Fixing Data Truncation in Storytell’s Feedback Aggregation

Overview

Storytell’s aggregation system is designed to provide users with a comprehensive analysis of their data, enabling them to extract meaningful insights from various Collections. However, a recent issue led to incomplete data retrieval—only 17 results were returned instead of 74 when querying multiple Collections. This discrepancy was first flagged by a user, prompting an in-depth investigation. We traced the root cause to a truncation mechanism in our aggregation logic that was inadvertently filtering out valid results. Here’s how we diagnosed the issue, implemented a fix, and validated the solution.

Investigating the Issue

User Reports & Initial Observations

The first sign of the issue emerged when a user reported that Storytell’s matrix table analysis was not returning all expected results. Despite the UI displaying 74 conversation assets, the backend aggregation engine only returned 17 records. Given that aggregation is crucial for accurate data interpretation, this inconsistency warranted immediate debugging.

Debugging & Root Cause Analysis

To pinpoint the problem, we took a systematic approach, analyzing the data retrieval pipeline, SQL queries, Collection hierarchy, and API request logs.

SQL Query Validation

To validate data integrity, we ran a control plane SQL query. The results showed a mismatch between the number of expected and retrieved assets, confirming inconsistency between UI representations and backend aggregation.

SELECT COUNT(1) FROM myTable WHERE column1 = 'this value';

• The query returned only 20 assets, despite the UI displaying 74.
• This suggested a failure in merging nested Collections correctly.

Collection Hierarchy Analysis

The affected user query involved multiple nested Collections under a parent Collection called User Feedback. The expected behavior was that assets from the child Collections would be included in the aggregation:

• Collection 1
• Collection 2
• Collection 3

Although the UI successfully aggregated these results, the backend logic failed to merge all assets into the parent Collection’s result set.

Payload & Logging Analysis

To rule out API request errors, we examined JSON payload logs. The logs confirmed that the request was structured correctly and included all relevant Collections. Since the API was correctly requesting data, the issue had to reside further downstream in the aggregation process.

{
  "kind": "message_prompt:v2",
  "scope": {
    "collectionIDs": [
      "collection_cuqfs8q9io6g00f3k1j0",
      "collection_cuqgaki9io6g00dd31fg",
      "collection_cur6ot29io6g00ca9ehg",
      "collection_cuqfsnq9io6g00f3k2eg"
    ],
    "assetIDs": []
  },
  "prompt": "Analyze all the provided feedback and identify three primary concerns."
}

Identifying the Truncation Mechanism

By analyzing system logs and executing real-time debugging, we discovered a truncation mechanism within the aggregation pipeline. Originally introduced to optimize performance, this mechanism imposed a limit on results when multiple nested Collections were queried. While designed to prevent excessive data retrieval, it inadvertently caused data loss, leading to incomplete query results.

Implementing the Fix

Adjusting the Aggregation Logic

Once we identified the root cause, we made adjustments to ensure the system aggregated all valid results across parent and child Collections. The fix involved removing the truncation mechanism while maintaining query efficiency.

Code Fix: Removing the Truncation Mechanism

The truncation logic was removed to prevent premature filtering of results. This update ensured that assets from all relevant Collections were fully aggregated before applying any additional processing steps.

if (results.size() > maxResultsLimit) {
    // Previously, results were truncated to 'maxResultsLimit'
    // Code to trim the list
}

Updated approach:

// Truncation removed to support full aggregation across parent and child Collections
// Log.debug("Truncation removed: Total results = " + results.size());

Validating the Fix

Functional & Performance Testing

Following the fix, we conducted rigorous testing to validate system behavior:

• We re-executed the affected query and confirmed that all 74 assets were retrieved as expected.
• SQL query results aligned with UI representations, indicating correct aggregation.

Monitoring & System Observability

• Internal monitoring tools verified that truncation no longer impacted aggregation.
• We introduced real-time observability enhancements to detect potential aggregation inconsistencies before they affect users.
• No unexpected performance regressions were observed post-fix, ensuring system stability.

User Feedback & Performance Metrics

• Users confirmed that Storytell now retrieves complete datasets.
• Query execution times remained stable, with no noticeable increase in response times.

Lessons Learned & Next Steps

Key Takeaways

• Hierarchical Data Aggregation: Issues related to nested Collection retrieval require careful testing to ensure complete data aggregation.
• Proactive Monitoring: Enhancing logging and observability can help detect and resolve aggregation discrepancies before they impact users.
• Validation of Optimization Techniques: Performance enhancements such as truncation limits should be thoroughly tested to avoid unintended side effects.

Next Steps

To further strengthen our aggregation process, we are taking the following actions:

• Enhance automated test coverage to include multi-level Collection aggregations.
• Expand real-time monitoring dashboards to track result completeness across query layers.
• Continue refining aggregation logic to optimize performance while ensuring data completeness.

By addressing this issue, we have strengthened Storytell’s data retrieval pipeline, ensuring more accurate and complete insights for users. Moving forward, we are committed to continuous improvements in validation, monitoring, and query optimization to maintain system reliability.