount"]
}
The sync query is trash for larger datasets and just drops counts. Use the async job endpoint and loop through the results with the cursor, otherwise the UX for your reporting is going to be a mess.
results = api.analytics_knowledge_api.get_analytics_knowledge_aggregates_jobs_results(job_id, cursor=cursor)
genesyscloud-python requires an explicit loop to handle the cursor value returned in the results payload. We’ve encountered similar data gaps in Power BI reports when the integration failed to poll the results endpoint until the cursor was null. This is the fastest way to ensure the full dataset is captured.
The data discrepancy likely stems from the synchronous nature of the query endpoint. For larger datasets, the async approach is required to ensure full record retrieval. The process involves polling /api/v2/analytics/knowledge/aggregates/jobs/{jobId} until the status is complete, then requesting the payload via /api/v2/analytics/knowledge/aggregates/jobs/{jobId}/results.
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